Award Recipients: 2021 Exploration

Viruses are the most abundant and diverse biological entities on Earth, and possibly contain homologs of all the planet's genetic information.[1] Although viruses are a small fraction of planetary biomass, their overwhelming presence affects most, if not all, organisms. For example, every second an Avogadro's number of viral infections kills about 20% of marine microbes-a population that produces half of the oxygen on Earth-underscoring the critical role of viruses in driving biogeochemical cycles.[1] However, surprisingly little is known about the metabolic capacity of viruses or how they influence metabolism of host organisms. For instance, natural products, or secondary metabolites, represent one of humanity's most impactful discoveries and span antibiotics like penicillin to herbicides like phosphinothricin. While most of these molecules are of plant, fungal, or bacterial origin, they occur widely across the tree of life.[2] Surprisingly, despite their vast diversity and abundance, viruses have been overlooked as a genetic reservoir of natural product biosynthetic capacity. We intend to address this major gap in knowledge using a three-pronged approach. First, computational approaches will identify candidate natural product-encoding viral genes. Second, we will test the ability of viruses (i.e. bacteriophage) to influence bacterial natural products biosynthesis. Bacteria are known to possess many `cryptic' or `silent' natural product biosynthetic genes clusters that are not expressed under normal laboratory conditions. We hypothesize that phage may play an important role in awakening these clusters and coaxing bacterial production of new natural products. Third, we will evaluate gene functions and metabolic products identified from the first two activities. By identifying new metabolites encoded by viruses, the proposed research potentially represents an entire new field of research that may lead to new medicines and biocatalysts.

1. Suttle CA (2013) Viruses: unlocking the greatest biodiversity on Earth. Genome 56:542.

2. Medema MH, de Rond T, Moore BS (2021) Mining genomes to illuminate the specialized chemistry of life. Nat. Rev. Genet. DOI: 10.1038/s41576-021-00363-7

The aim of this proposal is to pioneer and investigate a unifying non-equilibrium physics understanding of human physiology and health, including the impact of aging, exercise and heat stress.

The physical underpinnings of physiologic processes are vitally important, yet unexplored. Recent developments in non-equilibrium thermodynamics explain how order is spontaneously created in nature. While the Second Law states that entropy will always increase, the recently dubbed Fourth Law of Thermodynamics states that a system will preferentially choose the path of greatest ascent of entropy, and the Maximum Entropy Production Principle highlights how complex non-equilibrium systems seek states that maximally produce entropy. Ordered structures spontaneously form and perpetuate (e.g. a whirlpool) if they continuously dissipate energy gradients, thus producing entropy. Similarly, we must continuously metabolize O2 to CO2 and export heat to our environment, producing entropy to survive. Entropy production is continuously required for life, increases in childhood, decays with aging, and ceases when we die.

We hypothesize that health is characterized by robust entropy production at rest combined with the ability to further elevate it in response to exercise or heat stress (i.e. both function & adaptability). Complex vital sign variability is hypothesized to correlate with the difference between basal and maximal entropy production. Impaired entropy production and variability is hypothesized to reflect illness.

To evaluate these hypotheses, we will pursue the following novel experiments: 1) measure entropy production in healthy young (<30) and older (>60) subjects, with and without illness (e.g. diabetes), observed during rest, heat-stress and exercise, while continuously monitoring vital signs, heat production, oxygen consumption and entropy production; 2) determine if heart, respiratory rate and blood pressure variability are useful to monitor entropy production; and 3) lead international roundtable discussions on understanding the non-equilibrium physics of physiology.

A world-class multidisciplinary research team, co-led by a clinician scientist, physicist and kinesiologist, has the combination of prior theoretical research, novel tools (i.e. human calorimeter), software (e.g. multiorgan variability analysis), personnel and leadership to significantly advance our understanding of physics, physiology and medicine, thus leading to improved care.

An Urgent Need: Canadian women consistently report low levels of mental health and a failure of the mental health care system to fully meet their needs. The Covid-19 pandemic has dramatically elevated women's rates of mental illness while compounding isolation and barriers to services. Women with mental illness, particularly at times of crisis, are likely to interact with a range of fragmented crisis services and are disproportionately represented in their use of and engagement with emergency and social services. In addition, women who interact with the criminal justice system have significantly higher rates of mental illness. All these services exist within an institutional framework which is reactionary, too often upholds a power imbalance, and silences the voices of the women being served. Not only does the current fragmented system fail to address the needs of these women, but also it often violates the human rights of this vulnerable population.

Risk and Reward: To address the specific needs of this population and the challenges of mental health service provision, we will 1) co-create a Radical Mental Health Doula (RMHD) curriculum with our partners (I.e. women with mental illness, service providers, community partners across sectors, and interdisciplinary researchers) 2) train a cohort of RMHDs and 3) pilot the implementation of RMHDs within the current system. We use a transformative, grassroots approach derived from the Radical Doula model, beyond the traditional scope of childbirth, focused on diversity, intersectionality, inclusion and social justice. RMHDs will act as advocates and connection points between services, providing education, continuity of care, and individualized support. The project uses an interdisciplinary and genuinely participatory approach from the onset. The reward will be a co-developed curriculum, a tested model and a cohort of trained RMHDs that will provide personal, individualized support for women with mental illness. As a proactive community resource, the involvement of RMHDs could reduce crises and the requirement for intervention by healthcare and social service providers and the criminal justice system. This innovative approach will privilege the voices of and advocate for the rights, needs, and wishes of women with mental illness. Funds acquired through this cost-cutting measure could be redirected to the funding of RMHDs while freeing up critical professional resources.

It is estimated that 10-25% of memory and learning disturbances in children have their origins in fetal life. Many cognitive deficits in children are related to in utero exposure to maternal environmental factors (i.e., diet, infection), particularly during the third trimester, a period of exponential fetal growth and when perceptual abilities come online. While environmental factors have different aetiologies, a shared feature is adverse cognitive outcomes, suggesting a common neural pathway. Functional and structural development of the fetal hippocampus, a key region for memory, may be selectively impacted; yet little research is available on its typical prenatal development.

Ultra-fast magnetic resonance imaging (MRI) protocols that capture the moving fetus have advanced and permit the characterization of fetal brain structure. Functional development of fetal memory systems is challenging to study, but examining behavioural responses to new events, an elementary form of memory, has been achieved in fetuses. Previous fetal-memory studies primarily used lab-generated vibration or auditory stimuli, with responses habituating over time as an indication of memory. However, maternal voices are naturalistic. Newborns can recognize their mothers' voices, and this is associated with a robust `neural signature'. Maternal singing can activate fetal auditory brain regions. We hypothesize that maternal singing is an optimal stimulus to study fetal memory and hippocampal development.

To identify sensitive windows for fetal memory system development, we propose an MRI study of healthy fetuses (n=75) at two time points during the third trimester. Mothers will sing the same vs. novel songs during functional MRI. Newborn hippocampal development will be assessed with MRI and memory abilities will be assessed at 12 months to address our objectives:

1. To determine if maternal singing of the same vs. novel songs is associated with decreased hippocampal activation, characteristic of neural habituation.
2. To ascertain whether decreased fetal hippocampal activation is predictive of enhanced hippocampal maturation and neural responses in the newborn.
3. To determine if newborn hippocampal maturation is predictive of 12-month memory outcomes.

Through better characterization of developing memory systems, this will serve as a model that can be applied to study atypically-developing fetuses who are high risk for memory deficits and inform prenatal health guidelines.

Combating global warming caused by increased atmospheric CO2 concentrations is a grand challenge in the 21st century. To limit the global temperature increases to 2 °C, set in the 2015 Paris Agreement, enhanced carbon capture materials are urgently needed. Considering the scale of the problem, any material used to capture CO2 must be regenerated and used in a cyclic manner, otherwise, its global supply will exhaust rapidly.

CO2 capture processes typically involve pressure or temperature swing adsorption cycles. However, currently used materials do not exhibit the combination of high selectivity, capacity, longevity, and low regeneration energy, required for large-scale CO2 capture. In this project, a different approach will be taken towards the development of CO2 capture materials wherein photoactivity is the main driving force for CO2 capture and release for its subsequent utilization. Combining the unique electronic properties of CO2 molecule with the differences in the activity of the catalyst in the presence and absence of light, a novel approach will be provided to selectively adsorb and desorb CO2 from the mixture of gases usually found in power plant flue streams.

First, a genetic algorithm-based machine learning approach coupled with density functional theory analysis will be used to search for materials that capture CO2 and subsequently release it by generating high-energy electrons in the presence of light. The materials that are identified to have appropriate binding energies with CO2 in the presence and absence of light will be fabricated and tested. Specifically, nanostructured metal-based hybrid materials will be investigated. These metallic nanostructures will be supported by mesoporous supports that have an exceptionally high surface area and can enable a high degree of light penetration. Further, considering anthropogenic CO2 emissions are approaching 40 GtCO2 annually, the techno-enviro-economic assessment will be performed to evaluate the environmental and economic viability of implementing the discovered CO2 photo capture materials on a large scale.

The proposed research is high-risk, as it involves translating fundamental knowledge obtained from advanced computational research into a material that exhibits unprecedented CO2 capture properties. Nevertheless, if successful, this project will provide the long-sought affordable, efficient, and environmentally benign photoswitching materials for CO2 capture and release.

Biomarkers are objective and quantifiable measurements of biological processes utilized in clinical trials or clinical practice to diagnose diseases, quantify disease staging and predict clinical outcomes. As biomarkers predict the emergence of clinical manifestations and confirm the presence of disease pathophysiology without clinical outcomes, they become essential for precision and personalized medicine by staging the disease process, assessing the effects of interventions, at individual levels, independently from clinical outcomes. Despite all progress, existing novel biomarkers for many diseases still require better sensitivity, specificity and predictive power necessary for accelerating clinical trials.

Our long-term objective is to develop innovative technologies that could significantly improve the early diagnosis and treatment outcomes of various diseases through precision medicine. The specific hypothesis is that an innovative multi-modal approach, combining artificial intelligence (AI) with novel terahertz (THz) sensing technology named the THz chemical microscope (TCM), is well suited for this purpose. The TCM uses THz radiation to read out the binding and thus concentration of the targeted biomarkers in aqueous samples.

To this end, the PIs will develop and apply this multi-modal approach to AD patients. AD is the most frequent age-related dementia characterized by a progressive accumulation of protein aggregates and neurodegeneration. Over 747,000 Canadians and 44 million people worldwide are living with AD or another dementia, making the disease a global health crisis. Unfortunately, there is currently no simple way to detect AD. At present, AD is first identified based on clinical signs such as progressive memory loss. The diagnosis is then confirmed by a positron emission tomography scan - an expensive medical imaging technique. Alternatively, lumbar puncture, an uncomfortable procedure, can also sample the biomarkers of these proteins. To this end, the short-term objective of the proposed research is to combine AI and the TCM to develop a minimally invasive technique to promote precision medicine in AD. In this proposal, we will improve and use the TCM to rapidly and simultaneously measure the concentration of multiple biomarkers in the patients' samples (blood and saliva). Then, AI will be used to unravel the complex combinations of biomarker signals that could correctly diagnose the progression and sub-types of a disease.

Gynecological cancers account for ~12% of all new cancer diagnoses among US women. Among gynecological cancers, ovarian cancer results in the highest mortality and is the fifth leading cause of cancer-related deaths among women. The prognosis for ovarian cancer patients is often poor, and new therapeutic options are urgently needed.

The field of evolutionary developmental biology (evo-devo) has uncovered a highly conserved `genetic toolkit' that regulates the development of all animals, as divergent as humans and honeybees. Bee societies produce an inhibitory pheromone called `Queen Mandibular Pheromone' (QMP) that induces cell death (apoptosis) in worker ovaries to inhibit them from reproducing. Remarkably, QMP also inhibits ovary development in distantly related animals.

Our idea is to integrate evo-devo, behavioral and chemical ecology, and oncology to test the novel hypothesis that honeybee QMP can inhibit proliferation and induce apoptosis in human ovarian cancer cells, in much the same way that it suppresses ovarian development in worker honeybees. Success in this project will uncover an entirely new class of chemotherapeutics to fight ovarian cancer.

Aim 1: Test anti-tumorigenic potential of QMP in vitro: we will determine whether synthetic QMP and its individual major components inhibit proliferation and induce cell death of ovarian cancer cell-line subtypes. Aims 2-4 will build upon positive results: we have preliminary data showing that QMP decreases survival of ovarian cancer cells in vitro.

Aim 2: Identify targets and downstream effectors of QMP (or its components) responsible for its anti-tumorigenic properties: using transcriptomics and mass-spectrometry, we will identify genes and proteins in ovarian cancer cells that change their expression in response to QMP (or its components).

Aim 3: Test anti-tumorigenic potential of QMP in vivo: we will determine the ability of QMP (or its components) from Aim 1 & 2 to reduce tumor outgrowth and increase overall survival using an orthotopic xenograft mouse model of ovarian cancer.

Aim 4: Test for conserved mechanisms that suppress unregulated growth and reproduction in complex biological systems. Using gene expression and behavioral analyses, we will test whether genes and proteins responsive to QMP in cancer cells are similar to those that induce ovarian cell death in bee societies, as predicted from evo-devo.

La radiographie et son pendant 3D, la tomodensitométrie (TDM), comptent parmi les modalités d'imagerie les plus utilisées pour leur capacité à produire rapidement une image structurelle d'un sujet, et ce, à un coût très faible. Cependant, la TDM expose les patients à une dose importante de radiation de rayons X et des études en démontre des effets néfastes à long terme, incluant des mutations génétiques pouvant mener à des cancers. Pour cette raison, ces radiations ne sont utilisées qu'en ultime recours en pédiatrie, qui actuellement se prive de capacité diagnostique faute d'une dose considérée trop importante pour des enfants.

Une nouvelle technologie basée sur la mesure du temps de vol (TdV) des photons X entre la source et les détecteurs laisse entrevoir une percée majeure en termes de réduction de dose dans certaines configurations de radiographie et de TDM. Idéalement, une mesure temporelle du TdV des photons X individuels à une résolution de 10 picosecondes devrait être obtenue pour tirer pleinement profit de cette technique, ce qui n'est actuellement pas atteint technologiquement. De plus, afin de minimiser le temps de prise d'images, il faut également compresser drastiquement les quelques 120 téraoctets par seconde de données anticipées à quelques Gbit/s, et ce, en temps réel et à une très faible consommation, une prouesse technologique où seule l'intelligence artificielle semble prometteuse. Ce projet de recherche s'intéresse au développement d'un module de détection à base de métamateriaux et graphèmes qui seraient capables d'atteindre ces performances. Ces développements technologiques seront encadrés par des chercheurs en génie, en médecine et en sciences humaines qui s'assureront de l'acceptabilité médicale et sociale du produit qui en résultera, en particulier pour l'imagerie pédiatrique, qui sera une application importante pour laquelle il y a une forte réticence à utiliser les rayons X.

Ce projet soutiendra plusieurs personnels hautement qualifiés dans un environnement interdisciplinaire. Outre les retombées académiques, les développements technologiques pourront percoler vers d'autres modalités d'imagerie comme la tomographie d'émission par positrons, les lidars et le domaine de l'automobile. Cependant, ces retombées seront minimes comparées aux retombées médicales et l'exploitation potentielle de la radiographie en pédiatrie et pour des traitements longitudinaux exigeant des examens radiologiques fréquents.

Large-volume versus high-resolution information is an inherent conundrum in all domains of research that rely on imaging; you can achieve either one, or the other, but never both. The incentives to increase resolution while keeping large context are many, from comprehensive analysis of basic biological phenomena, to maintaining radiation safety standards in imaging, to preserving the integrity of rare specimens of cultural value. However, extrapolating nonexisting spatial information has always been an ill-posed problem because its solution is not unique. This paradigm changed with the arrival of deep learning using neural nets. Although there is ample literature on upscaling single images using super-resolution convolutional neural networks (CNN), recurrent neural networks (RNN) or generative adversarial networks (GAN), most algorithms are designed for (and validated on) synthetically downsampled 2D images. Here we merge expertise in deep learning, tomographic X-ray imaging, biomineralization, biological anthropology, and dental radiology to design and validate an open-ended upsampling algorithm using 3D images of historical (ancient mummies), clinical (dental cone-beam computed tomography) and basic science (bird eggshell) samples. Unique to our project is the availability of original multi-scale 3D image sets that span multiple resolution/volume scales and which can be accurately superimposed (registered) in 3D, and can be expertly segmented (having meaningful features identified and assigned to the target class on a voxel basis). Images are hierarchical, meaning that the neighborhood of local features is as important as the features themselves; indeed, that is the basis of the CNN operation which identifies and labels features based on their context (and the context of context). GANs include a generator algorithm that constructs artificial features, and a discriminator algorithm that compares artificial and true features: iteration of the two leads to convergence, and to construction of realistic artificial spatial information. By applying GAN-CNN to a low-resolution/large-volume image using a high-resolution/low-volume image as ground truth, we will achieve 3D image upsampling xn. To circumvent the inevitable increase of the data size (xn3) we will implement a parallel segmentation algorithm that reduces voxel depth, because the ultimate objective is the segmentation of upsampled images. Finally, we will explore the limit of image upsampling in 3D.

HIGH REWARD: To meet the demands of society for environmental protection, sustainable growth, and safety it is critical to design improved materials including their processing. Efficient development cycles require predictive computational models that also account for the in-service performance, e.g., to reliably predict material failure. Increasingly, such tools incorporate atomic scale phenomena down to electrons but linking to macroscopic mechanics, such as strain. Here, a revolutionizing development is to build interatomic potentials from universal approximators fitted to electronic structure models. These "machine learned" interatomic potentials (MLIPs) promise quantitative but computationally efficient models for interatomic forces and have the potential to revolutionize materials design as well as other disciplines, as diverse as biochemistry.

HIGH RISK: Significant challenges remain to make good on this promise: The computational cost of MLIPs is still too high for routine large-scale simulations. Moreover, crucial physics and chemistry such as electrostatics, charge-self-consistency, dispersion, or magnetism are yet to be treated adequately. Tackling these challenges requires novel and untested methodology from diverse disciplines.

OBJECTIVE: We will confront the most significant challenges in this field by developing new methodology hand in hand with cutting edge materials modelling applications, including but not limited to nano-engineered metals and alloys, rare earth based magnetic materials, and emerging amorphous materials.

METHODOLOGY: (1) Novel representations of potential energy landscapes will be developed, merging best-in-class ML and mechanistic models. Insight from approximation theory, mechanics and chemistry will be combined to construct interpretable representations leading to low-dimensional, highly efficient and transferable models.

(2) Training data collection will be automated guaranteeing excellent stability, generalizability and uncertainty quantification. This will be achieved by combining the representations from (1) with state-of-the-art Bayesian techniques.

INTERDISCIPLINARITY: The challenges and methodology require a tightly integrated interdisciplinary approach, merging electronic structure, mechanics, machine-learning and computational mathematics. Our team will consist of mathematicians, material scientists, computational scientists, engineers, and physicists.

Dementia affects cognitive function, but the impact on the person depends on their context. The psychosocial environment, for example, is vital in determining how risk factors for dementia are addressed and, once symptoms emerge, how care and treatment decisions are made. Much research has targeted the neurobiological sequelae of dementia, and parallel work is done on the psychosocial factors that modify risk and progression. Our objective is to merge these two streams using computational modelling. Dynamical systems theory will guide the model development, considering the different spatial and temporal scales over which neurobiological and psychosocial processes evolve and interact.

Our research approach will entail:

A) Updating the existing neurobiological platform to reflect better dementia-related cellular changes and their expression in the individual

B) Construct cognitive models of the interaction between affected and spared mental functions and relate to the modelled neural substrates

C) Derive group-structured models of population dynamics based on quantitative and qualitative identification of key psychosocial factors that determine risk and response to disease progression.

D) Integrate a, b, and c, using probabilistic causal models such as Bayesian networks to account for uncertainty in joint probability distributions that link scales.

The idea that there are biological and social determinants of dementia risk and progression is not new. What is novel with our proposed work is the explicit analytic base to integrate the multiple determinants and ascertain their dependencies. The model then enables forecasts of the effects of biological and social interventions, weighing the cost and benefits of each. Moreover, the multiscale aspect of the model supports a deliberate estimate of the combined effects of interventions, which is impossible in previous models. If successful, the platform will be an essential tool for integrating quantitative and qualitative research and potentially a tremendous asset in clinical decision support that accounts for the entirety of the patient's needs. The significance of the platform for addressing the societal challenges of dementia is evident. Beyond that, the multiscale approach can be extended to other biological and social applications where dynamical systems interact.

To the White Institution, i.e., institutions where the culture of White Supremacy predominates, the Black Body is a Dark Continent, a body that has historically inspired fear, considered ignorant and inhuman and denied the rights of other human beings. This Dark Continent had a previously fixed geographic location in Africa but is now spread across the globe, especially to the West via the institution of slavery. Unfortunately, the stigma attached to these bodies and the unacknowledged plunder of The Continent itself as a place of Darkness remains deeply ingrained in the minds and institutions of White Supremacy. This research seeks to inspire a radical shift in the thinking that supports the current system of inequity, maintains structural racism, and prevents a redefining of Blackness through Black lenses. We argue that an historic separation of Black families, and the unmitigated violence perpetrated against them, while pillaging their worth, has resulted in a profound fracture in communities, individual bodies and inherited knowledge systems. Our main objectives in this research are 1) to begin healing this fracture by facilitating better connections between our peoples locally, nationally and internationally, and 2) reimagining our past, present and future through a more complex notion of Black performance; and by performance we mean enacting imaginative futures in economic, social and scientific spheres through actions that range from human and traditional expressive behaviour to computation, efficiency and optimisation in institutional, social and digital systems. We will utilise tested and novel transdisciplinary, transcultural and transnational methodologies that foster dialogue; reimaging and co-creation between artists, scientists and humanist scholars. In doing this, we aim to break free of the largely White Research Industrial Complex that puts a stranglehold on scholarship, pedagogy and administration as we interrogate the artificial boundaries that restrain our creativity. This 2-year initiative will: 1) Convene "spaces" and explore ways of knowing that re-historicize our past. 2) Collectively engage in "re-choreographing" our collective futures to heal a fractured past, reclaim our histories, and invest in ways of knowing that are animated by our multiple and collective conceptions of Blackness. 3) Inspire new connections between disciplinary, cultural, and community spaces, and 4) Disrupt the White Gaze that always wants to be catered to.

As a major source of power, natural gas (NG) is extracted and transported to every corner of our society, where leaks are an important source of methane emission. Detection, localization, and quantification of NG are major challenges for greenhouse gas emission reduction programs as the emissions are fugitive, colorless, and many but small. The current practice uses a mobile methane detector or infrared (IR) camera to identify and locate the leak point, then uses a high-flow meter to measure the emission rate. However, this approach is labor-intensive, not in real-time, and may miss many smaller leaking points. It would be highly desirable if the emission rate can also be quantified by IR imaging to make leak monitoring continuous, automatic, and real-time. However, the appearance of NG plumes in IR imaging is affected by many factors, such as flow rate, distance, background, and dispersion behavior. In addition, those factors are nonlinearly related, which makes quantification of flow rate from IR images very challenging. Thanks to the rapid development of machine learning (ML) techniques and the high computing speed of microcomputers, quantitatively relating nonlinear factors is made possible. Therefore, we propose marrying the techniques in dispersion modeling, image analysis, and ML to develop an IR imaging-based method to automatically identify and quantify NG leaks.

This study involves three subtasks. 1. Plume detection. We will use multi-modality and non-rigid polymorphic object analyses to isolate NG plumes from their background and characterize factors relating to flow rate. 2. Determination of factors for ML. We will use dispersion modeling to construct synthetic parameters (involving plume distance, plume size, turbulence, temperature, humidity, wind, etc.) related to flow rate. 3. Controlled release and ML model construction. The latest ML algorithms will be tested to relate the known flow rates with imaging, spatial, and meteorological parameters and optimize the ML model by adjusting parameter selection and algorithm structure.

Although IR cameras have been used for leak detection by many facility operators, there have been no systematic studies on the effectiveness of IR cameras for quantifying leaking rate. Integrating the traditional techniques in IR imaging and dispersion modeling, augmented with the introduction of novel ML analysis, will allow for a new perspective and open doors for early detection and quantification of NG leaks.

Traumatic events such as natural disasters, rape, car accidents, pandemics, social stigmatization, and warzone exposure are experienced by 70% of the population and are potent etiological factors in mental illnesses such as posttraumatic stress disorder (PTSD). With a lifetime prevalence of 9% in Canada, the seriousness of PTSD was recognized by the Federal Framework on PTSD Act, which states "all Canadians can be at risk for PTSD." Although the risk of experiencing trauma is universal, access to mental health facilities is not as widespread. PTSD diagnosis and treatment require clinical consultation that uses expensive neural imaging and stimulation equipment. However, access to these mental health services is limited by socioeconomic variables, language barriers, and proximity to urban areas.

These factors have generated a section of the population whose mental health needs are underserved. To address this issue, we propose non-invasive, scalable, and low-cost methods to diagnose and treat PTSD. Our approach will integrate recent findings in the fields of ophthalmology and Alzheimer's disease. We build upon the discovery that pupil dilation is a physiological marker of PTSD and we leverage the finding that non-invasive rhythmic sensory stimulation (RSS) in mouse models of neurodegenerative disease activates the neural structures that are impaired in PTSD. Using a mouse model we will validate pupil dilation as a marker of fear memory and develop a RSS treatment that reduces the dilation response and fear expression. To establish a mechanistic understanding of RSS we will characterize neuronal circuitry dynamics in neuronal populations that are implicated in PTSD following RSS treatment. We will compare these measures with pupil dilation throughout experimental phases to assess RSS efficacy, and adjust treatment on an individual basis. Together this will build the translational bridge for individual-centred treatment of PTSD.

Our proposed methods represent a step-change in PTSD care that have the potential to allow early identification of subclinical individuals along the severity spectrum, provide flexible treatment regimes, and broaden access to mental health services. Our team synthesizes expertise in clinical treatment, physics, mathematics, neuroscience, and optometry to develop novel, accessible, and effective methods to provide care that will improve the quality of life for trauma victims across diverse populations.

Canadian immigrant populations come from diverse ethno-geographical backgrounds and exhibit differences in their culture and understanding of health and wellness. It is imperative to collaborate and empower these diverse communities by allowing them to become champions of their own health & wellness. Conventional approaches taken by health or social research sectors are largely project-focused data collection. However, we believe by enabling the immigrant communities, representing more than 1/5th of the total Canadian population, to build their health data cooperatives (HDC) has the potential to promote health equity through empowerment (enhance individual competence & self-esteem, increase community action & participatory learning exercises). HDC is a concept of a collective where health-related data (e.g., health condition, lab results, data generated from mobile health apps/smartwatches, social determinants of health data, etc.) are integrated, stored, used, and shared under the control of the cooperative members. The novelty of this proposed project is enabling a grassroots community-level HDC led by socially vulnerable populations. Having full control and ownership of their health-related data, the HDC empowers the participants to make informed decisions about their health, advance the quality of care, and promote health reform by improving community engagement. Furthermore, individuals and the community at large may profit both financially and/or in-kind contributions from sharing the health data with health-related establishments including pharmaceutical companies, research organizations, and government survey services.

We propose to explore the creation of community based HDC in an immigrant community, considering ethical & legal frameworks, organization management, data security, privacy, computing science, knowledge mobilization, and community development.

The goal of this exploration grant is to achieve the following interconnected objectives:

(I) To build a diverse interdisciplinary team comprised of immigrant-community members, academics, policymakers, and non-governmental organizations on the initiative of HDC

(II) To undertake a comprehensive environmental scan, including stakeholder analysis to conduct key-informant interviews, gather feedback, and summarize existing models of cooperatives that will inform this initiative

(III) To conduct early-stage assessments determining sustainability and scalability of the HDC initiative

Exposure to environmental stressors during pregnancy influences childhood lung health and increases chronic lung disease risk by altering cell development and function. The route of transmission from outside environment to the developing lungs is currently unclear. Fetal circulation is important, but the developing lung receives less than 10% of the cardiac output. During development, the lungs do not participate in gas exchange but are filled with a fluid that can exchange contents with the surrounding amniotic fluid. Given the close proximity of the developing lung and amniotic fluid, perturbations in amniotic fluid composition may represent an unexplored mechanism of transmission from the external environment to the developing lung. Problematically, there is currently no research investigating this important research question. By uniting three disciplines (gynecology, respiratory physiology, proteomics), we will explore how smoking change the amniotic fluid inflammatory composition and whether these changes influence airway epithelial cell function in culture. Using clinical samples from term pregnancies and unbiased proteomics, we will characterize smoking induced changes in amniotic fluid inflammation. We will also develop new cell culture models to understand if alterations in amniotic fluid inflammation influence airway epithelial cell development and function.

Basic and health sciences, and clinical medicine have a history of collaboration, but the scarcity of interdisciplinary teams with a focus on uniting the maternal-fetal environment and the respiratory system has contributed significantly to this important knowledge gap. Our team will integrate expertise in lung physiology, cell biology, and reproductive medicine to understand how the amniotic fluid acts as an intermediary between the external environmental and the developing lungs. A lack of published research and poor cell models of the airway-amniotic fluid interface makes this project high-risk. However, understanding the role amniotic fluid plays in linking maternal smoking to the developing lung allows us to explore targeted public health initiatives to reduce the burden of chronic lung disease in the next generation. These policies can reduce mortality and morbidity associated with chronic lung disease, representing a high-reward potential for this proposal. Finally, our team will develop tools and build capacity to enable research into other environmental stressors during pregnancy.

Social interactions provide the foundation for understanding the world and are critical for healthy social and cognitive development. Children with neuromotor disabilities experience limited social interactions because of impaired speech and mobility. As a result, these children suffer negative consequences including a limited ability for pragmatic reasoning.

Pragmatic reasoning is the ability to process and convey information within an interaction context using cognitive frameworks informed from life experiences. It begins to develop in childhood through play and is honed as children act in their physical environment, and interact with others, in accordance with the expectations of society.

Technologic advances can offer children with disabilities enhanced autonomy, and yet its potential benefits with respect to pragmatic reasoning have not been studied. This research aims to enhance pragmatic reasoning in children with neuromotor disabilities by allowing them to control their environment in collaborative play using advanced robotic technology.

Our research approach will only succeed by bringing together experts in the fields of rehabilitation therapy and child development, computer science, engineering and education. Importantly, we will take a participatory approach to our research wherein children, parents and families will be active team members. This study is high-risk because we propose to assist children with neuromotor disabilities initiate and participate in interactions with their peers without disability by using robots in a new way: as extensions of the children themselves. We will first apply computer science approaches to the modeling of pragmatic reasoning for children with disabilities. Then, robots will interact with participants to learn their communication intentions. Finally, the robots will be used as proxies that provide extra modes of control through physical action and communication.

Robots that can extrapolate a child's intentions and assist in creating multimodal communication pathways, can improve the quantity and quality of social interactions. This work can generate scientific insight into pragmatic reasoning in children and could be transferable to other populations and communication domains wherein the traditional cues humans rely upon are limited. Our interaction model can be applied to support creation of new technologies for applications such as human-robot interaction in manufacturing and autonomous vehicles.

Appreciable evidence suggests gut microbiota interacts with the brain and plays a key role in pathogenesis of mental illnesses. It has been suggested that this interaction can be directly mediated through microbial metabolites such as neurotransmitters or indirectly through endocrine, immune or metabolic systems. For example, the brain signatures associated with depression have been negatively correlated with the relative abundance of Bacteroides, that can generate the neurotransmitter ?-aminobutyric acid. Yet, the mechanisms by which microbiota interact with the gut-brain axis and modulate mental health -a prerequisite for the development of evidence-based microbiota-targeted interventions- remain hypothetical. Currently used techniques to map microbial species/metabolites throughout the gastrointestinal tract are costly, invasive, lack specificity and sensitivity. Novel mapping techniques are necessary to close this knowledge gap and enable therapeutic applications.

Bioimaging stands out as a potential mapping technique for the intestinal microbiota/bioactive metabolites. If assisted by opto-magnetic sub-10nm nanoparticles (NPs), it is particularly appealing for such applications as the NP size scale matches that of the targeted biological features. Structural and functional mapping of the intestinal microbiota requires both excellent spatial resolution and deep tissue penetration, which current techniques such as magnetic resonance imaging (MRI) and UV/visible optical imaging lack. Lanthanide-based NPs (Ln-NPs) enabling near-infrared imaging have shown to be strong candidates to break this compromise. Additionally, they have sensing capabilities for temperature, pH or chemical species and can act as MRI probes.

Application of near-infrared bioimaging to characterize the intestinal microbiota/metabolites would provide high-resolution, spatiotemporal, and functional information that would be the foundation of future theranostics. Therefore, optics and physico-chemistry of Ln-NPs and biomedicine will be leveraged to enable opto-magnetic imaging of microbiota/metabolites. Combined with ex vivo hyperspectral microscopy and in vivo MRI, aptamer-functionalized Ln-NPs will allow specific targeting and localized single species/metabolite detection and imaging. This highly ambitious interdisciplinary approach and the associated insights have the potential to unlock new diagnosis and therapeutic tools using our biggest and yet least known organ, our microbiota.

Problem/challenge: Kidney and cardiovascular diseases, closely interlinked with each other and with mental health issues, profoundly impact the health and wellbeing of Indigenous Peoples. Exacerbated by diverse socio-economic, geographic, and educational factors, a health system based on colonial practices and policies, and a lack of care provider awareness of cultural traditions and healing practices, Indigenous patients are more likely to require end-stage treatment for these diseases, suffer disproportionately from depression and have substantially lower life expectancies. As Canada moves towards patient centred precision healthcare model, Indigenous Peoples risk being further left behind. In this model, understanding a patient's biological make-up, gender, ethnicity, cultural expectations, experiences, and lifestyle is essential. Without this information, and without understanding barriers to care, including the lack of trust between Indigenous patients and the current healthcare system, it is impossible to provide care effectively and equitably for these patients.

Our objective here, therefore, is to create an entirely new paradigm for Indigenous healthcare that integrates traditional ways (bundles) with modern terminology (precision health) to guide culturally safe and healthy decision-making, facilitate healing, and improve patient outcomes. This work will build on the knowledge and perspectives of patients, their families, elders and care providers from Alberta-based Indigenous communities, and a cadre of researchers representing expertise in medicine, public health, psychology, education and the arts. Together they will collaborate to develop unique and personalizable bundles of tools and networks that empower individual patients to make healthcare decisions that fit their disease experience and personal circumstances; enable knowledge transfer through Indigenous art and cultural traditions to tell a story of healing in the context of the patient and their community; and make policy recommendations to multiple levels of government in order to help modern (western) health systems adapt to Indigenous needs and make care providers aware of their role in facilitating a healthier Indigenous population. "By Knowing the Past in the context of Seeing Today we can Change the Path going forward," and apply this knowledge to facilitate disciplinary and nation-wide healthcare change.

The intracardiac nervous system (IcNS) may be critical in health and disease, but its integrative function across the whole heart has proven impossible to investigate, due to limitations of available experimental models and technologies. Forming a comprehensive understanding requires a novel, high-risk, interdisciplinary approach to allow for in situ 3D measurement and interrogation of system wide IcNS activity with cellular resolution, combined with the computational data integration for mechanistic insight.

Our objective is to develop an innovative multi-modal, multi-scale experimental-computational approach to define the mechanisms and importance of the IcNS for cardiac regulation and pathophysiology, specifically quantitative insight into IcNS:

1. Functional 3D interconnectivity, intracardiac signal processing, and communication with cardiac cells.

2. Responses to (patho-)physiological stimuli and their influences on cardiac function.

3. Structure-function changes in disease and with ageing.

To accomplish this, our interdisciplinary approach will involve:

1. (Patho-)physiological stress of young-to-old zebrafish hearts (in which the entire IcNS can be visualised and manipulated), while monitoring 3D cell-specific IcNS activity and IcNS-cardiac interactions using genetically-encoded fluorescent indicators and novel high-speed volumetric imaging.

2. Interrogation of individual IcNS contributors and interconnectivity using novel optogenetic techniques for regional, cell-specific manipulation, combined with 3D cell-resolution imaging of IcNS and cardiac structure.

3. Novel, data-driven computational models for structure-function simulations to gain experimentally inaccessible insight into integrative IcNS function.

This is project is novel and high risk, as: (i) it challenges the presiding paradigm that the IcNS is simply a `relay station' for central nervous system inputs; (ii) by developing and applying an innovative approach driven by technological advances that rely on interdisciplinary expertise, which will be widely applicable for future neuroscience and cardiac applications; and (iii) will push the boundaries to overcome prohibitive limitations for investigations of complex, integrative IcNS function. It is also high reward, as it will for the first time provide direct evidence as to whether IcNS circuits locally process, integrate, and feedback neuronal signals, a critical issue for (patho-)physiological cardiac regulation.

Background

Choroidal nevus, or a mole on the back of the eye, has an estimated occurrence of 6.5% in the adult population. Approximately 0.2% of these will transform into malignant cancer, called uveal melanoma. The consequences of this can be fatal. Of those diagnosed with uveal melanoma, 45% will die as a result of their cancer within the first 15 years. This mortality rate has not improved since the 1970s.

Early detection and management of lesions associated with uveal melanoma is vitally important. Diagnosis should be made by an ophthalmologists with a focus in oncology. However, there are very few of these practices worldwide, and referred patients face long wait times. Delays can result in significant tumor growth and subsequent degenerative vision, removal of the eye, or death as a result of metastasis.

Objectives

Our long-term goal is to improve access to care for uveal melanoma patients. Our unique team brings together ocular oncology, software engineering, and health services research. Collectively, we aim to:

1. Test different deep learning methods for the analysis of diagnostic images of choroidal nevi.

2. Develop and validate risk prediction algorithms for malignant uveal melanoma.

3. Develop patient and provider decision aids for referral to ocular oncology.

To date, the use of artificial intelligence to diagnosis eye diseases has been a "black box", making it difficult to clinically validate. Our collaboration will bring a new perspective to the field by opening that "black box" and making the previously inaccessible results open to clinical interpretation.

Approach

We will work with a Canadian ocular oncology program with access to Canada's largest clinical and diagnostic image database of patients with uveal melanocytic lesions. There are inherent risks associated with all three aims: 1) the proposed deep learning methods are novel and have not been applied to clinical and diagnostic images data of this nature and 2) the resulting predictive algorithms have never been translated for use by clinicians and patients.

Significance

Achieving these aims will have high reward for patients and the healthcare system. This will help the 2 million Canadians with choroidal nevi get diagnosed quicker and, for those with uveal melanoma, access to care sooner. For the healthcare system, this

will ultimately result in shorter wait times for patients to see an ocular oncologist through better triaging based on risk of malignancy.

Treatment resistant depression (TRD) occurs in 30% of patients attending hospital clinics and has a prevalence of 22% in Canadian community samples. Functional neuroimaging has provided evidence for abnormal neurocircuit function in major depressive disorder (MDD), which contributed to the emerging interest in deep brain stimulation of the subgenual cingulate gyri (SCG-DBS). Clinical trials for SCG-DBS have established safety and tolerability, however only approximately 50% of patients are treatment responders. While these results are encouraging and demonstrate the potential of SCG-DBS to improve quality of life, there is an exciting opportunity for therapeutic optimization to improve both responder rate and therapeutic gain.

Like most new DBS indications, clinical applications of SCG-DBS "borrow" the stimulation delivery paradigm of subthalamic nucleus DBS for Parkinson's disease (i.e. continuous high-frequency stimulation 24hrs/day). This is largely because many questions remain about the mechanisms of action of DBS (i.e. how it modulates neural activity). However, new work unequivocally demonstrates that the effects of DBS on neuronal activity, evoked responses, and brain oscillations vastly differ on a structure-to-structure basis and depending on the applied stimulation settings. Evidence in humans suggests that DBS can up- or downregulate neuronal output, amplify or suppress evoked fields and oscillations, and potentiate or depress synaptic transmission fidelity (i.e. elicit long-term plasticity; LTP).

Our primary objectives are: (1) to gain a complete understanding of the mechanisms of action of SCG-DBS and the possible local (i.e. within SCG) and cortical network neurophysiological phenomena that can be elicited in patients with TRD, and (2) to develop and test novel stimulation approaches to restore neurocircuit function in TRD; i.e. paradigms to elicit LTP or favourably modulate circuit-level oscillations. To accomplish these objectives, we will implant prospective patients with state-of-the-art medical devices with chronic brain sensing capabilities (i.e. Medtronic Percept PC) and utilize transcutaneous electroencephalographic recordings, in combination with sophisticated neuropsychological testing. Our proposal therefore represents a high risk, high reward endeavour which integrates the fields of biomedical engineering, neurophysiology, psychiatry, psychology, and neurosurgery in search of an optimized chronic treatment approach for TRD.

Analysis of high-dimensional data plays a key role in data-driven insights in a wide range of domains including natural sciences, engineering, and business. However, correct analysis often requires experience in specialized programming languages. This presents a significant barrier for users without the required training, including those with accessibility needs. Furthermore, the complex nature of such analysis makes even experienced user workflows error-prone, leading to a significant time and resource sink.

Concomitant with the rise of data science, applications of machine learning have led to multiple breakthroughs. For example, OpenAI's GPT-3 model has shown state-of-the-art performance on language tasks such as automated image captioning. Notably, GPT-3 has demonstrated an impressive ability to automatically generate computer code from commands in natural language. While this has the potential to significantly lower the barrier to entry across a range of computer programming tasks, it has yet to be applied in making data analysis more accessible.

Here, we introduce Accessible & Inclusive Data sciencE (AIDE) project that will pair machine learning with user experience research and inclusive design to significantly improve data analysis accessibility. We focus on noisy, high-dimensional biomedical data that requires advanced analytic methods to extract biological insight. As a proof-of-concept study, we will build on GPT-3 language models to automatically generate analysis code given natural language commands. We will begin by surveying the user experience and accessibility needs of biologists to uncover the precise requirements code generation models can best fulfil. Secondly, we will train the machine learning models and implement the resulting solutions in preferred environments. Finally, we will deploy and evaluate prototypes with the community, gaining feedback to iteratively improve the designs and quantify the extent to which such approaches increase accessibility.

This project represents the first interdisciplinary effort to improve the accessibility of data analysis by incorporating machine learning, user experience research, and inclusive design approaches. While initially focusing on biomedical data, there is extreme potential to expand to other analysis application domains that involve of high-dimensional noisy data. The broader impact of this project is to democratize data analysis by making it available to a broad range of users.

Cannabis legalization has heightened concern among health professionals about prenatal cannabis use and its potential negative impact on maternal and child health. Sociological theory supports that social context, in particular processes of social stratification and disadvantage, form a vital context that shapes health outcomes, and health behaviours. While some evidence exists for associations between prenatal cannabis use and select maternal and infant health risks, the complete contemporary social context of prenatal cannabis use and its potential direct and indirect impacts on maternal and infant health among cannabis consumers remain unexplored. Using a novel integration of sociological and epidemiological approaches, we will recruit a population-based stratified sample of 1500 pregnant Canadians, administer online questionnaires in early and late pregnancy, and 6 months postpartum, and link to electronic health data to achieve our study aims: 1. Describe the current social context of prenatal cannabis consumption in Canada including cannabis-specific attitudes and beliefs, lived experiences of chronic and pregnancy-specific micro-aggressions, and economic privations 2. Determine whether social-context mediates or modifies associations between prenatal cannabis consumption and maternal perinatal health and postpartum mental health (risks or benefits), and 3. Determine whether social-context mediates or modifies associations between prenatal cannabis consumption and infant cardiac and renal health up to 6 months of life. Previous research on prenatal cannabis use and maternal/infant health has controlled for a small number of mediocre proxy-measures of socioeconomic status as nuisance factors. Our study is high risk, because it employs both a novel collaboration between sociology and epidemiology and a novel analysis approach, which will provide a more complete understanding of the role of social vulnerability in relationships between prenatal cannabis use and maternal/infant health. Further, our results may reveal unknown benefits of prenatal cannabis use, challenging current knowledge. Our project is high reward, as it will contribute valuable new evidence of health outcomes associated with prenatal cannabis exposure, by showing whether previous findings of risk are attributable to social vulnerabilities or to cannabis. Results will provide a sociological framework for optimizing public health strategy to improve maternal and infant health in Canada.

The equine industry contributes $19 billion annually to the economy. Musculoskeletal injuries are common in horses, particularly repetitive-use injuries that put joints at risk for further degeneration during aging. This makes the horse an important focus of research as a patient, but also a unique and translational model for similar human conditions. Just as in human medicine, many treatments for chronic orthopaedic disorders are not evidence driven. Therefore, many place hope in unproven regenerative medicine approaches, yet, paradoxically, no suitable large animal model exists to critically investigate these "therapies". Despite this limitation, many of these approaches have made their way into equine and human clinical practices - promising much but delivering diverse results. Commonly, these groups are claiming bone marrow (BM) or adipose derived mesenchymal stem cells (MSCs) can repair cartilage, or modulate inflammation to promote intra-articular healing; however, little to no benefit over symptomatic treatments (i.e. anti-inflammatory drugs/rest) has been observed.

In addition to the lack of an animal model for complex intra-articular injuries of the knee, we suggest the variable efficacy of pre/clinical MSC therapy is in part a result from the use of multiple MSCs sub-types; each with differing therapeutic potential. Our data show that standard MSC cell surface markers are not sufficient to distinguish between MSC sub-types of varying therapeutic potential. Therefore, in this proposal, we will undertake a blinded/controlled pre-clinical trial to determine if BM-MSCs can improve functional regeneration of complex joint injury in horses; and will also identify/validate new MSC surface markers which can enrich for MSCs with the greatest therapeutic potential. To accomplish this our team of stem cell biologists, large animal surgeons and biomedical engineers will:

1) Validate our novel equine model of complex intra-articular stifle injury

2) Use unbiased quantitative proteomics to identify cell surface markers that are distinct between sub-types of equine BM-MSCs.

3) Determine the efficacy in autologous BM-MSCs in reducing disease severity and/or increasing functional outcomes in our equine model.

By validating an equine model of complex joint injury, we can unbiasedly determine if MSCs are an effective treatment modality worth further study for the non-surgical management of these all too prevalent injuries/diseases in horses and humans.

Proper functioning of proteins in a cell requires specific structural organization (conformation) of protein molecules. However, under conditions that are not fully understood, some proteins adopt aberrant conformations. This can result in severe disorders such as Alzheimer's disease, Parkinson's disease, or amyotrophic lateral sclerosis, for which no preventive treatment or cure exists. To develop a treatment, the underlying molecular mechanisms need to be understood in detail. A fundamental conceptual leap is provided by the novel paradigm of subcellular organization through liquid-liquid phase transitions of proteins and other biological polymers in a cell. However, it is poorly understood which biochemical factors drive the formation of biomolecular phase-condensates; what are their major structural and dynamical determinants; and what distinguishes functional phase-condensates in healthy cells from their aberrant counterparts that are implicated in these diseases. We propose applying a potentially transformative method of nanoplasmonics to analyze liquid-liquid phase transitions and accompanying condensation phenomena for proteins associated with diseases. We will fabricate hybrid architectures interfacing solutions of proteins of interest with surfaces of nanostructured plasmonic devices. Due to their ability to convert energy of visible light in different forms, plasmonic nanostructures can influence the way the light interacts with molecules adsorbed on their surface, and even induce photo-chemical changes. We plan to combine monitoring of proteinaceous phase-condensates via surface-enhanced Raman spectroscopy (SERS) with attempts to modulate the phase-condensation through plasmonics-driven photochemical stimulation. The proposal relies upon the cross-disciplinary expertise of the PI (nanofabrication, SERS biodetection) and co-PI (cell biology, protein folding diseases). In case of success, this combining of traditionally unrelated disciplines, cell biology and electro-optical engineering, will significantly enhance our capacity to detect, monitor and modulate condensation behavior of proteins. We also expect to discover key properties of aberrant proteinaceous assemblies in order to rationally improve preventive health care. The proposed activities will provide unique cross-disciplinary training as well as a safe, inclusive, and equitable environment to all participating group members.

Radiation medicine plays a critical role in the lives of Canadians for diagnosis and treatment. However, fundamental questions remain regarding the interactions of ionizing radiation with tissue and ensuing biological response. Advancement of knowledge is hindered due to the limited approaches available to assess radiation energy deposition (dose) and connect with response at cellular levels.

The proposed research will bring together expertise in physics, biology, and bioinformatics to develop a novel system for evaluating radiation energy deposited in cells and the associated cascade of biological events.  The physical component of the system will be comprised of a population of cells adjacent to a chemical dosimeter, namely radiochromic film.  An approach will be developed to culture cells such that they may be irradiated simultaneously with the film. After irradiation, experimental measurements using Raman spectroscopy will detect (bio)chemical changes within the film and cells, generating micron-scale maps of response to radiation, which will be linked to cell viability and function. Monte Carlo simulations of the irradiation of the system of film and cells will be used to quantify energy deposition with micron-scale resolution.  Machine Learning approaches will be used to correlate experimental and simulation results, mapping the impact of radiation on cellular response.

This research proposes a unique direction - the development of a system for carrying out micron-scale analysis of energy deposition within a population of cells coupled with biological response therein. Once established, this system will be used to investigate the effects of high and low dose radiation on various cell types (cancerous, normal) and in vitro tumour cell and patient-derived systems. It offers the potential for high reward as a new paradigm-changing approach to study fundamental questions in radiation medicine by bridging the knowledge gap between radiation's insult and biological response, leading to translational outcomes including better radiation treatments (improved tumour cell kill, less normal tissue toxicity). There are no other comparable systems in existence due to the considerable challenges in evaluating energy deposition and biological response on cell scales, and no established Machine Learning methods for connecting the two. Further high-risk elements come from variability in biological response, as well as experimental uncertainties.

Scientific breakthroughs will arise from the active control of molecular pathways in living organisms while simultaneously monitoring the impact of these changes at the cellular or tissue level with molecular resolution. This control of molecular pathways is necessary in medicine to find the molecular origins and cures to diseases, but also in environmental sciences to improve the sustainability of agriculture. At the center of this challenge lies a technological gap, because contemporary techniques do not control and monitor biochemical pathways. We propose the development of a new technology combining optophysiology nanosensing with optogenetics to fill this gap, which will serve in this project to understand the neurochemical underpinnings of Parkinson's disease and the biochemical molecular pathways controlling plant growth. Optogenetics is used to activate or silence molecular pathways in cells. In neuroscience, it serves to trigger the secretion of neurotransmitters with exquisite time and spatial resolution to investigate the molecular mechanisms of neurotransmitter release and neurodegenerative diseases. In plant biology, it is used to stimulate and control plant growth, with the aim of increasing crop productivity and creating more sustainable agriculture. However, the chemical information acquired by modern fluorescence and electrochemistry tools limits the ability to fully understand the chemical biology of plant and animal tissues in optogenetics studies. Plasmonic optophysiology is a technology capable of monitoring a large spectrum of chemicals using the power of surface-enhanced Raman scattering coupled to machine learning. Plasmonic optophysiology is fully compatible with optogenetics, but instrumentation combining these two approaches does not exist. We will create the first optophysiology/optogenetics microscope to address this challenge, making this tool unique in the world, which will be used in combination with novel biomathematics to extract chemical information from optophysiology and elucidate chemical gradients involved in plant growth and neurochemical responses during optogenetic experiments. In this grant, we will develop and validate novel molecular technologies, based on our respective expertise in technological and applied science to address two of the grand challenges in the 21st century in agriculture and brain diseases.

A substantial number of young people are facing increasing difficulties in (i) completing an education; (ii) entering the workforce; and (iii) moving out of the parental home to become established and independent adults. This phenomenon is known as "failure to launch" and is a serious and oft-ignored issue that can contribute to social exclusion, marginalization and adverse mental health.

Importantly, evidence suggests that young Black men are particularly affected by failure to launch. For example, a recent Statistics Canada report found that 20% of young Black men are in the "Not in Education, Employment, nor Training" (NEETs) category, compared to 12% of other young men. This report also found that only 17% of young Black men have a university degree, compared to 34% of young Black women. Such exclusion from work and education may contribute towards high rates of loneliness in Black youth, with one study finding that 37% of Black adults report no close friends, with highest rates in those lacking post-secondary education. Importantly, research indicates that factors such as low educational attainment, unemployment and loneliness are strong determinants of adverse mental health outcomes in youth including substance abuse, depression and suicidality.

In this study, we will use a novel participatory action research approach to address failure to launch in young Black men. This will involve university researchers from diverse disciplines working closely at all stages of the project with a Black educational community organization that includes teachers, youth and parents. In particular, the team will:

(i) co-design and co-create a targeted bottom-up group intervention aiming to help young Black men acquire new skills that can assist in the transition ("launch") to adulthood;

(ii) implement the intervention in a local community setting; and

(iii) pilot test the intervention for acceptability, feasibility and preliminary impact through mixed-methods research.

This is a high-risk project with the potential for high-reward, as it will be the first study of its kind focused on failure to launch in young Black men, with the grassroots community partner driving project progress throughout. Ultimately, this study may produce a feasible intervention, which will be packaged and primed for ?formal testing and scale-up if the results are promising. This will help address a serious and oft-ignored racial inequality with severe psychosocial consequences.

Objectifs du projet de recherche proposé: Déterminer 1) les composantes physiques (motrices, cardiovasculaires), 2) psychologiques (participation sociale, sentiment de compétence, autonomie, appartenance) et 3) environnementales (adaptation des caractéristiques du milieu, formation (animateurs, parents et décideurs)) des enfants atteints d'une difficulté ou d'un trouble d'apprentissage (TA) avant et après la prise en compte des besoins psychologiques fondamentaux (autonomie, appartenance, compétence) par l'écosystème communautaire et municipal. Le sous-objectif est de vérifier si ces services peuvent soutenir le système de première ligne en santé.

Approche de recherche: Des études démontrent que les TA sont associés à des difficultés motrices. Le modèle de Stodden démontre que les difficultés motrices sont associées à une faible perception de ses compétences ce qui conséquemment, mène à une faible participation aux activités (sport, module de jeux, camp de jour, loisir) et donc, à la sédentarité et au déconditionnement physiques (capacités musculaires et cardiovasculaires) ce qui accentue le phénomène. Considérant ces données probantes récentes, étonnamment, peu de services et de recherches utilisent méthodes novatrices pour soutenir les TA et leurs familles afin de réduire l'impact psychologique et physique des TA. Pour ce faire, DYSactivation (formations adaptées au TA, basées sur un modèle largement éprouvé: théorie de l'autodétermination) sera optimisé et implémenté dans l'offre d'activités (GymnO) pour les familles en attente de diagnostic ou ayant reçu un diagnostic de TA. Un devis pré et post intervention sera utilisé pour comparer les compétences des enfants avant et après 1 an de participation à DYSactivation (entretien, questionnaire, grille d'observation, tests moteur et cardiovasculaire).

Le caractère novateur et l'importance se caractérisent par; l'approche menée dans les domaines des sciences pures, de la santé et humaines ainsi que l'innovation technologique. Cet alliage aux perceptives différentes mais complémentaires permettra d'optimiser en coconstruction et d'évaluer par une équipe intégrée (kinésiologue, designer industriel, psychologue, santé publique, éducateur physique, parent, intervenant.) une approche inédite, DYSactivation qui comble le besoin criant de services pour les TA. Les données issues de ce projet ambitieux à haut risque pourraient démontrer l'efficacité d'un réseau parallèle aux systèmes scolaire et de santé.

Paraplegia from spinal cord injury (SCI) is a devastating condition. SCI leads to spasticity, where the paralysed limbs become overreactive to innocuous stimuli. Spasticity negatively affects quality of life by generating spontaneous movements, preventing hygiene, and interfering with sleep. Spasticity also implies that, even though muscles in patients with SCI cannot be voluntarily controlled, they remain strong and effective at generating movement.

Spinal cord stimulation (SCS) is a technology used in clinic for the treatment of chronic pain. It consists of implanted epidural electrodes connected to a battery. When activated, the electrical current activates spinal cord neurons and generates a tingling sensation in the limbs which alleviates pain. When the current is increased, reflex motor contractions can be seen. This is considered an adverse effect of the stimulation as these contractions are uncontrollable and can be painful. Because patients must feel the stimulation for it to be effective, SCS is seldom used in SCI patients, as their injury typically abolished sensation in the paralyzed limb. This also means that, in theory, stimulating the spinal cord below the level of injury could induce motor reflexes without generating pain.

The goal of this multidisciplinary project is to restore voluntary movement in a spastic, paralyzed limb by inducing controlled reflex contractions using spinal cord stimulation. Briefly, in the neurophysiology laboratory, a neurosurgeon will implant a SCS system in cats with SCI to generate stereotypical motor reflexes. An external stimulator will be controlled in real-time by a custom-designed, wearable, haptic glove interface in which each finger will be assigned to a specific and functionally relevant reflex. The strength, duration and combination of induced reflexes will be modulated to recreate limb actions, such as postural maintenance, leg extension and gait. Proprioceptive signals will be measured from the dorsal columns by recording local field potentials and transmitted back to the glove as vibration patterns to refine motor control.

If successful, this study would demonstrate how pathological spasticity in SCI can be used to restore volitional movement in a paralysed limb. The real-time induction of reflex motor contractions through implanted epidural electrodes would open a completely new treatment paradigm for individuals with paralysis, which is currently an incurable condition.

How does knowledge production and dissemination in the social and natural sciences implicitly or explicitly marginalize, diminish, and ultimately erase the contributions of Black, Indigenous, and People of Colour (BIPOC) scholars within Canadian institutions? In other words, what accounts for the erasure of BIPOC scholars in our disciplines and how can such marginalization be addressed using an integrative cross-disciplinary approach? Bringing Canadian scholars from across social and natural science disciplines, this project aims 1) expose hidden contributions of BIPOC scholars across the social and natural sciences, 2) explore the epistemological ramifications of racism and whiteness within the sciences in Canada with emphasis on lab ethnography, and 3) initiate interdisciplinary transformation through syllabi diversification workshops. Our objectives will be addressed using a mix of qualitative and quantitative methods consistent with the epistemological pluralism embedded in the research team, and will form the basis for launching what we envision in the long term as a National Centre of Excellence for Inclusive Scholarship. Immediate key outputs will include a digital mapping of the `colour of the field' via the examination of BIPOC representation across social and natural sciences course syllabi in Canada, a Canadian hidden figures online dialogue platform, and traditional dissemination through publications in high-impact, interdisciplinary journals - all of which will go towards the promotion of diversity and inclusion in different disciplines. By exposing the hidden contributions of BIPOC scholars, exploring the epistemological ramifications of whiteness and racism, and initiating interdisciplinary transformation within the Canadian academic context, this project seeks to disrupt the prevailing systems of whiteness and thereby facilitate the decolonization of the production and dissemination of scientific knowledge within Canadian institutions. While operating a research program and developing new scientific practices within a plural, reflective and collective interdisciplinary framework is at high risk of failing, this project has the potential to fundamentally alter the inclusivity and diversity of Canadian academic disciplines. In particular, the cross-disciplinary thinking and collaboration that is fundamental to this project represents a significant first step in transforming our disciplines into anti-racist sites of inclusive excellence.

Antibiotic resistance is rising at an alarming rate and is particularly problematic in chronic wounds infections. Chronic wounds affect ~2% of Canadians, with direct healthcare costs of ~$4B each year. Wounds are most commonly infected with Staphylococcus aureus, colonizing chronic wounds as biofilms. Biofilms are surface-associated microbial communities tolerant to antibiotics; however, they are often studied under standard in vitro conditions, likely overlooking key virulence factors involved in infection.

Indigenous peoples have long used natural remedies to treat wounds and infections; however, their knowledge has rarely been considered for modern medicine. The stagnation of the antibiotic discovery pipelines prompted us to turn to Indigenous medicine as an untapped source of potential new antimicrobials. This project aims to uncover novel biofilm-related virulence factors and discover new treatments for drug-resistant S. aureus chronic wound infections. Unlike typical antibiotic discovery campaigns, we will combine high-throughput whole-genome approaches with the exploration of traditional Indigenous medicines.

Objective 1 aims to uncover novel biofilm virulence factors by screening a sequence-defined S. aureus mutant library for biofilm formation under conditions mimicking human wound infections. We will characterize putative novel factors in an ex vivo human skin infection model and assess their mechanism using established microbiological and biochemical assays. Objective 2 will explore Indigenous medicines to combat S. aureus biofilms. An array of Indigenous medicinal plants will be selected, guided by Elders, and screened for their anti-biofilm activity under wound infection-mimetic conditions. Top hits will be tested in in vivo and ex vivo skin infection models. Objective 3 will identify the mode of action of these hits. We will fractionate the traditional remedies and assess the anti-biofilm activity of the fractions. Active principles will be identified using various chromatographic and spectroscopic techniques, and the S. aureus mutant collection will be screened to evaluate their anti-biofilm mechanisms.

This work will provide valuable insights into the bacterial responses under clinically relevant conditions while providing novel druggable virulence targets for new antimicrobial strategies. By integrating modern and Indigenous approaches, this novel research charts a path for new anti-biofilm treatments for chronic wound infections.

This proposal calls for the development of a flexible drone-based platform that will provide novel measurement capabilities for both astrophysics and glaciology. Radio-frequency astrophysical measurements often employ stationary telescopes (dishes or antennas) that are sited in remote, rugged locations. One of the most critical aspects of radio telescope characterization is the measurement of the spatial response on the sky, or the "beam pattern." Because stationary telescopes are unable to actively re-point and scan over celestial sources, the only way to obtain complete beam pattern information is to move a source relative to the telescope, scanning the full field of view. For some radio telescopes, the details of the beam pattern are further complicated by dependence upon the electromagnetic properties of the underlying earth. In these cases, complete knowledge of the beam pattern requires careful characterization of the earth using measurements from ground-penetrating radar. Ground- and ice-penetrating radar measurements are fundamental to glaciology research. One of the challenges of these measurements is that they also take place in rugged locations, and the measurement procedure typically involves personnel manually dragging radio-frequency transmitter/receiver hardware along the ground or ice surface. This process is not only time-consuming, but also potentially hazardous to the personnel conducting the measurements.

Drones carrying transmitter/receiver payloads, which can scan large swaths of terrain with automated flight patterns, provide a unique solution to the shared needs and shared deployment locations of radio-frequency astrophysics experiments and glaciology research. The measurement challenges facing both of these fields present an exceptional opportunity to combine interdisciplinary expertise to develop shared instrumentation with wide-ranging benefits. We propose to develop the technology for a custom built drone that will operate in the Canadian high Arctic and that will have the flexibility to carry an assortment of payloads to service both astrophysics and glaciology research. In contrast to existing drone-based measurement platforms, we will take the novel approach of developing a low-cost, open-source drone that is optimized for long flight times, high lift capacity, and that is easily serviceable/replaceable in the high-risk environment of the Arctic.

Antibiotics have saved countless lives, transformed healthcare and extended life expectancy by decades. With use, however, these therapies have become increasingly ineffective due to the development of drug-resistant bacteria. The need for new life-saving antibiotics has reached crisis proportions.

Since the discovery of penicillin almost one hundred years ago, the search for new antibiotic drugs has always begun with a chemical compound that halts the growth of bacteria. The ensuing decades saw dozens of new antibiotics found in this way but it has now been more than fifty years since the discovery of a new drug to treat the most dreaded bacterial pathogens. Indeed, despite remarkable technological advances in the modern era, the search for new antibiotics fundamentally remains a hunt for novel compounds that kill bacteria. Our proposal aims to redefine antibiotic drug discovery by innovating at the earliest stage of the discovery process.

Rather than searching for chemicals that halt the growth of bacteria, we have developed a method to identify those that instead enhance bacterial growth. How can such compounds help in the search for new antibiotics? We have discovered that these chemicals are a powerful tool for enabling antibiotic action in other molecules. These growth-promoting chemical moieties can be grafted onto otherwise ineffective antibiotics, vastly improving the penetration of such drugs into bacteria. Importantly, this molecular trickery has spectacular impact on antibiotic efficacy.

In the proposed research, we will exploit this discovery platform and the chemical enhancers that we have discovered to create new antibiotic molecules for treating drug-resistant infections. This work will require an interdisciplinary team to carry out biological analyses of growth enhancing compounds and systematic chemical synthesis to explore their potential to improve conventional drugs. Our approach has the potential to transform therapy and, consequently, will require new thinking to address socioeconomic hurdles of sustainability, access and stewardship. Thus, we will concurrently examine these elements to ensure that our novel therapy can ultimately be integrated into existing social, economic and healthcare frameworks, in Canada and worldwide.

In all, our innovative science, combined with forward-thinking socioeconomic analyses, have the potential to provide impactful solutions where conventional approaches have failed.

Early detection and intervention are critical for supporting optimal outcomes in mental illness, yet gaps remain in predicting individual risk. Being born very early or very small is known to increase risk for Autism, ADHD, depression, anxiety, and psychosis. As such, preterm birth has been suggested to confer a "transdiagnostic biological vulnerability" to mental illness. However, outcomes following perinatal complications are highly variable, and the biological clues offered by this `model system' have yet to be leveraged to support early identification.

Neuroimaging studies describe alterations to the brain's white matter connectome in preterm birth including substantial heterogeneity that may relate to differential risk. However, accurately characterizing inter-individual heterogeneity requires reliable (deep) sampling and synthesizing information from high-resolution whole brain data requires sensitive, validated computational tools.

Network control theory is an emerging mathematical framework with which to describe how function and behavior arise from the brain's white matter connectivity. Control is essential to the functioning of neural systems and loss of control manifests through brain disease and disorder. We will develop a network control theoretic framework to understand the system-level implications of network alterations observed in preterm birth, and mechanistically describe how heterogeneous white matter alterations may lead to common network patterns that associate with transdiagnostic mental illness risk.

Our interdisciplinary study will integrate methodology from psychiatry, radiology, neurology, network science, and control theory to precisely characterize functional and structural brain networks in youth with transdiagnostic mental illness risk related to perinatal complications. We will deeply phenotype and densely sample individuals to derive precision brain network metrics and verify their individual reliability and sensitivity to clinical features. We will develop a network control theory-based framework to explain how heterogeneous structural alterations lead to functional and behavioral variation, with the ultimate goal of building a unifying network model of mental illness risk. The development of such a novel, fundamental framework from highly detailed and heterogeneous precision neuroimaging data is inherently high risk and has the potential to yield high-reward personalized early screening tools for mental illness.

Objective: To improve prescription drug safety using visual analytics.

Background: We trust our doctors to know the safety of the drugs they prescribe. However, most data on drug dosing and safety comes from small clinical studies that exclude older high-risk patients. This is a problem because as people age their kidney function declines and drugs cleared by the kidney need to be dose-reduced or avoided to prevent adverse reactions. In older adults, 1 in 6 hospitalizations are for adverse reactions to prescription drugs.

The Problem: Understanding the harm caused by which drugs at which dose and in which patients is immensely challenging. Health Canada and the U.S. Food and Drug Administration rely on post-marketing, population-based studies to inform safe drug prescribing. We have conducted 60+ population-based drug-safety studies using Ontario's administrative healthcare databases-with many studies published in high-impact journals, including JAMA and Annals of Internal Medicine. Our results have been used to refine product-label warnings. Unfortunately, the traditional pharmaco-epi approach has limitations:

1. Each study can examine only one drug or drug class and a few select outcomes.

2. Small knowledge gains take years to achieve.

3. Many harmful drug effects are missed.

Innovation: We will overcome the limitations of the traditional pharmaco-epi approach by integrating visual analytics into our analysis of administrative healthcare data. This approach will utilize interactive data visualization, artificial intelligence, and machine learning to improve the interpretation of complex analyses. Using automation, high-throughput computing, and visual analytics, we will simultaneously study the effect of multiple prescription drugs and their interactions on many patient outcomes. Our novel approach will allow us to efficiently identify and verify adverse drug reactions in vulnerable patient populations.

Collaboration: Our interdisciplinary team includes physicians, computer scientists, pharmacologists, and epidemiologists from Computer and Information Science, and Clinical Medicine.

Impact: We expect to discover 30+ unsafe prescribing practices and drug-drug interactions. Our use of population-based data will allow us to examine risks in under-studied patient groups and by gender. We will translate this information into better education, policy, and regulation to protect patients and reduce healthcare costs.

Next-generation portable solid-state lighting applications are being developed using compound semiconductor light-emitting diodes (LEDs) within a $33B market. This technology also creates opportunities for developing portable ultra-violet (UV) LEDs for water purification, providing an antimicrobial agent with low voltage and power requirements compared to conventional mercury lamp systems. However, the operational periods are limited by the battery that powers the LEDs and the emitter brightness.

With the objectives to extend running times and enhance LED brightness, we propose an approach that utilizes a thermoelectric generator (TEG) to take advantage of the heat generated from the LEDs. By exploiting the individual expertise through this interdisciplinary project, the disadvantages of one system (heating of the LEDs) will be used for the advantage of the second (electricity generation from heat). Given the disparate properties of the materials systems involved, this combination has never been considered for energy generation. Its realization would create a new class of hybrid-powered self-sustaining portable solid-state lighting systems that has never been achieved.

The team combines the extensive expertise in optoelectronic devices of the co-PI and in thermoelectric materials chemistry of the PI to define a new standard for portable solid-state lighting. Each technology will be optimized on separate platforms and then combined to create a novel integrated microsystem. Accomplishing this goal will, for the first time, enable simultaneous cooling of the lighting system that drives the TEG to continuously recharge the portable battery while raising LED performance. When integrated with portable UV lighting, stand-alone water-purification systems will be enabled. Achieving performance improvements for these applications with this hybrid-power system define the high risk of the project. The reward is from a fully integrated system on a single platform with no moving parts, enabling portable lighting with autonomous high-reliability operation. This achievement ultimately increases operational lifetimes and function without additional maintenance requirements. Further rewards will be in portable UV LED water purification systems for remote undeveloped regions. This reward is particularly significant for First Nations communities, where the technology will eliminate a lack of clean-water access due to infrastructure deficiencies in Canada. 

According to INTERPOL, the trade in illegal forest products is estimated to be worth almost USD 152 billion a year. The significant environmental, economic and social costs that result from this trade are felt in Canada and around the world. Illegal trade contributes to deforestation and loss of biodiversity, increased carbon emissions, human contact with wildlife infectious diseases, financing organized crime, undercutting legitimate suppliers, and social conflict with Indigenous and local populations. While Canada and many other countries have strict laws governing the trade in plant and timber products, these laws are poorly enforced due to the challenge of identifying illegal species at the point of inspection. Hence, our objective is to develop an electronic (e-)nose that can be used by frontline personnel to rapidly identify illegal forest products based on their unique odour `fingerprint'.

Development of an e-nose solution relies on our interdisciplinary expertise in analytical chemistry, electronic engineering and artificial intelligence (AI). The approach will involve generating an odour reference database for trafficked timber and plant products as well as those that can legally enter our borders. Statistical analysis will identify the mixtures of volatile compounds that accurately distinguish the odour profiles of illegal and legal species. A prototype e-nose (NOS.E) will be further developed, by augmenting the chamber design, flow and battery capabilities, as well as sensor selection involving AI-based pattern recognition techniques. This is a high-risk project as it relies on the sensors being sufficiently sensitive to distinguish the distinct species' odour fingerprints. The resulting prototype will be a field-portable device that collects the odour and rapidly identifies the unique fingerprint pattern for each species in the database.

This project will generate the first e-nose on the global market to mimic a dog's nose for sensitivity with the increased value of rapidly identifying illegal products for apprehension and prosecution of the offenders. The e-nose would be employed by provincial and federal border enforcement agencies in Canada to regulate the import, export and interprovincial transportation of species covered by international treaties. It would also be employed on a global scale, including for island nations such as Australia, where forestry crime can lead to significant biosecurity threats. 

We envision a future in which talk therapies for mental health and addiction disorders can be delivered by a computer, enabling far greater access to therapy. Recent innovations in artificial intelligence make it possible to develop a conversational agent capable of the free-form interaction that is used in human-to-human therapy. Our specific goal is to help smokers quit smoking by exploring and developing the automated delivery of known-successful clinical therapy. We have brought together an interdisciplinary group of clinician/researchers in mental health and addiction, computer science and engineering, and social sciences to do so.

Addiction to tobacco affects 4.6 million Canadians and leads to many adverse health outcomes. A key step towards smoking cessation is the decision by the smoker to quit, yet over 50% of all smokers are ambivalent about quitting and make no current effort to stop. These smokers can be helped by a successful talk therapy approach known as Motivational Interviewing (MI), in which a clinician gently guides a patient, in a conversation, through a process of self-reflection. This process has been shown to increase the likelihood of successful behaviour change. The key steps in this approach involve asking open-ended questions relevant to the behaviour, and providing reflective, summative, and supportive conversational responses. An important part of the conversation is to build trust between the clinician and the patient.

Highly-trained MI clinicians, however, are in short supply - there are not enough of them for everyone who needs help, nor are they located where, and available when they are needed most. The goal of this project is automate such conversations, with a software-based `chatbot'. If we can successfully build such a system, the cost of deploying help will be significantly reduced, and the ability to help patients at any time and place will dramatically increase. Our system could also form the basis of many other automated talk-based interventions.

The long-term goal of this research is to reduce smoking prevalence world-wide by providing a low-cost method to engage ambivalent smokers in an MI conversation and move them towards the decision to quit. We will evaluate the success of our system by measuring smokers' readiness to quit before and after exposure to the intervention by a chatbot.

Lung cancer is the leading cause of cancer deaths with overall 5-year survival rate less than 20%. Due to heterogeneity of the disease, precision therapies are essential. The small interfering RNA (siRNA) therapeutics can specifically silence the expression of target genes including those traditionally considered to be "untreatable" by small-molecule drugs. However, siRNA therapy faces challenges such as poor cellular uptake, enzymatic and endosomal degradation. Encapsulation of siRNA in nanoparticles has shown to overcome some of these challenges. However, most nanoparticles tend to accumulate in liver and effective siRNA delivery in extra-hepatic tissues remains a challenge. Therefore, to maximize the efficacy of siRNA therapeutics in lung cancer, there is an unmet need to develop approaches to achieve preferential accumulation of siRNA in lungs.

Conjugation of nucleic acids with hydrophobic moieties has shown to modulate their interactions with plasma proteins, thereby impacting their stability against enzymatic degradation, cellular uptake and endosomal escape. Herein, we propose a highly inter-disciplinary approach, combining expertise in lipid chemistry, polymer chemistry, engineering and pharmaceutical sciences to design and validate a lipidated-siRNA delivery method for lung cancer treatment. We propose a high risk project to develop monomeric, oligomeric and polymeric lipid-conjugated siRNA therapeutics and perform a systematic study correlating the impact of lipid properties including chain length, hydrophobicity, charge, functional group and degree of unsaturation on the biodistribution of lipidated siRNA. This interaction will enable us to identify unique lipid properties required to achieve preferential accumulation of lipidated siRNA in lungs. We will also evaluate the impact of lipid properties on cellular uptake and endosomal escape of the lipidated siRNA.

Our specific aims are: i) Design and evaluate the lipid polyplex with variable structures for cellular uptake and gene silencing; ii) Investigate the biodistribution of lipid-siRNA conjugates for lung accumulation; iii) Evaluate antitumor efficacy in lung cancer model.

The proposed research is risky, from identifying model lipid-siRNA conjugates with preferential accumulation to evaluation of antitumor efficacy in lung cancer. The successful development of this new approach has the potential to effectively and selectively treat lung cancer with huge social and economic benefits.

The cerebellum is a part of the brain responsible for diverse regulatory functions including motor control, sensorimotor adaptation, speech regulation, emotion regulation, and other functions. It is said to be involved in all behaviors of precision. By 1967 the neuronal structure of the cerebellum was completely mapped out by Nobel prize winner John Eccles and his collaborators. Around 1992 a theory of cerebellar function emerged in which the cerebellum learns a so-called internal model of the part of the body being regulated. Unfortunately, despite important advances, researchers have not been able to find conclusive experimental proof of this theory. After a 50 year search, there is still no consensus on cerebellar function.

We are pursuing an alternative hypothesis on cerebellar function motivated by ideas from control theory. We hypothesize that the cerebellum embodies adaptive internal models of exogenous disturbance signals acting on the body. The internal model principle of control theory says that any good controller must build an internal model of all persistent exogenous signals impinging on a control loop. This principle would suggest that cerebellar internal models regard the external world, not the body itself. Any internal models of the body may well reside in other brain regions.

By applying recently developed mathematical tools from control theory, we have modelled the cerebellum in the context of two motor systems: the oculomotor system and visuomotor adaptation. Our models recover the known behaviors of those systems, and they are consistent with the neural circuits in the brain. There remains an overarching challenge that control theory alone cannot address. Can we find experimental evidence that the cerebellum contains internal models of the external world and not of the body? Do internal models of the body reside in other regions of the brain? Control theory and neuroscience must come together to address this challenge.

The stakes for our work could not be higher. Resolving the paradox of cerebellar function would aid medical researchers to understand important classes of brain diseases such as ataxia, Huntington's disease, and Parkinson's disease; it would shed light on the role of other brain regions that interact with the cerebellum; and it would alleviate the dependence on primates for open-brain experiments. If our hypothesis on cerebellar function is correct, the contribution to science would be seminal.

Fire safety is a serious concern in Canada, particularly in our most vulnerable populations like the elderly who make up >39% of fire deaths in Ontario. Yet fire and life safety codes provide intransigent guidelines based on human behaviour parameters derived from young male historical datasets, with no consideration for physiological differences due to sex, wellness, age, culture or mental facility. Consensus-based factors then arbitrarily `adjust' this behaviour for diverse populations found in homes, hospitals, nursing homes or other residential settings. Imagine, instead, if buildings were outfitted with intelligent Safety Companions- flexible and scientifically-grounded life safety systems designed for a range of populations. Using an interdisciplinary approach the project's objective is to combine our expertise in fire engineering, exercise physiology and artificial intelligence (AI) to develop such a Companion. The project will accomplish this objective with three steps. First, obtain empirical data and tools for real-time assessment of key safety indicators (e.g. carbon monoxide) in harsh modern evolving fires. In fire science, data around accumulation of particulates, toxic/irritant gases and smoke in real fires is lacking, due to challenges emulating harsh fire environments and finding sensors that survive and provide time-resolved occupant exposure data. To overcome this problem we will develop a novel lung system and suite of new robust sensors to measure what a human inhales in a real fire. Second, unite the novel modern fire data with human physiology to determine human responses to real fire scenarios. Specifically, the fire conditions will be replicated in humans to explore their impact while accounting for sex, age, culture and conditions. Third, develop an AI Companion that integrates fire-human exposure models and accounts for diverse occupant physiology. Our Companion will use AI to direct evacuation via auditory, visual and kinetic cues. Our project will foster a unique interdisciplinary team linking the seldom combined fields of fire engineering, exercise physiology and AI. Our Companion has the potential to radically change fire safety and how egress models are developed for new buildings. Success of our companion could substantially improve fire safety especially for those from more vulnerable populations who are unaccounted for in current models yet currently suffer disproportionately greater mortality and morbidity from fires.

The mechanical environment of the central nervous system (CNS) plays a key role in regulating axonal growth. Both overall stiffness and stiffness gradients impact growth, and it has been shown that local mechanical manipulation can alter growth patterns. Thus, an approach that could non-invasively and locally manipulate tissue stiffness in the CNS could be provide a novel avenue to direct and promote axonal growth. In particular, in the injured CNS, where scarring results in lowered tissue stiffness, creating an environment that is mechanically more amenable to regeneration could work synergistically with chemical promotors.

Focused ultrasound (FUS) is a novel brain therapy that is clinically approved for treating essential tremor via thermal ablation, but can elicit a wide range of permanent and reversible bioeffects depending on the exposure parameters. At low-powers, focused ultrasound in combination with intravenously administered clinical ultrasound contrast agents (microbubbles) can cause local, transient and reversible opening of the blood-brain and blood-spinal cord barriers, a therapeutic approach that has not only reached clinical investigations in several brain disorders, but that has been shown pre-clinically to increase neurogenesis and plasticity. The mechanical changes occurring in the exposed tissue during this and other types of FUS treatment have never been investigated. Given the ability of ultrasound to produce controlled mechanical effects at depth in tissue with high spatial specificity, and the existing evidence that mechanical changes in the CNS environment can impact axonal growth, we posit that FUS can be developed as a tool to promote regeneration. Specifically, we hypothesize: 1) that focused ultrasound can be used to locally modify the mechanical environment in the brain, 2) that these changes will modify patterns of axonal growth. We will test these hypotheses in rats through two specific aims:

Aim 1: To use Atomic Force Microscopy (AFM) to characterize the effects of focused ultrasound on the mechanical properties of the brain.

Aim 2: To evaluate axonal growth following focused ultrasound using Light Sheet Microscopy.

The main outcome of this study will be the demonstration that ultrasound can be used to manipulate axonal regeneration. This will open up an entirely new therapeutic approach for CNS regeneration with potential application in both traumatically injured and neurodegenerative patient populations.

Language is at the core of Indigenous identities, knowledge systems and world views, and is critical for well-being and social cohesion. Yet, most Canadian Indigenous languages are nearing extinction, with little to no intergenerational language transmission. The project focuses on revitalization of lullabies and traditional ways of infant oriented speech as means of recreating language-focused intergenerational relationships. Using a multi-method approach, informed by co-design principles, this project connects elder women with younger women who often do not speak their Indigenous language. Besides the positive impact on language development, lullabies promote emotional bonding between a child and their caregiver. We hypothesize that engaging with Indigenous lullabies will promote the sense of Indigenous identity and create additional support structures for the mothers, contributing to both maternal and infant emotional and health well-being. We also expect positive emotional health and community benefits for older adults. The project indirectly addresses intergenerational trauma associated with language loss, often through the impact of residential schools, and proposes a restoration of intergenerational language knowledge transmission as a healing process.

We propose a unique framework and methodological approach to language revitalization utilizing innovative connections between psychology and linguistics. Specifically, we are applying a psychology-based theoretical framework, Bronfenbrenner's socio-ecological model, which puts the infant at the center of the model and examines how a novel parenting approach (promotion of traditional lullabies) impact maternal, child, intergenerational and community outcomes to language revitalization. This is novel in that: 1) we are examining the potential to build the foundation for language revitalization starting at an early development point, engaging intergenerational relationships within a community model (a proactive approach); and 2) we are adapting evidence-based parenting programs (e.g., book sharing) and extending these practices to lullabies within an Indigenous context.

Starting in infancy offers a powerful window to influence healthy development and create an early foundation for language revitalization. With its unique interdisciplinary lens and multi-method approach, the project has the potential to positively influence mother-child, intergenerational and community outcomes and relationships.

DNA methyltransferases (DNMT) add small chemical modifications to DNA called DNA methylation (DNAme) which is a normal epigenetic mechanism that silences the expression of many genes. However, some gastric cancers are caused by abnormal DNAme of the tumor suppressor p16, decreasing its expression. DNMT inhibitors (DNMTi) reduce p16 DNAme, increase p16 expression and shrink tumors. Unfortunately, there is currently no way to inhibit DNMT only at the p16 gene, so DNMTi also increase the expression of many normal genes, reducing treatment efficacy. In this proposal, DNMT inhibition will be targeted to the p16 gene to increase its expression, mitigating these problems, and in the process making a novel gastric cancer therapeutic.

Hypothesis:

p16 expression can be selectively increased by reducing p16 DNAme using a single oligonucleotide containing a targeting sequence (TS) that binds to the p16 gene, and a DNA aptamer (Apt) sequence that inhibits DNMT (TS-Apt).

Specific Objectives:

1) Design TS-Apt and determine their in vitro activity.

2) Evaluate the efficacy of TS-Apt in gastric cancer cell lines.

3) Evaluate the efficacy of TS-Apt in a mouse xenograft model.

Approach:

Several TS-Apt will be synthesized targeting p16 DNAme sites, and their inhibitory activity quantified using mass spectrometry (MS) and recombinant DNMT. TS-Apt will be delivered to gastric cancer cells using a nanoparticle delivery system (NP). Increases in p16 expression, and decreases in p16 DNAme and viability will be quantified. Global changes in DNAme and gene expression will be measured using Illumina and RNA-sequencing. TS-Apt will be evaluated in a mouse xenograft model by measuring cell growth, and global and p16 specific DNAme. TS-Apt will increase p16 expression without effecting global DNAme and gene expression.

Novelty, high risk / reward:

TS-Apt will become a novel class of anti-cancer drugs which selectively increase tumor suppressor p16 expression by inhibiting DNMT at the p16 gene using a single oligonucleotide. This will produce new treatments for gastric cancer which is the third leading cause of death from cancer. TS-Apt will solve the problem of genome wide inhibition of DNMT caused by existing DNMTi. The novel interdisciplinary approach combines experts in, drug discovery, to design and test the TS-Apt, nanoparticles, to formulate TS-Apt into NP, and epigenetics, to show that the effects of TS-Apt are confined to the p16 gene.

IMPACT: Lockdowns have been an effective approach to limiting the spread of COVID-19. Unfortunately, reduced building occupancy also leads to the growth of dangerous environmental microbes such as the bacteria Legionella pneumophila (the causative agent of an often-deadly pneumonia, Legionnaires' disease). Under-utilized water systems must be constantly flushed, monitored, and treated using harsh chemicals. Even with these remediations, some buildings become chronically colonized by the pathogen. A next generation of bioremediation tools would change the dynamic and could potentially eliminate the threat of Legionella from the built environment. We propose to identify, isolate, and engineer Legionella phages as the first step towards developing "phage therapy" for our buildings.

AIMS:

1. Integrate phage detection with existing diagnostic workflows.

2. Use metagenomics to assemble phage genomes from prioritized samples.

3. Isolate and engineer phages in order to model bioremediation effectiveness within engineered water systems.

RISK: Several L. pneumophila genomes contain clear evidence of contemporary encounters with phages. We know that these phages exist, but their identity can only be pieced together by way of short sequence signatures (spacers) left behind at CRISPR-Cas loci. To gain full utility of this knowledge, we must launch a broad search for Legionella phages in the environment. Prospecting, whether for gold or new phages is intrinsically a high-risk, high-reward endeavour. Traditional funding streams strongly favour projects with a defined set of candidates (in this case, phages) in hand, thus this type of project typically goes unfunded, despite its clear benefits for society if successful.

TEAM: We have assembled a team uniquely positioned to find the elusive Legionella phage: experts in microbiology, diagnostics, environmental metagenomics, and the modelling of Legionella behaviour within engineered water systems. Our expertise is matched by a unique set of resources: environmental freshwater metagenomes (and the ability to collect more) and access to contaminated water samples sent for molecular testing. Key to prospecting is establishing a sustainable search - as such we will develop methodology to integrate Legionella phage detection with existing diagnostic workflows and environmental sampling. Our experience modelling the built environment will then allow us measure the bioremediation potential of candidate phage.

Pseudomonas aeruginosa is an opportunistic bacterium known for its severe pathogenicity, particularly in immune-compromised patients and those with cystic fibrosis. The increasing incidence of multidrug- resistant P. aeruginosa infections has led the WHO to deem this bacterium a Priority 1 pathogen that is in urgent need of new antibiotics. To circumvent the resistance problem, there is an increasing interest in developing drugs that interfere with virulence and persistence, as opposed to directly killing the cell, thus the `disarm - don't kill' approach. Recently, we made a preliminary discovery that a family of compounds can effectively inhibit polyphosphate kinase (PPK) and attenuate biofilm formation and virulence phenotypes. However, the assays currently available are not amenable to efficient and sensitive screening of antivirulence drug candidates in vivo.

To solve this dilemma, we will develop and test a novel, double layer cantilever microsensor with a functionalized surface to measure pyoverdine levels (a surrogate for PPK inhibitor potency). This microsensor will be coupled with electrokinetics (electrically charged fluids) for assessing drug efficacy with exceptionally high sensitivity and selectivity. Using this advanced technology, we aim to further screen PPK inhibitor candidates and develop a structure-activity relationship (SAR). SAR will facilitate our efforts to improve PPK inhibitor structures and obtain optimized antivirulence drug.

If successful, this will be the first antivirulence drug ever developed based on PPK inhibition. PPK is an attractive drug target because its inhibition will unlikely result in antibiotic resistance. The proposed microsensor has never been designed and developed before and will offer a very effective and economic method for evaluating the efficacy of a PPK drug. The collaboration of two distinct disciplines (biomedical research and mechanical engineering) in a new way is necessary if we are to meet our objectives. Discovering a PPK antivirulence drug that can treat a P. aeruginosa infection while avoiding antibiotic resistance is inherently high-risk but a positive outcome could help millions of patients suffering from infections each year. In addition, the microsensor technology will offer a practical and sensitive means to guide future drug design efforts.

Motivation: New evidence suggests that the bacteria found in a person's gut (the gut `microbiome') influences the growth of cancer tumours and how they respond to therapy. For example, transplanting bacteria from long-term pancreatic cancer survivors into mice with pancreatic tumours can reduce tumour growth. These bacteria influenced the properties of immune cells in the tumour and changed the types of bacterial communities found in the tumour (which differ from the bacteria present in the gut). This phenomenon offers an exciting opportunity to improve current cancer therapies, but exactly how certain gut bacteria influence tumours and the immune responses are not understood. A major challenge in understanding tumour-bacteria interactions is a lack of lab-based experimental systems that can accurately and reproducibly reflect the biology of human tumours and their microbiomes, while also allowing a detailed molecular analysis.

The objective of this project is to use newly developed tissue engineering approaches to create and mix different combinations of microbiomes and tumours in a dish that will allow us to study the interaction between a patient's microbiome and their tumour in the lab.

Our specific Aims are to:

1. Establish a tissue-engineered based method to create hundreds of unique bacterial communities in a dish and quantify the resulting properties of each community.

2. Establish a scalable protocol to mix engineered tumours in a dish with products secreted from different bacterial communities to determine the impact of gut microbiome on tumour cell properties.

3. Establish a method to culture bacteria from tumours in engineered tumours in a dish to study the interactions between bacteria and tumour cells.

Novelty and Significance: This project will combine novel bioengineering, microbiology, and tissue biology methods to establish powerful methods to study bacteria/tumor interactions in the lab. Knowledge generated here may help us i) stratify high risk patients on the basis of what bacteria they carry, ii) predict patient response to therapy, iii) improve patient response to standard-of-care therapies by modulation of the microbiome, and iv) monitor disease progression. This project will also provide new fundamental knowledge about how the composition, organization and surrounding environment of bacterial communities influences their properties and behaviour over time.

Cardiovascular events, including heart attack and stroke, account for nearly 20% of all deaths in Canada. They are commonly caused by blockage of the blood flow, which happens when atherosclerotic plaque build-up on the wall of the blood vessels triggers the formation of blood clots. Pathologists study the morphology of plaques to understand what kinds of structure are more likely to pull the trigger. The well-recognized "vulnerable plaques" have enlarged necrotic cores capped by a thin layer(s) of cells. However, this is not a "one-size-fits-all" feature. In women, more than twice as many blood clots are triggered by plaques having a thick cap. How to identify the real "vulnerable plaques" remains a puzzle.

We need to go beyond the reliance on morphology and incorporate Omics data when analyzing histology images. We challenge the traditional morphology-based prediction and hypothesize that underneath the many faces of plaque morphology, it is essentially the combination of disease-related biological processes, and where they are located in the plaques that decide the vulnerabilities.

This project stands at the interface between bioinformatics and digital pathology, aiming to establish a novel model to solve the problems within each discipline: 1) One can analyze gene networks of the entire tissue, but cannot translate them to biological processes without tissue orientation; and 2) The other can define the distribution patterns of pixels in tissue images. However, each pixel does not carry information of gene networks from specific cell phenotypes, and each image represents one section of the tissue.

OBJECTIVE: Create a pipeline that converts disease-related gene networks to pixels in the digital images of plaque sections, followed by spatial analysis to identify their distribution patterns correlated with cardiovascular events.

Our team will develop multimodal integration methods to align data from single cell RNA-sequencing and spatial gene expression, in a way to capsule disease-related genes into different microregions across a plaque section. We can then interpret biological processes in the tissue context. Each microregion, now representing disease-related biological processes, will be analyzed as pixels to determine their distribution patterns correlated with patients' clinical records of cardiovascular events.

This exploration is the first step towards our long-term goal of developing better methods to identify high risk patients.

Current treatment of glioblastoma (GBM) includes surgical resection followed by radiation and chemotherapy with Temozolomide (TMZ) but frequently leads to TMZ chemoresistance and GBM recurrences that are fatal. Little is known about the role of resident brain cells in GBM progression and treatment response to TMZ. This interdisciplinary team of experts in brain tumors and soft electronics will use in vivo cell-targeted optogenetics for stimulation of selected brain cells. We utilize two unique pairs of patient-derived GBM stem cell models exhibiting two different molecular mechanisms of TMZ resistance plus their TMZ sensitive parental lines. Stereotactic injection of virus for cell-type specific expression of channelrhodopsin-2 (CRP2) into the right striatum establishes an optogenetics recipient brain in immunocompromised mice. When CRP2 expression is present in the desired brain cells, patient GBM stem cells +/-TMZ resistance are xenografted using identical stereotactic coordinates and an optogentic stimulation probe with micro sized LED light source is inserted into the tumor graft location. This probe is connected to a wireless, battery-free subdermal implant and enables extended untethered operations in freely moving mice. Externally controlled optogenetic stimulation of CRP2 expressing cell populations in the tumor microenvironment commences two weeks after xenografting and coincides with the start of TMZ treatment. The probes also register temperatures and monitor oxygenation/ vascularisation of the target area daily before and after optogenetics stimulation in mice bearing TMZ sensitive and TMZ resistant GBM. We monitor the effect of optogenetic stimulation of distinct brain cell types within the GBM microenvironment on tumor-specific parameters (progression, survival, apoptosis) and use several mouse behavioral assays. We use spatial tissue profiling of brain tumor sections at defined time point before/ after TMZ treatment to generate spatiotemporal gene expression maps of brain tumor tissues. This high risk project critically depends on the unique interdisciplinary team skills to make exciting new discoveries. For the first time, we will generate cellular maps that demonstrate the contribution of selected optogenetically activated resident brain cell populations to a GBM microenvironment +/-TMZ resistance. We also expect to create new classes of exploratory and therapeutic soft electronics tools to interrogate and alter the GBM microenvironment.

Background: In the same way that different levels of autonomy and integration of machine intelligence for cars exist (i.e., conventional cars, adaptive cruise-control cars, driver-assist cars and self-driving cars), five possible levels of autonomy and intelligence exist in systems for robotic surgery:

1. Teleoperated surgery robots that work under direct human control and correspond to the lowest level of intelligence.

2. Robots that have some level of intelligence and provide physical guidance or assistance for better task execution to surgeons.

3. Robots with more autonomy that automate the execution of parts or all of specific tasks (e.g., suturing) under the supervision of a surgeon.

4. Robots with even more autonomy that strategize task execution.

5. Robots that are fully autonomous and act as entirely robotic surgeons.

Except for Level 5, other robotic systems essentially execute what the surgeon commands with varying levels of details being left to semi-autonomous systems.

Objective: Currently, the state of the art in robotic surgery is focused on task assistance (Level 2). Our objective is advancing from that to shared control (Level 3), surgeon-supervised surgery (Level 4) and eventually autonomous surgery (Level 5). This will not only increase the capacity of the healthcare system by reducing the time and energy required from surgeons but also enable highly skilled surgeons to remotely supervise the performance of surgeries in small towns and rural communities.

Approach: To push the boundaries of the state-of-the-art, we propose a framework and methods for highly autonomous robotic surgery (Levels 3-4) and will demonstrate its feasibility for breast tumour lumpectomy as a challenging yet generalizable case study. The three essential components of this surgery are (i) stabilization of the highly mobile breast tissue, (ii) lesion localization using medical images, and (iii) precise lesion removal under the guidance of medical images. This framework can then be extended to other highly challenging surgeries such as procedures on the beating heart.

Novelty/Significance: Autonomous surgical robotics technologies will make interventions more efficient and will reduce the burden on the medical staff. Increasing the level of autonomy of surgical robots from assistance to decision making and taking actions intelligently during surgery can also significantly improve the outcomes and safety of procedures for patients.

Canada's colonial legacy has pushed Indigenous communities onto land that is subject to frequent flooding, now exacerbated by climate change. Flooding has become one of the most expensive climate issues in Canada and worldwide, yet economic analyses alone do not convey the trauma, nor the loss of life, homes, possessions and ecosystems. Reducing debilitating flood impacts without causing displacement is especially crucial for Indigenous peoples who are culturally, generationally and spiritually connected to the land. The current Canadian policy of "managed retreat" (assisted relocation) is an insensitive reminder of the practices of colonialism.

This proposal seeks support for research on amphibious architecture (structures that rise and fall in synchrony with changing water levels) as an innovative flood mitigation and climate change adaptation strategy, to promote resilient communities by combining Indigenous Traditional Knowledge (TK) with modern science. Our research takes an interdisciplinary and collaborative approach, engaging Indigenous communities as well as researchers from architecture, engineering and social sciences. The project approaches Indigenous communities with respect, to weave their input into designs for amphibious housing that will meet the particular needs of each community and align with its TK and cultural practices. We propose to integrate this work with the investigation of several technical research questions necessary for the safe application of this novel strategy to Indigenous lands. Our proposed research is high risk because amphibious architecture, whether as new or retrofitted construction, is essentially unknown in Canada and has not yet been implemented here, much less in an Indigenous community in Canada. As such, it is a pioneering venture on multiple fronts.

The implementation of amphibious architecture takes a community-based, bottom-up approach to flood mitigation that adapts to and works in sympathy with water, not in opposition to it. Water can be viewed as nurturing a land and its people, rather than as a hazard to be subjugated. Our research challenges existing paradigms, to shift flood management practices from the imposition of control over nature to a paradigm of acceptance, accommodation and adaptation to natural events. As climate-change-induced flooding becomes more frequent throughout the world, we are motivated by the potential to impact people's lives not just in Canada but across the globe.

In recent years, significant attention has been given to pulse-based protein production around the world. Pulses form a symbiotic relationship with rhizobia bacteria, whereby the rhizobia reduce atmospheric nitrogen into ammonium to produce protein-rich seeds. However, most pulse crops still suffer from suboptimum nitrogen fixation, especially under unfavorable environmental conditions (e.g., drought, low temperature). Therefore, discovering an innovative solution that can maintain or improve symbiotic nitrogen fixation (SNF) under environmental stress conditions will help improving protein production in pulses. Lately, cold-plasma (CP) technology has been studied to understand its potential for crop production applications, including seed germination enhancement. CP comprises of a mix of atoms, excited molecules, charged particles, and short-lived reactive oxygen and nitrogen species. We hypothesize that plasma seed treatments of pulses will change the seed germination, root hair formation, root growth, and root isoflavonoids secretion, which are critical for successful rhizobia invasion, nodule formation, and SNF. In this project, we propose to develop novel plasma assisted seed treatment technologies to improve SNF and protein production in pulses under environmental stress conditions.

Objectives:

1. Investigate the possible mechanisms involved in nodulation and SNF in pulses under plasma seed treatments.

2. Evaluation of plasma seed treatment on SNF, seed protein production, protein quality, and functionality in pulses under cold and drought stresses.

3. Optimization of plasma assisted seed treatment in maximizing nodulation, SNF, and seed protein production in pulses.

Three different plasma treatments (plasma activated air, plasma activated water mist, plasma activated water) will be tested with diverse pulse crops (e.g., pea, lentil, faba bean) under stress conditions. Seed germination, root hair formation, root architecture, isoflavonoids secretion, phytohormone production, rhizobia invasion through root hairs, nodule leghaemoglobin, nitrogenase activity, nitrogen fixation, and plant gene expression will be evaluated to understand the possible mechanisms involved in nodulation and SNF. The effect of plasma seed treatment on protein production, protein quality (amino acid composition, digestibility) and functionality traits (solubility profile, fat binding capacity, gelation, emulsification, foaming properties) will also be evaluated.

Background: Innovation is essential for societal adaptation to changing environmental demands. The rapid rate of change in contemporary society currently make innovation especially important. Innovation may involve introduction of a novel device, system, service, or intervention often aimed to improve competitive edge. Unfortunately, there are challenges associated with innovation.

Our research focuses on three problems associated with the evaluation of innovations. First, innovations often occur within a single discipline and use a narrow discipline-specific perspective to evaluate positive/negative consequences. Second, researchers examining the results of innovation rarely focus on the unintended and undesirable outcomes of the innovation. Indeed, only 0.2% of innovation studies exam unintended consequences despite innovations historically having caused wide-ranging problems. Third, researchers typically look primarily at the short-term rather than long-term consequences of the innovation9 and erroneously assume them to be static.

These innovation evaluation problems will be addressed by our multidisciplinary team. First, we will create a novel theoretical framework on the ecology of change triggered by innovation. Second, we will create a practical cross-disciplinary evaluation tool based on this framework. Third, we will assess the validity of the tool across various society sectors. Finally, we will create an online platform to ensure access to the evaluation tool by diverse users. This will result in researchers being able to assess the impact of innovation via a multidisciplinary model that, in addition to typical evaluation criterion, takes into account both unintended and long-term effects of the innovation.

Methods: We will use both qualitative (QUAL) and qualitative (QUANT) methods as per the broad steps below:

1. Refine framework; develop evaluation tool (QUAL: Consensus panel)

2. Psychometric validation (QUANT)

3. Pilot tool with innovators and evaluators (QUANT)

4. Online platform user experience study (QUAL)

Novelty & significance: Sustainable innovation depends upon evaluative feedback that can mitigate undesirable impacts. Our cross-disciplinary approach will yield a framework that is urgently needed for balanced, reflexive inquiry on innovations. Critically, it will facilitate discovery of critical conditions for the optimization and longevity of innovations and build a valuable evidence base for future innovators.

Polarization refers to the process by which strong bifurcations of opinions occur that divide a population. While a moderate amount of disagreement over public policies is healthy and arguably constructive in a democracy, its excess is often destructive. Even though Canada is not notorious for opinion polarization, data show that the polarization process appears to be underway particularly in areas such as energy and climate. Despite the advanced research in human science disciplines, a concrete viable approach to examine polarization is still lacking. Furthermore, models of opinion dynamics, that are mostly developed by the researchers in natural sciences and engineering disciplines, have also proved inadequate to address polarization.

We propose an interdisciplinary approach to analyze and manage polarization as it pertains to Canada through three objectives: (1) To collect various datasets based on which machine learning and dynamical models of opinion evolution are designed; (2) To analyze the previously designed models to derive concrete conditions for the polarization process, which determines whether polarization is existent or anticipated; and (3) To develop methods to manage polarization, that is whether to prevent or fix it, via appropriate intervention techniques.

The proposed research activity would be of high risk as first, a comprehensive interdisciplinary approach is crucial to bring in knowledge from independent and quite often extraneous disciplines such as control engineering, mathematics, sociology, and political science which is unprecedented. Most existing models are inherently incapable of explaining opinion polarization, mainly due to a lack of insights into the fundamental aspects of human psychology and social behavior. Second, creating consistently assessed control groups to obtain reliable information about the evolution of public opinion on certain subjects is complex and requires careful assessment. In return, obtaining the opinion dynamics model will be highly rewarding as it can explain the mechanisms and conditions of the emergence of popular extreme beliefs in both united and divided populations inspired by the socio-psychological analysis of the groupthink phenomenon. Consequently, an intervention is aimed in this research to alleviate known negative impacts of opinion polarization such as hostile behavior towards members of opposite political parties, weakened family foundation, and diminishing empathy and sympathy.

HIGH RISK: Canada's and the world's population are aging rapidly. Age-related physical, cognitive, and social declines require support but older adults (OA) also vary tremendously in abilities and needs. Virtual reality (VR) technology can foster physical, cognitive, and social engagement. However, for VR to achieve its full potential to support OA's health and wellbeing, their unique needs, abilities, and interests must be reflected in its design. VR design for OA is often driven by researchers, clinicians, and/or industry, where small teams of developers consult with a few OAs at milestones, tests are conducted in laboratory settings, and key design choices are made without OA input. We propose a flipped approach that goes beyond user-centered design whereby researchers take on a support role to OAs and trainees in the co-creation of a relevant, trusted, and enjoyable VR intervention.

OBJECTIVES: 1) Establish a model for perpetual tech development by a sustainable, interdisciplinary community of OAs, trainees, and academics. 2) Co-create a VR intervention for OA health and wellbeing that is valuable to key stakeholder/community groups. 3) Innovate responsible design by investigating how to support trust, choice, and safety for OAs.

INTERDISCIPLINARITY: Defining a model that successfully brings together stakeholders, who often have disparate goals and experiences, to effectively define objectives and sustainably collaborate to achieve them requires buy-in, innovation, and continuous engagement from all members. Our new approach to technology development will found a community of OAs, trainees, and researchers with expertise in health sciences, engineering, psychology, and computer science.

APPROACH: The community will engage in ongoing collaborative development, deployment, and evaluation of a responsibly designed VR intervention that supports personal health and social connection for OAs. Relationship building and knowledge transfer between community members will enable an agile design process, with researchers ensuring state-of-the-art methodology and outcome tracking.

The need for supportive housing for individuals with developmental disabilities (DD) has reached crisis levels. In Canada, thousands with DD live in conditions that may harm their health and well-being as they spend years on housing wait lists. Intentional community residences (ICRs), which offer staff support and designs emphasizing shared living and inclusion, have emerged as a practical option. However, little is known about how people with DD experience ICRs and how ICRs affect their health and well-being. Also, little is known about qualitative methods for engaging people with DD, which may be contributing to the lack of knowledge about their housing experiences. We aim to engage both gaps.

Objectives:

1. To explore (a) how individuals with DD and their families experience ICRs and (b) how ICRs affect their health and well-being.

2. To explore the use and effectiveness of qualitative methods for engaging people with DD.

We will collect data from ICR residents with DD via activity-tracking exercises, interviews, and a suite of arts-based methods that enables them to select a suitable mode of communication. Family members will also be interviewed. Interviews will end with questions about participation experiences to identify issues and advance qualitative methods for people with DD. Art products will undergo visual analysis, interview data will be coded, and a disability studies lens will be central to our analysis.

High Risk: This groundbreaking work will engage two knowledge gaps, demands an interdisciplinary team with expertise in fields not often combined, and has ambitious goals to mobilize findings in ways that enrich the lives and community participation of people with DD. We are uniquely qualified for this work given our expertise in disability studies, housing design, planning, qualitative methods, and various health fields.

High Reward: Our use of input from people with DD will shift how we plan and design ICRs and communities. We will advance this group's inclusion in processes of housing development, planning, and qualitative research. We will also produce real-world applications, such as: (1) ICR design best practices, (2) a methods toolkit for municipalities to engage people with DD in planning processes, and (3) a framework for planning/design advisory councils comprising members with DD. This work will have global implications for people with DD by enhancing their inclusion and well-being within their homes and communities.

Adolescence is an intense period when peer interactions are crucial to social development. Teens today interact heavily through online mediums which are often impoverished in noverbal cues and physical contact, curtailing opportunities to learn social skills, buffer loneliness and build resilience. Adolescent loneliness doubled from 2012 to 2018, as smartphone and social media use grew.

In other work, we are developing a platform that integrates nonverbal and physical cues into group digital interaction, with a novel approach of interaction through an "emotionally supportive swarm" of small table-bound droids as an embodied proxy for a teen friend group, reproduced polymorphically in each teen's location and joined by a hive mind. The small bodies interact physically with each other and their local human (e.g. teaming to squeeze a hand) with behavior generated, steered, adapted by and visually expressing members' emotions. A team of psychology and human-robot interaction experts are building this vision with AI-adaptive interaction and authoring behaviors atop a basic swarm.

Our goal here is to learn how to design such technology explicitly for teen subversion and ownership. How can it incite engagement, improvisation and extension? What traits will make it compelling, while also inherently inclusive and accessible? How can it enter teens' worlds, if framing as a therapeutic or educational practice undermines acceptance?

We will use early prototypes to co-create a framework for "designing for subversion" for youth, co-created with teen groups recruited by snowballing and maintained in longitudinal partnerships through workshops and social media clusters. This framework will guide us and others in creating open, extendable systems whose natural affordances lead to group and individual dynamics and benefits - e.g. opportunities to experience and build skills in expressing sympathy, play, hierarchy navigation and emotion in new ways that may feel more safe than other mediums.

This project is motivated by directly observed teen psychology and mental health concerns, and its results will inform a unique approach to family, social and clinical practices in supporting adolescent development. The interdisciplinary team makes a novel connection between computer science (HRI, affective haptics), computational media (social emotion regulation in teens) and psychology (adolescent social/emotional development, cognitive neuroscience, clinical practice).

By using the Universe as a laboratory, cosmologists can study physics at scales that cannot be replicated on the Earth. Recent observations have indicated new physics beyond that we understand: The expansion of the Universe is accelerating, requiring either a new energy-density component in the Universe or a modification to Einstein's theory of gravity. The problem has been given the name "Dark Energy", but little is known about it-simply naming the phenomenon does not imply we understand it! Digging deeper into recent cosmological measurements, one finds a more confused picture with different measurements yielding different conclusions. As a result, cosmology is often described as a field in crisis. However, it may not be so; the statistical tools used to analyse cosmological data are often archaic and in many cases may lead to biased results.

We will form a small interdisciplinary team, adapting methodological expertise from the field of biostatistics to this cosmological `crisis'. Biostatistics and cosmology are both tasked with drawing robust conclusions from available data but differ in their goals and methods. Bringing together experts in these disparate fields offers a fresh perspective on an important problem.

Many cosmological analyses adopt off-the-shelf statistical tools that make dubious assumptions about the nature of experimental data. In order to confirm-or overturn-the discovery of new physics, we need to understand the extent to which these assumptions may be affecting inferences. To that end, we will first conduct sensitivity analyses-via simulations and in application to the compressed data of multiple experiments-to characterize the impact of standard assumptions on inferences in cosmological analyses. Second, we will compare the standard analytic tools commonly used in cosmology to cutting-edge methodology in biostatistics and data science, and we will develop tools for robust inference tailored to cosmological analyses. Our hope is that a modernized statistical toolbox will help us understand what we truly know about the Universe and Dark Energy.

The discovery of new physics, or insights into that physics, would be an extremely high reward for this work. An obvious risk is that the new methodological developments offer no clearer picture of the conflicting cosmological evidence. Alternatively, we might find that current inferences are simply too optimistic, which, although interesting, would not be an important discovery!

Microbiologically induced calcite precipitation (MICP) is a cutting edge environmentally friendly ground improvement technique, where natural bacteria are used to produce bio-cementation. Currently, majority of researchers rely on the introduction of Sporosarcina pasteurii bacteria and urea as nutrient to achieve bio-cementation. Despite promising laboratory evidence, multiple scientific/engineering gaps restrict the use of this technology as a cost-effective alternative ground improvement technique. Current gaps include poor understanding of the involved bio-chemical-hydro-mechanical processes; limited success under certain environmental conditions; and lack of monitoring guidelines for engineering applications.

We propose a novel bio-cementation technique, for two critical applications concerning Canadian infrastructure: (i) stabilization of mine tailings; (ii) stabilization of low-volume gravel roads, specifically in cold regions in the North. Environmental contamination caused by mine tailing spills in Canada is a crucial problem that has killed hundreds of people and damaged hundreds of kilometers of waterways (economic loss ~30 B$/yr, Mining Assoc. of Canada 2018). With regards to low-volume roads, the extent of the Northern Territories and challenging climate conditions in Canada have resulted in substantial retardation of economic growth and increased carbon footprint (~129 M$ for road improvement, Gov. of Northwest Territories 2020).

Our interdisciplinary team (geomechanics, microbiology, structural health monitoring, pavement, mining) proposes a multidisciplinary research framework, for a high-risk high-reward application that encompasses three innovative areas: (1) identifying, characterizing, and assembling genes responsible for MICP in S. pasteurii into a wider range of bacteria to overcome environmental limitations (high-risk high-reward); (2) non-destructive testing (NDT) to monitor enhanced properties of mine paste and road subbase; (3)multiphase numerical modeling to understand fundamental coupled processes. Anticipated outcomes include: transformative environmentally friendly bio-cementation technique for cold regions and extreme environmental conditions; rigorous NDT process monitoring guidelines; and practical predictive numerical tools to optimize the effectiveness of MICP. The proposed techniques have broad implications beyond economic benefits, as they will significantly improve mine and road safety and reduce the carbon footprint.

Construction has one of the highest rates of injuries and fatalities in Canada. The objective of this proposal is to develop an anchorless, lithe, and cost-effective RTLS to reduce the rate of incidents in Canadian construction sites. Real-time Locating Systems (RTLS), and in particular Ultrawide Band (UWB) tracking, have shown potential to reduce injury rates in construction sites by enhancing situational awareness and informing workers when they are exposed to safety hazards. However, their actual deployment in construction sites has been a long-standing challenge. UWB anchors (readers that detect tags) require accurate and onerous calibration and connect to each other through cables; in the fast-changing environment of construction sites these become hazards themselves. This study aims to addresses the problem at source, vaulting over the evident steps of streamlining installation or wireless connection, by eliminating the readers from the UWB RTLS. The approach challenges the basic principle of RTLS which is based on communication between readers and tags. Here, tags will communicate directly with each other through UWB signals. Highly accurate location estimations are computed by integrating Machine Learning and Artificial Intelligence into Time-of-Flight (TOF) algorithms. Eliminating the readers also eliminates the need for Wi-Fi, which is not always available in remote and rural areas, and reduces the cost of each tracked object drastically, from $1000 to $25. However, worksite injuries are predominately related to human behaviour and characterized by epidemiological analysis of workplace injuries. This study is conducted through unique and unprecedented collaborations that take the research beyond its current engineering boundaries. Psychological analysis of human factors will define the most effective means to inform those exposed to safety hazards in terms of type of signal, the recipient, and the most efficient timing of signal regarding speed and behavioural responses. Injury epidemiology analysis will be used to determine the efficiency and effectiveness of the system in prevention of workplace injuries. Sports injury frameworks in kinesiology will be adopted to incorporate key intrinsic and extrinsic factors into the design of system. The application of the system expands beyond the construction sites to anywhere that tracking is needed. Anchorless RTLS, can also change the way the world works, as tracking is a large part of daily life today.

De plus en plus fréquents dans les unités de soins intensifs néonataux, les prématurés extrêmes (22-24 semaines de gestation) subissent une mortalité très élevée (50 -70 %) avec une prise en charge très dommageable pour le système respiratoire. Et, lorsque l'enfant survit, cela se fait à un coût élevé en termes de qualité de vie.

Pour répondre à ce défi médical, plusieurs chercheurs expérimentent des techniques de transition de l'utérus de la mère vers le monde extérieur. En 2017, une chercheure du Children Hospital of Philadelphia, a publié dans "Nature Communications" les résultats sur un dispositif extra-utérin qui a permis de supporter pendant 4 semaines des fotus d'agneaux équivalents à des prématurés humains extrêmes. Afin d'optimiser la maturation pulmonaire des nouveau-nés sous placenta artificiel et leur sevrage suite à la délivrance, il appert que ce dispositif doit se combiner à une technologie expérimentale de ventilation liquidienne totale (VLT) qui consiste à remplir et ventiler les poumons avec un liquide respirable. Des résultats préliminaires de VLT sur des ovins prématurés extrêmes suggèrent un effet prophylactique sur leurs poumons lors de la transition à l'air.

L'objectif d'adapter un respirateur liquidien à la scène expérimentale avec un placenta artificiel impliquera différents changements technologiques non triviaux grâce à la combinaison des savoirs de deux disciplines. Le génie pour la conception et la réalisation du respirateur liquidien adapté au modèle animal de très petit poids et à une VLT de transition performante. La médecine pour évaluer la méthode in-vivo sur des modèles animaux afin d'optimiser le respirateur liquidien avec la vision de son usage ultime en clinique. Les échanges entre les personnes des différentes disciplines seront cruciales afin que la technologie développée réponde aux attentes des cliniciens chercheurs.

Enfin, le respirateur liquidien pourra alors être utilisée dans le cadre de recherches conjointes de pointe. Ainsi, des résultats seront collectés afin d'évaluer les avantages d'une VLT en synergie avec un placenta artificiel sur des porcelets extrêmes prématurés. Au-delà de la finalité clinique de faire chuter le taux de mortalité des prématurés extrêmes en unités de soins intensifs néonataux, le projet pavera la voie au développement de l'utérus artificiel qui aboutira à une technique de grossesse extracorporelle.

Plastics are essential to modern life and used in myriad applications, including toys, food packaging, and construction materials. Microplastics (diameter <5mm) are most often generated unintentionally by degradation of larger plastics and fibers and have the potential to cause adverse health effects at all stages of life, including pregnancy and fetal development. Humans are primarily exposed to microplastics by inhalation of dust, ingestion of food contaminated by dust fall, and drinking-water. Nanoplastics (diameter <1 µm) are small enough to translocate from the lungs and the intestines into the blood and accumulate in other organs such as the placenta and fetal brain. Despite these concerns, the accumulation of nanoplastics in human tissue and its impact on human health remains unknown. This knowledge gap exists because of the dearth of analytical methods that can reliably detect nanoplastics.

Multidimensional mass spectrometry (MMS) hyphenated with comprehensive two-dimensional gas chromatography (GCxGC) is an innovative technique that will enable the detection of nanometer sized plastics that are otherwise invisible to microscopy and spectroscopic methods. The goals of this research are to: (1) Develop a GCxGC-MMS method that is capable of accurate determination of nanoplastics in tissue; (2) Study the effects of nanoplastics exposure on fetal and placental development using advanced biomedical imaging modalities (ultrasound, magnetic resonance imaging) and experimental mice; (3) Establish the types, sizes and concentrations of nanoplastics that pregnant women are exposed to by characterizing an existing repository of placental tissue and identifying associations with clinical data such as placental blood flow and birth outcomes.

Our team has a record of collaboration and cross-disciplinary expertise in mass spectrometry, imaging physics, mouse models of pregnancy, environmental chemistry, and maternal-fetal medicine. With the completion of this study, we will have addressed a critical gap in our knowledge of the occurrence of nanoplastics and the extent to which we are exposed to these particles. We will have identified whether nanoplastics are associated with adverse pregnancy outcomes and demonstrated the effect on placental and fetal development. These are the crucial first steps towards establishing guidelines to limit exposures, and ultimately to prevent adverse pregnancy outcomes that result from exposure to nanoplastics.

The COVID pandemic has shown us the increasing need for accessible solutions for remote assessment of patients with hand injuries. We have worked on a transformative augmented reality (AR) framework that will be easily adopted within current clinical workflows. We developed a low-cost and high-accessibility remote assessment tool for finger range of motion. This AR application ("DIGITS") utilizes the front facing camera of a smartphone to track bony landmarks of the hand and uses deep learning to classify the results of the range of motion.

Funding from this application will allow us to build a database of cases, to have a baseline range of motion from a healthy population across all demographics (age 5-80, equal representation of sex). Similar measurements will be taken on patients with hand pathologies such as trauma, arthritis, and congenital anomalies. We will refine our AR application based on results, and work on offering a more comprehensive platform.

After validating the range of motion assessment in patient populations, we will build in velocity and dynamic tracking, as well as a remote assessment of strength and dexterity. In addition, additional remote monitoring capabilities such as scheduling or physical therapy exercises, post-operative monitoring of swelling and potential infection, as well as self-reported pain scales will be integrated. All of these aspects will provide us a more comprehensive picture of the recovery of hand function. In collaboration with our local experts in AI, we hope to incorporate machine learning to understand the recovery trajectory of patients with a variety of pathologies, basic demographic, and rehabilitation information.

The implementation of this intervention will be studied in a clinical setting in terms of its effect on the speed of post-trauma recovery of full pain-free range of motion. Additionally, the patient satisfaction as well as perceived autonomy with regards to one's own health will be assessed.

With the increasing adoption of telemedicine and virtual care, strong support exists to incorporate AR in the delivery of high caliber care. The "DIGITS" application will serve as one of the first next generational AR virtual medical care technology for hand tele-rehabilitation to serve our community's ever evolving needs. Future expansion of the project can include additional orthopedic issues including full upper extremity or lower extremity rehabilitation.

A major challenge in permanent gene therapy for genetic diseases is the low efficiency of gene targeting. Lung epithelial cells are particularly challenging to manipulate due to the structural complexity of the airway epithelium, the high cellular turn over of surface epithelial cells and the host immune responses leading to a need for repeated gene delivery. Developing a novel strategy using a single delivery vector for permanent gene correction is required for effective gene therapy approaches in the future. Recent advances in engineered endonucleases, specifically the CRISPR-Cas systems, has made site-specific permanent gene correction possible. However, gene editing efficiency remains a challenge that limits the feasibility and safety of these systems for in vivo clinical applications. Recently, two independent groups have discovered that the bacteria Scytonema hofmanni and Vibrio cholerae, can hijack the CRISPR-Cas system to guide a Tn7-like transposon for site-specific and high efficiency gene integration without generating double-stranded DNA breaks. This is important as DNA breaks often introduce errors in a mammalian cell's natural DNA repair mechanism thereby reducing targeting efficiency. To date, the CRISPR-Cas guided transposon system has not been used for genetic manipulation in mammalian cells. Our goal is to engineer this system to genetically alter genes in human cells and harness this newly identified technology for permanent gene replacement therapy.

Our unique team has the expertise and models to re-engineer codon-optimized genes required for the CRISPR-Cas guided transposon systems and develop powerful gene expression cassettes specifically for mammalian cells. Next, we will engineer a single viral vector for efficient delivery of the CRISPR-Cas guided transposase system into human airway epithelial cells. Using a helper depended adenoviral (HD-Ad) vector, we can achieve efficient targeting of airway basal stem cells, a key end-goal for permanent gene correction in native airways. As proof-of-concept, we will test the efficiency of gene correction and functional restoration of a defective protein (Cystic fibrosis transmembrane conductance regulator or CFTR) in iPSC-derived airway models harbouring cystic fibrosis genetic mutations. Our success in developing a highly efficient gene targeting system will be a major step forward in the use of gene therapy for treating rare genetic diseases. 

Photometry is becoming an increasingly popular approach for monitoring the brain activity of laboratory animal models in biomedical and preclinical research. Our interdisciplinary team of experts in motor neuroscience and optical physics aims to develop a new photometric system to spatially monitor the neural activity of several adjacent brain regions with minimal invasiveness using a single fiber. Typical optical fibers used for photometry have a flat-faced tip, which limits the volume of neural tissue that can be monitored to the region below the tip of the fiber. Alternatively, tapered fibers have been recently developed to spatially activate distinct areas of the brain along the fiber by remotely adjusting the angle of light input to the fiber without moving the implant. Using such tapered fibers in transgenic mice, we propose to monitor the neural activity of restricted neuronal populations in distinct but adjacent brain regions pertaining to motor control and locomotion.

Our first objective is to design and fabricate tapered optical fibers and test their physical properties in a fluorescent gel. We will also develop a new photometric device to modulate the light input angle and collect the fluorescence on a camera based on the light output angle, thus allowing spatial reconstruction of the fluorescent environment surrounding the tapered fiber.

Our second objective is to test in vivo the efficacy of this new photometric system by monitoring the calcium activity of distinct but adjacent brain regions in transgenic mice. Using different light input angles and genetically encoded calcium indicators, we will measure neural activity of adjacent mesencephalic regions known to initiate or stop locomotion. This neural activity will be correlated to locomotor activity by kinematic and electromyographic recordings in freely behaving transgenic mice.

By the end of this project, we will have optimized the design and fabrication of a new photometric system with tapered optical fibers to deliver light into the brain with revolutionary versatility and minimized invasiveness, overcoming the limitation of photometric devices currently available on the market. This system will enable photometry of adjacent but distinct brain regions with extremely thin and sharp optical fibers.

Our university's land acknowledgement emphasizes that we take responsibility for the violence, harms, and mistakes of the past, and dedicate ourselves to moving forward in partnership with Indigenous communities in a spirit of reconciliation and collaboration. This vow speaks directly to understanding the University's complicities in the violence of settler colonialism, and, like this proposal, is grounded in ideas of Truth-Telling, Social Repair and Atonement. Founded in 1962, our department houses a large number of Ancestors and their belongings. Over the past two years, we have begun an Indigenous-led initiative for respectful repatriation. The work is guided at every stage by our partners who serve as Grandfathers, Grandmothers and Elders, and who work in Indigenous Studies and Administration. Our goals involve moving beyond contemporary curatorial practices of repatriation that tend to be isolated by institution, and department, across Canada.

We will:

1) Mount a coordinated, transdisciplinary and Indigenous-led response to the respectful need for repatriation, truth-telling, and accountability across the University. 

2) Research the complicity of our institution in the violence of Settler Colonialism that brought the Ancestors and other belongings here, and model ethical institutional transparency, responsibility, and atonement. 

3) Develop collaborative provincial best practices for institutions in support of Indigenous Nations' truth-seeking and repatriation, and a 10-year holistic, inter-institutional implementation plan grounded in Indigenous sovereignty and priorities.

Through these objectives, we will build a collaborative supportive framework for committed action regarding repatriation efforts, and a respectful ethical foundation for Canadian post-secondary truth-telling and atonement. 

This work is complex and sensitive, and must emphasize respectful process and Indigenous protocols to walk a path where community consensus and wellbeing is paramount. Dependent on working together in novel ways in constant flux, there is thus a high risk of unanticipated challenges. Nevertheless, the respectful foundation already established, and the integration of such an interdisciplinary and cross-sector team, places us in a unique position to build a truly collaborative, Indigenous-led, respectful, and high reward support response to these pressing needs for institutional truth-telling, decolonization, and reconciliation. 

Climate change is causing dramatic extremes in water availability, resulting in more severe and prolonged droughts which are a very serious threat to world food security. Agricultural productivity has greatly benefited from molecular breeding programs that improve crop resilience to environmental stresses. These breeding programs focus on shoot traits as they are readily visible to breeders. Breeding for improved root traits has lagged behind because roots grow in opaque soils. To address this, we have been developing root growth and imaging platforms whereby roots are readily visible for imaging, including hydroponic, gel, and soil-based growth systems. These platforms are now allowing us to image, analyze and quantify traits associated with root system architecture (RSA) on hundreds to thousands of plant varieties in specific genetic mapping populations. It is now widely understood that variation in RSA is a major genetic trait for efficient acquisition of water and mineral nutrients. Our recently developed root imaging platforms are allowing us to genetically map RSA traits that will lead to identification of genes that allow us to improve crop water use efficiency via molecular breeding and gene editing. In this proposal we will phenotype well-structured wheat mapping populations for drought tolerant RSA traits. Currently, the major bottleneck in improving crop root traits is determining the RSA phenotypes that will be the foundation for breeding for better root systems. We will address this by using deep learning methods that we have found to excel in these types of image analysis tasks, precisely because they do not prescribe features a priori, but instead learn the best features directly from examples. Our group has pioneered a novel method for phenotyping stress responses from shoot images by learning image features that best discriminate between plants grown in normal vs. stress conditions. This latent space phenotyping (LSP) approach automatically generates a response-to-stress trait from an image dataset that can be used in genetic mapping. LSP has never been attempted for RSA images, and has the potential to dramatically increase the predictive power of genetic mapping for variation in RSA, whether it is due to genetic variability within populations, or to responses to drought and other abiotic stresses. If successful, this methodology will have a substantial impact on research and crop breeding for improved stress resilience.

High-risk/High-reward: Based on Canada's geology, Arsenic (As) represents one of the most prevalent environmental carcinogens linked to skin, bladder, kidney, prostate, lung, breast and cervical cancer in Canadians. Half of Canadians are susceptible to develop cancer in their lifetime, with risk modified heavily by genetic susceptibility, behavioural factors and environmental exposure. Whilst cancer risk prevention strategies have extensively focused on physiological and behavioural factors, environmental exposure as a cancer risk factor has not been well studied which has led to missed opportunities to reduce the risk of cancer through environmental population health programs, such as reducing chronic arsenic exposure by treating contaminated groundwater currently consumed by Canadians. Increased As levels in human toenails has been detected in the Atlantic Partnership for Tomorrow's Health (Atlantic PATH) cohort. Innovative population health interventions, focusing on predicting the susceptivity and type of As induced cancers across Canada are urgently needed to mitigate the increasing prevalence of cancers in Canada.

Objectives: To investigate environmental cancer biomarkers, and to develop innovative data-driven environmental cancer risk assessment tools to help reduce the incidence of cancers caused by As exposure in Canada.

Approach: We propose a multi-disciplinary approach that integrates analytical toxicology, Machine Learning (ML) and population health to (a) Profile As species and metallomes of human toenails that cause cancers using toxicological analysis, (b) Develop ML based predictive models to predict As induced cancer risk based on As metallomes profiles, and generate As cancer risk phenotypes by data clustering; (c) Assess relationships between metallomes profiles and cancer using ML based data analytics to help develop population health based cancer prevention strategies.

Novelty and Significance: This project is proposing an innovative proactive, community-facing, non-invasive cancer risk assessment solution targeting environmental carcinogens, as opposed physiological and pathological approaches that are incidental, costly and invasive. Significantly, this project will generate cancer screening tools to (1) impact environmental As exposure causing cancer across Canada; (2) predict the risks for different cancer types due to environmental factors; and (3) reduce the burden of cancers due to As via population health interventions. 

News outlets and social media portray images of the white vigilante that calls on law enforcement officials to regulate space in gentrifying areas, as shown in viral videos of White, often female, residents calling the police on Black residents in public spaces. These acts of indirect policing of marginalized people in order to make way for shifting cultural norms in whitening neighborhoods have also taken a subtler approach: the use of social media platforms (like Facebook, Reddit, Instagram and NextDoor) to warn others of crime and danger, cultivating online vigilantism among gentrifying residents. As Canadian cities continue to grow and attract investment, questions of inclusion for marginalized groups like Indigenous peoples and immigrants in changing neighborhoods are key to the development of a more equitable society. Accordingly, we are seeking funding to answer the following: What effect does participation in social media networks have on residents' perception of crime, safety, law enforcement, and behavior? And how does it impact the way law enforcement officers carry out their roles?

Using a mixed method approach, we will observe the effect that engagement on social media platforms can have on the attitudes of residents, and the degree to which law enforcement are responding to this information. Utilizing emergent methods in natural language processing, we plan to observe sentiment and polarization in social media posts related to neighborhood safety, character, and identity in three neighborhoods: Moss Park (Toronto), Saint-Henri (Montreal), and Downtown Eastside (Vancouver). To determine the impact of these forums on policing practices and resident perceptions, we will also use data from interviews with police officers and residents.

This project will constitute one of the first applications of natural language processing to show the effect that participation in social media has on real world behavior and culture. One risk is that algorithms are not yet trained to identify racialized sentiments or polarization, and must be developed for this purpose. Our ability to gather data is also sensitive to the accessibility of the social media platforms we select, and the cooperation of police. However, if successful, this research could be a breakthrough in our understanding of both strategies to re-imagine public safety and develop more prosperous and inclusive Canadian cities.

In recent months, the rapid acceleration of developments in commercial space travel through tech giants like SpaceX and Blue Origin have threatened to undermine the assiduous work of raising the profile of women (both past and present) in the fields of engineering and space science. Space is increasingly seen in the public eye as a new site for capitalist and colonialist mindsets. At the same time, the landing of Perseverance on Mars has also revitalized a widespread interest in the interpretation and experience of the new worlds in space that have hitherto been subjects of fantasy and fiction. In this unprecedented time of access and democratization of tools, there is an urgent need for a reframing of space not as a `new frontier' for appropriation and extraction, but as a critical site for considering how we can as a whole, participate in pioneering explorations in the skies above us. Space-art has been recognized as a tool for public outreach for many years in its myriad representations of data, creative fiction and myth-making. These networks are sites for further potential today, in the rising need for amateur space observations to support recording and identification of an increasing number of space objects like satellites and debris - termed Space Situational Awareness (SSA). Therefore, the objectives of this project are to (1) develop hybrid and synergistic strategies across space engineering, community practice and visual arts to catalyze a collective imagination and envisioning of future worlds (2) create access and accountability in the use of high level data for public workshops around SSA data visualization and physical/virtual modes of creative data visualization (3) Promoting the representation of women and racialized minorities in the engineering/science disciplines where they are traditionally underrepresented. (4) develop new technologies and workflows through a combination of citizen science activities e.g. backyard telescopes; and cutting edge tools in the field e.g. nanosatellite design and deployment, artificial intelligence for image processing etc. The team will collect qualitative and quantitative data around SSA, space exploration and the commercialization through interviews with workshop participants, field specialists and social media analyses. We will also adopt research-creation strategies around data visualization and public exhibition formats, constantly evaluating our methods for effective communication.

Les enjeux de justice sociale sont au cour des défis contemporains de nos sociétés. Incontestablement, les inégalités économiques et culturelles croissent et créent des tensions sociales et des dynamiques d'exclusion difficilement soutenables, ainsi que des problèmes environnementaux sans précédent. L'éducation mathématique n'est pas neutre quant à ces enjeux et nous devons penser urgemment à la manière dont elle peut contribuer à y faire face.

Or, des perspectives émergentes tentent de repenser fondamentalement l'enseignement des mathématiques afin d'accueillir et affronter ces enjeux de justice sociale. En s'ouvrant à des champs de recherche externes comme l'éthique et la sociologie, elles soulignent comment, à travers les pratiques mathématiques et leur enseignement, sont convoquées tout un ensemble d'attitudes et de manières d'être dans le monde qui participent de l'incrustation des mathématiques au monde social et politique. Cette mise en lumière porte avec elle la possibilité d'une nouvelle éducation mathématique, plus éthique, car davantage lucide et sensible quant aux enjeux sociaux et politiques inhérents aux mathématiques.

Cela dit, ces perspectives éthiques émergentes restent pour l'instant limitées au domaine de la recherche et leur appropriation et valorisation manquent fortement dans la pratique. C'est pourquoi, au sein de huit universités francophones canadiennes, une approche participative sera déployée auprès des formateurs des enseignants en mathématiques. Elle permettra la création conjointe d'espaces de réflexions dialogiques sur ces perspectives éthiques, ainsi que sur leur articulation avec la formation des enseignants. Dans ce contexte, notre étude a pour objectif de :

- Documenter la manière dont ces perspectives éthiques sont accueillies et pensées par les formateurs en termes théoriques et pratiques,

- Rendre compte, par une réflexion conjointe, des manières envisagées de développer la formation des enseignants selon ces perspectives.

Notre étude se démarque par la combinaison inédite d'ancrages et thématiques multiples, ainsi que par une approche participative et dialogique audacieuse auprès d'une population peu étudiée. Elle mettra en place un puissant espace réflexif et créatif, susceptible d'engendrer une émulation sans précédent dans le milieu. A long terme, les retombées éducatives et sociétales de tels changements pourraient être d'une ampleur très vaste en termes de bien-être social, environnemental et économique.

Computer-aided molecule/material design is hindered by the inability of current computational methods to rapidly, yet accurately, preselect substances that are likely to have desirable properties. In short: methods that are fast enough to screen millions of compounds are too inaccurate, and methods with sufficient accuracy can be applied to at most a few thousand compounds.

Low-cost black-box simulation methods suitable for high-throughput computational modelling--whether they be based on direct quantum simulation of the substance, classical atomistic parameterization, or modern Machine-Learning (ML) methods--tend to be unreliable when the system is strongly correlated. Strong correlation is, alas, ubiquitous, occurring whenever chemical bonds break and form, in redox-active catalysts, as well as in materials (molecular magnets, spintronic devices, superconductors) where electrons have long-range order.

This project proposes a novel approach to address the problem of strong correlation and aims to design new tools that are computationally efficient and easy to use enough for nonspecialists to guide their research and enrich their understanding. Specifically, we take a key concept from physics (the one-electron reduced density matrix; 1RDM) and draw a link to quantum information theory (the quantum marginal problem) and pure mathematics (numerical ranges). With these insights, instead of determining the 1RDM by solving the Schrodinger equation, we can compute the 1RDM by solving a (non-commutative) multi-marginal optimal transport problem. This approach opens the door to powerful methods, concepts, and techniques available in the world of optimal transport, allowing us to use ML techniques, notably deep learning.

Deploying these functionals in software will allow nonexpert users to choose the right balance between computational cost and accuracy for their specific (bio)chemical and materials science applications. Specifically, we are targeting applications related to band-gap prediction (e.g., for semiconducting devices, LEDs, and solar energy applications), industrial catalyst design, and cancer drugs that use covalent inhibition.

The team consists of chemists and mathematicians with interdisciplinary training/research in bioengineering, materials science, physics, and computer science. HQP will be trained at the nexus of these disciplines so that they learn not only to speak, but to dream, in the languages of chemistry, mathematics and AI.

Neonatal hypoxic-ischemic encephalopthy (HIE) is a devastating condition resulting from a disruption in oxygen-rich blood flow to the fetus or neonate in the perinatal period. Neonatal HIE has an estimated incidence of 3 per 1000 live births and is responsible for the death of over 500,000 newborns worldwide. The current standard of care for neonates presenting with moderate to severe HIE is therapeutic hypothermia (TH), which has been shown to reduce mortality and improve neurodevelopmental outcomes. However, despite TH, approximately 40% of infants with moderate to severe HIE will die or suffer significant developmental disability. There are several ongoing studies of potential adjunctive therapies for HIE, but to date, none have shown definitive benefit or gained widespread utilization. Therefore, there is great need to identify novel therapeutics for HIE.

In recent years, the drug metformin has emerged as a promising neuroprotective agent, with numerous in vitro and in vivo studies demonstrating positive impact on the birth of new neurons (neurogenesis) and the ability of the brain to adapt after injury (neuroplasticity). Importantly, in preclinical and clinical studies in older children, metformin can be administered months after the initial brain injury, as the mechanism of action improves neural circuit remodeling and recovery. This is important, as metformin can potentially serve as a neuro-restorative agent after the initial insult during the newborn period. Metformin has been used as an anti-hyperglycemic drug for over 60 years with very limited safety concerns. However, metformin has not been administered to children under 2 years, nor has it been administered to infants after brain injury. Given the unique drug metabolism of infants, it is critical to establish the safety, maximum tolerated dose, and drug metabolism of metformin in this population before proceeding to studies of metformin efficacy for HIE-associated brain injury. Therefore, we propose a Phase I randomized safety and feasibility trial of metformin in infants affected by HIE, with the following Specific Aims:

1. Assess the safety and feasibility of metformin administration in infants with HIE.

2. Measure pharmacokinetics and pharmacodynamics of metformin in infants with HIE.

Importantly, this study will serve as the foundation for future studies to develop metformin as a novel neuroprotective therapy for HIE.

Loss of musculoskeletal (MSK) function represents the primary cause of chronic disabilities, according to the World Health Organization. In Canada, the economic burden of disabilities from MSK diseases is estimated at a total of $25 billion. A quarter of the total cost incurred by MSK diseases is attributed to degenerative joint disease. Prosthetic joint replacements have revolutionized the care provided to patients suffering from degenerative joint disease. According to the Canadian Joint Replacement Registry, over 130,000 joint replacements were performed across Canada in 2019-20. Despite the immense benefits of these devices, prosthetic joint infection (PJI) is a devastating complication that impedes their intended functional benefits. The incidence of PJI ranges from 1-2% after the initial joint replacement in healthy individuals. The ultimate goal of this proposal is to develop a superior therapeutic modality for PJI using a Single-stage Multipurpose AntimicRobial implanT (SMART) device that will effectively eradicate the bacterial infection after a single intervention while preserving patient's function and mobility. Successful implementation of this SMART device will eliminate the current need for multiple operations and prolonged use of systemic antibiotics required to control the bacterial infection. We plan to design an implant with a smart interface that provides a dual function: 1) controlled local delivery of therapeutic antimicrobial doses that target the bacterial biofilm causing the PJI; 2) enhanced osteointegration of surrounding host bone on the implant surface to ensure its functional stability. The novelty in our single intervention approach for PJI is reflected in several folds: 1) combining antimicrobial therapies of phage cocktails and antibiotics; 2) designing a controlled local delivery mechanism for this combination therapy; 3) providing a dual functionality of the implant surface design by targeting biofilm eradication and promoting osteointegration. This project will impact the health care system by reducing the associated economic burden of PJI. This project also offers a novel therapeutic solution leading to a shift in PJI management, improving patient quality of life and provides a proof of principle for the future development of antimicrobial coatings for other implanted medical devices.

COVID-19 patient outcomes depend on sustaining blood oxygenation rates, and this means maximizing lung drainage efficacy. Interestingly, maximizing drainage in a porous media such as the filter resin inside water softeners has similar implementation challenges. We propose the development of a new device to assist drainage not only in lungs but also in water softener filters through vibrational excitation of detritus/salt&minerals using an optimized combination of mechanical vibrations at different frequencies. Currently lung drainage is enhanced using intrusive equipment or percussive impacts, aggressive massaging, and hand vibrations on the back of the patient without any optimization in the repetition rate of the impacts nor the use of complementary vibrations. There is also not a single device on the market to clean the water softener filters from outside the tank.

This project will bring together an interdisciplinary team of experts in four main disciplines (i.e. ultrasonics, medicine, geology, and engineering) to create a new hand-held vibratory drainage stimulation device: VDSD; which will use an optimized combination of high and low frequency sources at different selectable amplitudes. We have the required combined theoretical and experimental experience to start a new era in the use of controlled vibrations for drainage stimulation. First, we will experimentally determine the optimum sensor (source) configuration and frequency ranges for the VDSD using physical models of synthetic tissues that mimic blocked alveoli and the actual filter resin inside water softeners. We will use real-time imaging and flow measurement techniques to assess the progress of the induced draining. Second, we will use numerical models to optimize the design of our novel device. Then, we will build a laboratory prototype to lay the foundation of the final VDSD.

This project is high risk because the optimized combination of three vibration sources in three different frequency-ranges (i.e. ultrasonic, acoustic, and seismic) is novel and has never been used for drainage stimulation in lungs or water filter resins. It has the potential for high reward with broad impact and reach: it will push the boundaries of medicine, geology, ultrasonics, and engineering to create a "smart" device capable of optimizing vibration sources to help patients with lung blockages and millions of homeowners in Canada to reduce the waste of water and excessive disposal of salt in the environment.

Infants born ≤26 weeks of gestation are at increased risk of developing bronchopulmonary dysplasia (BPD) and disorders of control of breathing (COB). At this gestational age, both the lung and brainstem are immature and vulnerable to injury, with prenatal and postnatal inflammation being key risk factors. Local lung inflammation without systemic illness is associated with increased frequency of apnea in premature infants, suggesting the existence of lung-brain axis supported by pre-clinical studies; lung inflammation increases expression of inflammatory cytokines in brainstem nuclei associated with altered ventilatory responses to hypoxia. Only a limited subset of brainstem nuclei and inflammatory cytokines have been studied. A thorough characterization of the effect of lung inflammation on neuronal and non-neuronal elements that shape the central respiratory network has not be done. Moreover, few effective and safe therapeutic options for BPD and disorders of COB exist. We seek to address these gaps by exploring the effect of a novel therapy, L-Citrulline (L-CIT), on lung function and brainstem signaling in a rodent model of BPD. Pre-treatment with the non-essential amino acid, L-CIT blocks lipopolysaccharide (LPS) induced lung inflammation and histopathology consistent with BPD. Whether L-CIT also blocks inflammation in the respiratory network induced by lung inflammation is unknown. We will apply high resolution spatial mapping of cell type-specific transcriptomes in tissue sections, enabling unprecedented characterization of molecular mechanisms governing adaptation of the central respiratory network. To characterize the extent of lung-brain axis inflammatory response and the effect of novel therapies in mitigating adverse effects in the central respiratory network, we propose the following Aims: 

1. Determine the effect of L-CIT on lung function and COB in a model of BPD induced by intrapulmonary LPS administration during early lung development.

2. Determine the effect of L-CIT on LPS induced lung inflammation on brainstem inflammatory response by a) spatial mapping the cell type-specific transcriptome in the central respiratory network, and b) assaying for the presence of microglial-derived extracellular vesicles in the brainstem and blood.

Although high risk, these studies leverage cutting-edge molecular biology, physiology, and neuroscience to explore a novel, safe therapy that could decrease co-morbidities in premature infants.

Embryonic development involves an orchestrated dance between billions of cells that specialize to form functional tissues. Tremendous effort was involved to untangle the genetic rules that govern this dance, forming the basis of our understanding of cells as programmable units of life. The cell's programmable "processor" is composed of an interconnected network of genes, akin to computer circuitry, that direct its behaviour in response to signals. Manipulating the cell's processor has led to development-in-a-dish, in which therapeutically-relevant cells are derived from embryonic stem cells (ESCs) by manipulating their processor. Despite lab-grown cell therapies in clinical trials, we still lack the ability to engineer high-quality cell products and coax ESCs to give rise to tissues with prescribed functions. To predictably program ESCs, we need a paradigm shift in the way we engineer cells.

Computer-aided simulations of ESCs have the potential for game-changing rewards, moving us from "tinkering" to "controlling" their fate. To date, models have successfully simulated the core network of genes that compose the ESC's processor. However, they are far from predicting the composition of cell types that emerge from ESCs. A key missing ingredient is biological time, which follows the rhythm set by the cell cycle. Cell cycle duration varies greatly between cell types and can alter gene expression; however, it has only recently become possible to measure, making it a new perturbable parameter for controlling cell fate. We propose to revamp models of the ESC processor, forming the foundation of a new class of cell simulators that use cell cycle to reliably predict and program the trajectory of ESC-derived cells.

In our high-risk proposal, we will pioneer an interdisciplinary approach using 3D computational modeling, synthetic biology, and single cell transcriptomics to control ESCs as they specialize. Using an experiment-to-theory loop, we will design and validate an augmented computational model, incorporating cell cycle to model dynamic cells that give rise to emergent populations of specialized ESCs. The model will be used to push boundaries, driving synthetic biology experiments that enact model-based designs. Using genetic engineering tools, we will program key genes along with cell cycle duration to control ESCs. This framework will fundamentally change the way we engineer cells, accelerating the biotechnology ecosystem in Canada and beyond.

Considerable growth in the global population and economy leads to an increase in fuel demand. This requires production of clean fuels with minimum CO2 emissions to maintain climate, energy, political, and social security. Hydrogen is a promising carbon-free fuel that can be produced from various renewable sources such as wind and biological systems. The microalgal hydrogen production has potentials of negative CO2 emissions and is less energy intensive, compared to the fossil fuel-based hydrogen production. Also, the operating conditions in bio-hydrogen production processes are generally atmospheric pressure and temperature. Brown algae are a large class of multicellular algae species; they are mainly found in marine environments. The brown algae play a key role as food as well as potential habitat for several other species. This type of algae has a high potential of hydrogen production through both aerobic and anaerobic conversion modes. There are some technical and non-technical challenges with algal hydrogen production such as biological (oxygen sensitivity of hydrogen, light capture efficiency, and electron supply), scale-up, and economic prospect. This proposed project aims to explore important technical and non-technical aspects of hydrogen production from brown algae through experimental and modeling studies. In the first phase, the current status, future perspectives, and possible challenges of bio-hydrogen production are studied through economic and statistical analysis. Then, an experimental work is conducted to produce hydrogen using brown algae at various operating conditions through a systematic design of experiment. The experimental phase covers microbial community analysis, analytical tests, and kinetics tests. Molecular dynamic simulations will be then conducted to tailor a suitable microbial community and to determine interfacial, thermodynamic, and structural characteristics of brown algae. The interaction/conservative forces between molecules and kinetics reaction rates will also be investigated. The last phase is to conduct energy, exergy, and economic analysis of bio-hydrogen production through hybrid modeling tools to obtain optimal operational conditions where a strategic marketing plan is proposed to address the challenge of large-scale infrastructural investments. This research can lead to considerable economic and environmental benefits to Canada, particularly further progress in decarbonazation strategies and green energy supply.

The proposed project will research an implementation of AI to augment disability-related assessment of functional limitations and service recommendations in higher education. Provision of disability services in postsecondary settings is a legislated human rights mandate. Participation and success in postsecondary education is one key factor that eliminates the large gap in rates of employment for persons with disabilities in Canada. This is a high-risk/high-reward, interdisciplinary project that aims to address the need for expertise, efficiency of procedures, strength-based considerations and student self-advocacy in assessment of functional limitations and interpretation of results to inform support for students with disabilities. There are critical ethical and technical challenges inherent in this project, but also potential for significant gains in increasing access and participation for persons with disabilities in higher education.

The research project will be carried out at a university where assessment of functional limitations is part of the intake process at the student disability services. The research data includes over 2000 existing samples collected from students in recent years with the World Health Organization's WHODAS instrument and newly collected data. The AI methodology will consist of multi-label classification and a variation of the Bidirectional Encoder Representations from Transformers (BERT) applied to numerical WHODAS scores to select relevant interview questions and interpret free-text student responses along with their WHODAS profiles to generate recommendations and rationale. Students with lived experience of disability and subject-area experts from disability services will collaborate with a multidisciplinary research team to ensure a meaningful and ethical approach to the development of AI-augmented assessment of functional limitations.

There are three overall components to the research project:

1) Collection and consolidation of functional limitation datasets from the WHODAS and student responses to clarifying background, historical, and strength-focused questions;

2) Development of sets of expert disability services recommendations with rationales for given profiles of student functional limitations;

3) Iterative design and training of a machine learning model to interpret numerical data and student responses, and produce outputs with recommendations for student services. 

Despite great advances in technology and in the understanding of biological systems, vaccine discovery and development is still a lengthy, expensive, difficult, and inefficient process with a low rate of therapeutic discovery. The discovery and development of new vaccines is multidisciplinary. Historically, mathematical modelling has been used as a tool for economical assessment, after a vaccine candidate has been fully developed, tested, and ready for market.

It is increasingly recognized that the incorporation of mathematical modelling into vaccine discovery/development at the bench and clinical trial stages can optimize and accelerate the entire process -- mathematical models of immunological and vaccine candidate processes and characteristics can be used to provide both quantitative and qualitative measures of immune system outcomes that cannot be measured in the lab, or in clinical trials. Modelling studies, which are also much cheaper to conduct than extra laboratory experiments, can also be used to quantify pharmacokinetic/pharmacodynamics in individuals with different immune system characteristics, that can then be used to obtain measures of vaccine efficacy and effectiveness in populations. A full picture of the costs and benefits of a vaccine can thus be developed.

In this project, we combine expertise in mathematical modelling, immunology, and vaccine development, to determine a mathematical modelling framework for vaccine discovery and development. Mathematical models of immune system interactions with vaccines + adjuvants will be developed and fit to vaccine and immune system data (for different vaccines) from in-vitro and in-vivo studies, and clinical trials, to uncover rates of different immunological processes, and immunity outcomes that are not observed/measured. Mathematical analysis will be used to quantify correlates of protection from different vaccine + adjuvant combinations, in both the humoral and cell-mediated arms of the adaptive immune response. Sensitivity analysis will be used to assess immunity outcomes given different immune system conditions. Finally, machine learning will be used to classify and identify vaccine formulations with acceptable characteristics for optimal outcomes. Ultimately, the framework will provide a process under which vaccine discovery and development can be optimized, for accelerated identification and design, for efficient economic outcomes, and maximal population benefit.

Extreme prematurity remains an unsolved clinical problem. More than 1 in 10 babies are born prematurely and preterm birth continues to increase across the globe. Advances in neonatal care have failed to substantially improve mortality and morbidity, especially in the extremely premature. Current strategies aim to reduce complications but insufficiently address the lack of maturation. The artificial placenta (AP) replaces the placenta with an oxygenator connected to the umbilical cord, while keeping the fetus in an artificial fluid environment. Fetal physiology is maintained, and thus maturation continues. Using pigs, we developed the closest-to-human large animal model to date that mimics human fetuses 23-25w gestation, the preterm babies at highest risk of poor outcome. We have shown that heart failure impedes support in small fetuses, significantly limiting clinical translation. This has also been reported by other groups working with more robust sheep models. With technical modifications and the inclusion of a centrifugal pump, we have now achieved support of fetuses as small as 490g for >1 week - a major milestone towards clinical application. Despite improved hemodynamics, however, we have noted a gradual decrease in AP blood flow over time that limits length of support. We attribute this to a combination of high afterload, sympathetic activation, and characteristics of the device. Our herein proposed research aims for a detailed understanding of extrauterine fetal physiology during extended AP runs, fetal management strategies, and effects on fetal maturation. We will (1) track hemodynamics of the preterm pig fetus in utero, during, and after transition to AP with continuous flow and pressure measurements in various compartments of fetus and circuit, blood gas analyses, hormones, and imaging; (2) modify circuit characteristics and fetal management to achieve near-physiologic parameters; (3) perform postmortem analyses of lung, heart, brain, and other organs to assess fetal maturation. With the substantial progress we have achieved in the support of extremely small fetuses, we are ideally positioned to spearhead the development of a clinically applicable AP system. Our interdisciplinary team consists of leading experts in cardiovascular and intensive care medicine, fetal and neonatal care, basic science, pharmacology, fluid dynamics and engineering. The results of this proposal will pave the way to an entirely new clinical field: fetal neonatology.

The objective of our proposal is to develop a high risk/high reward technology to assess degenerative diseases of the brain and eye. Our research approach will be undertaken by an interdisciplinary group of bioengineers, geneticists, vision- and neuro-scientists to develop novel, advanced biomedical imaging for in vivo assessment of cellular changes in brain and eye degenerations for clinical translation.

During development, the retina and brain derive from the same embryological tissues and display molecular, cellular and anatomical similarities. As the retina is readily imaged via the pupillary axis, while the bony skull prohibits non-invasive imaging of the brain, we will use the retina to assess neurodegenerative changes in eye and brain.

We will combine our formidable resources and expertise to develop a transformative technology that will uncover unique retinal "signatures" that correlate with neuronal, glial and chemical changes in the brain and eye using mouse models. The novelty of our approach is to exploit these retinal "signatures" to develop innovative imaging algorithms to track in vivo changes, ultimately in patients, to assess the progression of debilitating neurodegenerative diseases of the brain and eye.

Our aims are:

1) Implementation of Combined Adaptive-optics Two-photon microscopy and Polarization-diversity optical coherence microscopy (CATP) for in vivo subcellular and functional small animal retinal imaging. CATP retinal microscopy, comprising a 10-fs Ti-Sapphire laser and polarization diversity detection with Sensorless Adaptive Optics (SAO)-based wavefront optimization module, is capable of providing molecular and cellular information in microscopic retinal tissue regions.

2) Development of cross-platform 3D registration algorithms and adaptive kernel based molecular contrast formation algorithms. These algorithms will reconstruct digitally "stained" 3D volumetric retinal structure with functional and molecular specific contrasts at a subcellular resolution.

The significance: Our project will provide next-generation biomedical technology for in vivo eye imaging to facilitate the understanding of retinal diseases and neurodegenerative disorders in central nervous system. Our results will shed light on the detailed cellular mechanisms associated with the development of age-related neurodegenerative diseases of the brain (Alzheimer's, Parkinson's, Huntington's) and eye (AMD, glaucoma, diabetic retinopathy).

Our project will link experts in public health modelling, data management, citizen science, community engagement, participatory research, and climate justice who are based in South Africa, Brazil, and Canada, with the shared goal of learning from the COVID-19 pandemic to build stronger and more resilient governance strategies and increase preparedness to face future challenges equitably. By sharing our research processes, results and conclusions as well as our interdisciplinary perspectives, we hope to build an emergent framework for addressing global-scale socio-ecological challenges which invariably impact the marginalized first and hardest. We are excited to have the opportunity to `learn by doing' in this way.

The main goal of this project is to demonstrate WHAT the pandemic has shown regarding governance failures to protect the most vulnerable; WHY the participation of marginalized community members is vital to build effective climate and pandemic protection for all; WHICH data is most relevant for community-level actions and for improved governance; and HOW data collection, management, and dissemination, with community engagement and collaboration, can be successfully undertaken in various contexts (e.g. rural, urban, health, agriculture, coastal, gender, etc.)

We will do this by pursuing four Project Objectives:

A. Build a dialogic space for formalized institutions and structures to actively engage and interact with community stakeholders and equity-seeking informal networks;

B. Co-develop theoretical and operational frameworks that identify and address the systemic risks of pandemics and climate threats;

C. Co-create technological platforms for systemic risk assessment and management;

Collaboratively apply and iterate learning from the theoretical framework, technology platforms, and participatory initiatives.

The Transformational Outcomes of the project will include novel theories, policies and operational tools and practices in pandemic and climate management and response. Together, these transformational outcomes will adopt intersectional approaches to vulnerability reduction and resilience building that is equitable, and takes into consideration the complex, and contextual realities that shape the everyday existence of those who face the highest level of risk. Our novel outcomes will also build mutual support across formalized institutions and community (in)formal networks.

Mutations in histone genes are found in most cancers, but how they contribute to the oncogenic process remains largely unexplored. Several challenges preclude our understanding of the roles of histone mutations in cancer. First, specific functions of histones in many epigenetic signalling pathways are still enigmatic and critical histone residues are ambiguously defined. Second, the mutational landscape of histones in cancer is large, including thousands of mutations, which prevents their systematic analysis. A handful of histone mutations have been studied and shown to drive tumorigenesis, emphasizing the need for new approaches to identify oncogenic histone mutations and to understand their molecular effects.

Many DNA-templated processes are regulated at the level of chromatin. Histones represent the crucial component of chromatin, they are highly conserved across species and are encoded by multiple gene copies. Interestingly, most cancer-associated histone mutations affect a single gene copy, indicating that they exert dominant oncogenic effects despite ample levels of wild type proteins.

We hypothesize that cancer-associated histone mutations drive oncogenesis through dominant effects. To test this, we will focus on the impacts of histone mutations on histone posttranslational modification sites and protein-protein interactions, some of which have been previously shown to be disrupted in cancer. More specifically, we will leverage the genetic simplicity of the yeast model system and pair it with advances in mass spectrometry as well as computational methods of molecular modeling, molecular dynamics simulations and machine learning. Our final goal is to develop an integrative platform that examines and predicts the effects of histone mutations and their driver potential in cancer.

We bring together expertise in genetics, oncology, mass spectrometry, computer science, and biophysics. Our proposal is risky because gain-of-function/dominant mutations are rare, difficult to study and interpret. Even though there is some support for dominant effects for histone mutations, this may be the exception rather than the rule. Our study has the potential to drive a paradigm shift on the critical mechanistic roles of cancer-associated histone mutations, providing a framework for their prioritization, and illuminating their utility as diagnostic biomarkers or targets for therapeutic intervention.

Research Objectives:

Here, a semiconductor and helium physicist expert in classical and quantum flow measurements, an electrical engineer expert in high-frequency signals, and a nanobiophysicist expert with nanopore fabrication will team up to create a sonic black hole, the fluidic analogue of the cosmological black holes found in the Universe.

Summary of the Approach:

Black holes are ubiquitous in the Universe, and despite their great interest for cosmological scenarios and the fate of stars (or for the fate of the Universe as a whole) they remain vastly mysterious objects. This is in large part because by definition black holes cannot be seen directly, nor probed by experiments. Moreover, the celebrated `black hole evaporation' predicted by Hawking in 1974 has never been confirmed by observation. Despite these drawbacks, there is still hope to study physics that is analogous to black holes albeit in laboratory setting. Here, we propose to study the physics of high-velocity fluid flow (close to, or at Mach number one) for which Canadian physicist Unruh showed that a "metric" exist with a mathematical similar to those of black holes. With the same reasoning used by Hawking in his seminal prediction of black hole evaporation, Unruh argued that these "sonic black holes" should also evaporate and lead to radiative emission of phonons, or sound. Motivated by the great importance of detecting and understanding the physics of black holes, our team will create sonic black holes formed by the passage of high-velocity gas flow in nanoscale nozzles fabricated in semiconducting membranes, and study them by way of direct flow, noise, and particle sensing experiments.

Objectives: To investigate whether non-invasive stimulation of preserved neuronal brain networks using optimal, individually-tailored stimulation parameters could facilitate brain reconnection and recovery of consciousness in patients presenting with disorders of consciousness (DoC).

Research Approach: Optimal interventions seeking to promote recovery of consciousness have yet to be established. The heterogeneous nature of acquired brain injuries in terms of injury mechanisms and lesion characteristics suggests that intervention success is more likely to be achieved with an individually-tailored approach.

Advanced neuroimaging and electrophysiological techniques have revealed new insights into biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive. Non-invasive brain stimulation techniques (NIBS) allows the modulation of brain networks dynamics which was shown to be a promising avenue in modifying states of consciousness. Among NIBS, transcranial alternating current stimulation (tACS) is an easy-to-use, inexpensive tool that offers the unique possibility to effectively and durably (especially in multisession protocols conducted over consecutive days) modulate endogenous brain oscillations within a specified frequency range. Among natural brain frequencies, the alpha (8-12Hz) frequency range has been the target of most tACS protocols given its central involvement in conscious/cognitive processes as well as its mediating role on long-range brain network connectivity. While other NIBS technologies have been used in DoC patients with variable success, there is no study to our knowledge that conducted a multi-session alpha tACS stimulation protocol to longitudinally study induced effects on brain network connectivity and consciousness states acutely following sedation weaning. Our approach will also innovate by using advanced brain connectivity modelling based on functional magnetic resonance imaging and electroencephalography to tailor optimal stimulation parameters according to each patient's brain injury characteristics.

Anticipated outcome: By non-invasively stimulating the acutely injured brain via an individually tailored modelling approach based on preserved brain networks, this intersectoral project has the potential to facilitate reconnection of idling neurons and to expedite emergence into consciousness in severely brain injured patients.

Designing with biomaterials offers an opportunity to address critical challenges in the built environment, maybe the most relevant being climate change. On this regard, bio-based materials can help reduce the need for extraction and transformation of traditional materials. Certain biomaterials can optimize hygro-thermal performance of standard wall assemblies for northern climates, they can be produced at room temperature, with lower energetic and financial costs and using agricultural and industrial waste. Consequently, designing with biomaterials supports circular economies, reduces construction waste and overall energy use, and can improve access to affordable housing.

Another challenge specific to northern and isolated communities in Canada is their high dependence on shipment of construction materials from remote areas. This is due, in part, to a disconnection between design solutions and local resources availability. Materials used in northern projects have not been necessarily designed for northern specific climatic conditions and this generates premature failures and costly maintenance. Locally developed and harvested biomaterials will reduce the need for expensive shipments and lower the use of non-renewable resources while increasing these communities' resilience in the face of drastic environmental changes.

Therefore, this research project proposes to: (1) explore and re-design a series of bio-based materials to adapt and optimize their morphological, hygro-thermal and physical properties for the North; (2) analyse qualitative and quantitative impacts of biomaterials in the race towards climate change adaptation and mitigation; 3) create a set of guidelines to ensure knowledge transfer to local communities and next implementations steps.

Outcomes of this research will have direct and/or indirect effects on peoples' health, building science innovation, housing affordability, and social equity. This research will advance current knowledge on the fields of biomimetic design and biomaterials. Biomimetic design represents a paradigm change from traditional architectural design and practice, and defies conventional theories on sustainable architecture. On this regard, biomimetic design provides a novel pathway towards technological innovation, offers a profound and radical change in design thinking processes and novel opportunities to address climate change.

Multiple sclerosis (MS) is a leading cause of disability in young adult Canadians. MS is a chronic inflammatory neurological disease where the immune system attacks the insulating myelin sheath of nerve fibres, a process known as demyelination. Causes of MS remain unknown; new therapies are in high demand since current treatments benefit only certain types of MS with variable effectiveness.

The toxin cuprizone, frequently used in model studies to induce demyelination, shares several similarities with MS in its action. If cuprizone is removed, spontaneous remyelination and recovery allow studies of the remitting process. Following prolonged cuprizone treatment, inadequate remyelination after cuprizone removal emulates the incomplete remyelination of some progressive MS forms. Cuprizone-induced demyelination is thought to involve essential metals such as iron, copper or zinc, but molecular-level details remain unknown in part due to scarcity of specific probes. How abnormal brain metal distribution, reported in MS, links to disease and might be exploited as a target for treatment also is unclear.

OBJECTIVES: 1) Develop super-resolution X-ray fluorescence imaging (XFI) and 2) apply this to determine the role of metals in cuprizone-based demyelination and remyelination.

APPROACH: Our team will use physical science methods in developing super-resolution XFI to probe metal distribution in the cuprizone model on whole organism to subcellular scales. We will use both acute and chronic cuprizone models as a unified tool to study metal changes in different pathological stages, correlating metal measurements with histological, biochemical and behavioral analyses. Finally, we will apply our approach to tissues from MS patients obtained at autopsy and/or biopsy.

NOVELTY AND SIGNIFICANCE: Reports of cuprizone as an MS model number in the thousands, but only a handful focus on metals. Our work takes a bold new approach, against established norms for health research. Through our new developments in super-resolution XFI we will generate a fundamental understanding of the role of metals in cuprizone-based demyelination and remyelination. Our research has potential to identify novel targets for MS therapies, both preventive (prevent demyelination) and reparative (promote remyelination), which may translate to the clinic. Our super-resolution XFI methodology has potential to transform microscopic measurements of metals from environment to human health.

Antibiotics are used to treat bacterial infections. As such, they support the current historical peak in the lifespan and the healthspan of humans. Thus, the rise of antibiotic resistance poses a serious threat to public health. One of the keys to flattening the occurrence of resistant microbes is to reduce the use of antibiotics including through their replacement with other classes of antimicrobials. Antimicrobial peptides (AMPs) are expressed in all kingdoms of life, thus representing one of the most promising alternatives to antibiotics. Nonetheless, technologies to develop novel AMPs with desirable properties are lacking because of limitations that can be best addressed through an unprecedented approach combining synthetic biology (SB), data mining and machine learning (ML). Based on the provocative hypothesis that gram-negative bacteria are suitable AMP-expressing hosts, we will develop the AntiMicrobial Peptides SECretion (AMPSEC) platform. We will use a SB approach to express AMPs as releasable cargos on the surface of gram-negative Escherichia coli. The secretion of AMPs will allow their purification from the growth medium or their direct action against selected gram-positive bacteria. These include Staphylococcus aureus, Enterococcus faecium and Streptococcus pneumoniae, which are among the 12 bacteria for which new antibiotics are urgently needed according to the World Health Organization. To facilitate the design of peptide libraries against these targets, we will identify the most promising scaffolds using bioinformatics to mine AMPs found in curated databases. The latter will be further analyzed using ML to rank AMPs according to their gram-positive over gram-negative activity ratio. This disruptive interdisciplinary approach will be a game changer. Indeed, it will enable the smart design of libraries and their streamlined screening to evolve potent AMPs against specific bacteria. Although the current proposal is aimed at gram-positive bacteria, the tools and expertise described herein will facilitate the development of equivalent approaches targeting gram-negative bacteria. Our overarching goal is to identify novel AMPs that will have an impact in the real world. We anticipate that this will lead to the implementation of alternatives to antibiotics, thereby contributing to curbing the rise of antibiotic resistance. Due to the widespread use of antibiotics, applications may range from medicine to the agri-food and biotechnology sectors.

The brains of vertebrates and insects possess a complex network of neuronal circuits that keep track of orientation in the environment, thus enabling navigation. However, how this system learns the visual surroundings and transforms this information into an internal representation of space remain elusive. In mammals, the retrosplenial cortex (RSC) plays a crucial role for long-term memories of environmental contexts and for spatial orientation. In this project, we hypothesize that these two aspects of spatial learning result from the same process whereby the RSC learns the correspondence between place-specific viewpoint and internal sense of direction, resulting in a representation of the context. We further make the hypothesis that sleep is instrumental in training the network. It has recently been suggested that artificial networks that receive the same inputs as the RSC (vision, position, and direction) can learn to orient an agent from a limited number of visited viewpoints. The goal of this proposal is to unravel, both at the experimental and theoretical levels, the neural basis of spatial learning underlying these cognitive abilities.

In a series of experiments in freely moving mice, we will monitor the activity of RSC neuronal ensembles with calcium imaging and multichannel electrophysiology. We will test the prediction that RSC neuronal population code for viewpoints in a context-specific manner. We will further test that, during sleep, the RSC learns to generalize all possible viewpoints from a limited experience. Finally, we will work on a biologically-plausible machine learning models that uses predictions of sensory stimuli based on spatial location to orient an artificial agent.

This project will entail the collaboration between experimentalists with an expertise in monitoring brain activity at the neuronal level in behaving animals, and theoreticians whose research program aims to understand the basis of learning in the brain. This project will establish a fruitful and interdisciplinary dialog, as the experiments will directly test theoretical predictions and, in turn, will inspire new theoretical developments. This study is high-risk, high-reward as it will use a combination of cutting-edge technologies to test state-of-the-art work in machine learning and artificial intelligence, and will shed lights on the neuronal networks allowing animals to navigate their environment, one of the most fundamental cognitive abilities.

The chemical industry synthesizes nearly all the products we use to live; however, most products end up in the atmosphere as the greenhouse gas carbon dioxide (CO2), or as plastic waste in landfills or water. The chemical industry relies mostly on limited fossil resources, and is responsible for 10% of global energy consumption and 7% of global GHG emissions. The International Energy Agency aims to reduce energy related CO2 emissions by 50% in 2050 compared to 2009. Meeting this target requires innovative, transdisciplinary solutions.

Bioprocesses use living cells to convert renewable, non-food biomass and waste into chemicals. Carbon neutral fuels and chemicals can be produced from CO2, water, and sunlight directly using photosynthesis. However, these processes are slower than traditional chemistry due to inefficient light absorption and conversion in photosynthesis.

In this project, we will explore the concept of powering bioprocesses directly by renewable electricity such as wind and solar. We will develop electro-bio hybrid systems integrating electrochemical and biological processes that efficiently produce biodegradable polymers, such as poly-hyroxybutyrate, from CO2, water and renewable electricity.

To achieve these goals, we have brought together a team with expertise from three scientific fields that do not often interact: electrochemical engineering, computational system biology, and microbiology. We will develop electrodes for CO2 reduction to multi-carbon oxygenates - the substances that can serve as both energy and carbon sources for microbial growth. We will engineer the genetics of the microbes and computationally optimize the system to convert these oxygenates to biodegradable polymers. 

This project will generate new knowledge in microbial energetics and electrochemistry, leading to an efficient electro-bio platform for renewable chemical synthesis. This platform has strong potential environmental benefits by reducing energy consumption and green house gas emission, and enabling cost-effective, large-scale production of biodegradable bioplastics to reduce plastic waste.

Lack of seizure control in epilepsy surgery candidates is due to poor localization of surgical targets, as similar spatio-temporal dynamics are seen during the ictal and interictal phases of SEEG recordings, and the degree of these similarities and distinctions are still not well understood by clinicians. Using computational modeling, we propose a comprehensive interpretation of SEEG results that will dramatically improve our understanding of epileptic networks by more accurately predicting the localization of surgical targets and ultimately improving surgical outcomes.

The extensive interpretation of SEEG data using signal analysis would not be possible without the expertise of our multi-disciplinary team. Our collaborative team with expertise in the fields of neuroscience, physiology and pharmacology, mathematics, and engineering, is developing an innovative methodology entitled the Western Assessment of Individualized Networks in Epilepsy (WAINE). The goal of WAINE is to improve our understanding of neurophysiological changes in the epileptic network and to help localize the area that should be resected to improve the seizure outcome after epilepsy surgery (Epileptogenic Zone or EZ).

The main objectives are:

1. Identify interictal epileptiform discharges (in between seizures) and ictal patterns (during seizures) in SEEG recordings and differentiate them from physiological transients using novel computational methods and a learning virtual reality task.

2. Map and localize interictal transients and ictal patterns onto anatomical images of individual patients' brains to create models of epileptic networks and their spatiotemporal dynamics, creating a `computational epileptic intervention zone' (Computational EIZ).

3. Integrate the models obtained in objective 2 (`computational EIZ') with clinical data from the current standard of care surgical approaches (including an area of resection and outcome after surgery) to develop the `clinical epileptic intervention zone' (Clinical EIZ), and then generate probabilistic analysis targets for surgical intervention in an individualized manner to increase the chances of becoming seizure-free after epilepsy surgery.ç

Findings will result in better spatiotemporal network modeling of abnormal brain activity in patients with medically resistant epilepsy, which will improve the efficacy of surgical interventions, reduce the direct and indirect costs associated with epilepsy, and improve the quality of life.

The apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC) family cytidine deaminase enzymes mediate anti-virus roles in mammals by mutating viral genomes in infected cells. APOBECs mutate C to U in single-stranded DNA (ssDNA) in unique signature "hotspot" sequence targets. The viral restriction roles of APOBECs are well established through many studies on retroviruses, most notably HIV which replicates via an ssDNA phase. On the other hand, we and others showed that viruses can flip the coin and benefit from APOBEC action by having enriched their genomic sequences for APOBEC hotspots in positions where APOBEC-directed mutagenesis generates immune-escape or drug-escape variants.

Bats have wide geographic ranges and it is becoming increasingly appreciated that they have an unusually high tolerance of viruses that have underpinned zoonotic disease outbreaks. Three emerging observations form the basis for this proposal: (1) APOBEC genes are under strong evolutionary pressure due to their anti-viral roles, particularly the APOBEC3 subfamily which has expanded from 1-2 enzymes in all mammals to 7 in primates. At least some bat species appear to have evolved a remarkably high number of APOBEC enzymes, almost three times as many as in primates, (2) studies of APOBECs in human cancers are highly suggestive that several members of the APOBEC family may have the ability to mutate RNA in addition to ssDNA, and (3) new studies of SARS-CoV-2, an RNA virus, implicate APOBECs as a source of viral mutagenesis. Therefore, we hypothesize that bat APOBECs have evolved unique anti-viral roles which contributes to the ability of bats to tolerate high viral loads, and further, that this is reflected in a co-evolutionary scenario of common bat virus genomes, including RNA viruses.

We will establish a unique multi-disciplinary approach that combines computational genomics, structural biology and biochemistry, and ecology and genomics, to characterize APOBEC enzymes and their evolution across several bat species that harbour viruses with zoonotic potential. Using wet-lab experimental results, we will build deep learning-based models to predict mutability in viruses of bat origin and use these to predict the potential variation of bat viruses in humans following a hypothetical zoonotic transmission. This will be the first functional study of a key facet of the bat immune system which plays a pivotal role in virus evolution and transmissibility to humans. 

Our ability to digitally connect people online has fundamentally changed the nature of everyday social life. As millions world-wide struggle with the effects of social isolation from COVID-induced lock-downs-accompanied by a drastic rise in rates of substance abuse, anxiety and depression-this digital connectedness has never seemed more vital. Our project tackles a key question of our time: How effective is `online' social connectedness in protecting us from causal somatic effects of social isolation?

Experimentally, this question is challenging to answer in humans. From an ethical standpoint, socially isolating humans in a controlled setting-a prerequisite for studying if and how `online' social connections may protect us from the effects of isolation-is rarely possible. From a practical standpoint, data collection in humans is often limited to non-invasive measures and only a few time points, leading to an incomplete picture of neurobiological changes and their time-scale. From a privacy standpoint, experimenters have limited monitoring of their human subjects outside of the lab (e.g., their social media use, sleep patterns), introducing `unseen' variables that obscures our understanding of the effects of digital technology on neurobiology.

To overcome these challenges, we will use a colony of non-human primates (NHPs)-our closest evolutionary relatives-to address two interrelated research aims:

Aim 1: Understand the multifaceted neurobiological changes that occur as NHPs transition from rich social environments (group living) to living in isolation or smaller groups.

Aim 2: Test whether and how virtual interactions with conspecifics (face-to-face video chat) can attenuate the physical effects of isolation.

Using our world-class NHP facility, we will manipulate NHP social experience (Aims 1 & 2) and longitudinally track changes in numerous biomarkers (including brain structure/function, hormones, inflammatory markers, gut microbiome) and behavior (24/7 video tracking). This will require an interdisciplinary approach, combining tools of media & communications, biology, psychology, neuroscience, and computer science.

Our approach will transform our understanding of the short- and long-term somatic effects of COVID-induced isolation and will have implications for digital technology applications (e.g. remote education, telemedicine) and social policy (e.g. concerning vulnerable populations with limited access to digital resources).

Intimate partner violence (IPV) is a serious societal and medical issue that has severe impacts on the lives of Canadian women. Of the many challenges faced by IPV survivors, brain injury and post-traumatic stress disorder as a result of the physical attacks are two of the most significant.

Despite initial studies that suggest there is evidence of brain injury and PTSD in the vast majority of IPV survivors, how it contributes to their lived experience, and how outcomes can be improved, remains remarkably understudied. The brain injury that occurs in IPV is unique because in IPV there is typically a combination of both mild TBI (mTBI; i.e., concussion) and non-fatal strangulation (i.e., a hypoxic/ischemic insult). Thus findings from sports and military related mTBI cannot be generalised to this setting. It is also known that there is a strong association between brain injury and PTSD; however whether this relationship is causal in the context of IPV, and whether there are reliable clinical methods to improve outcomes, remains unknown.

Advanced blood biomarkers and neuropsychological assessment are clinically applicable methods that are sensitive to the brain injury and PTSD, and can be applied to bridge the major knowledge gaps pertaining to these conditions in the IPV context. There is also promising initial evidence pertaining to the use of psilocybin, a naturally occurring substance produced by fungi, in the treatment of brain injury and PTSD in other contexts. However, it is important to acknowledge that the many confounding variables in IPV populations make it difficult to adequately investigate biomarkers and treatments of brain injury and PTSD purely in patients. Therefore, we have also developed the first rodent model of IPV to provide translational insight into these questions.

Now our balanced and complementary research team consisting of brain injury, PTSD, IPV, blood biomarker, neuropsychology, and knowledge translation experts, along with community and knowledge user partners, propose a high risk but feasible translational project that aims to provide a foundational understanding of biomarkers and treatments for brain injury and PTSD in IPV. Aim 1 will apply our novel animal model of IPV to investigate biomarkers and the efficacy of psilocybin, as well as the underlying neurological mechanisms. Aim 2 will involve a parallel pilot study that will to validate the biomarkers and treatment in human patients. 

Fruit d'une collaboration interuniversitaire et collégiale de chercheurs en science forensique, en criminologie, et en santé, ce projet ambitieux est dédié à la compréhension et à l'amélioration de l'action de sécurité dans l'investigation des incendies. Unique au monde, son objet d'intérêt est la trace incendiaire (physique, chimique, biologique, et numérique) comme élément initiateur et fédérateur à l'échange de données et à la collaboration des différents acteurs de la santé et sécurité publique.

Le fond EXPLORATION permettra l'activation de cette recherche pluridisciplinaire, jusqu'alors inexistante au Canada, en finançant un premier projet pilote associant sciences naturelles, sciences sociales, santé publique, ainsi que les premiers intervenants en matière de sécurité civile. Appliqué aux incendies, ce projet abordera des questions fondamentales de la prévention et de l'investigation sous l'angle de la santé publique (protection des intervenants, toxicologie), de la criminologie (modes opératoires et influence des facteurs contextuels et spatio-temporels), ainsi que le rôle et l'utilisation proactive de la trace dans l'investigation criminelle (analyse des débris, renseignement, et analyse criminelle). Ce rassemblement de chercheurs de cultures scientifiques variées permettra de mieux comprendre les synergies, les rationalités, et les approches de la très large communauté de protagonistes (pompiers, préventionnistes, policiers, enquêteurs, techniciens de scène de crime, criminologues, psychologues, experts en sinistres, .) afin de proposer une architecture idéale de l'action de sécurité au sein de laquelle ces domaines normalement cloisonnés peuvent coexister et collaborer de manière logique, participant à l'élaboration de nouvelles connaissances en matière d'incendie.

Les retombées de ce financement ne se limiteront toutefois pas seulement au domaine de la sécurité en matière d'incendies. Cette recherche vise en effet à rompre le paradigme nord-américain actuel qui voit l'utilisation de la trace comme seul élément probatoire, pour la replacer dans un contexte proactif qui contribue à orienter la gestion et les décisions de prévention et d'investigation. Le cadre de réflexion proposé se veut applicable à toutes les traces indiciaires et permettra d'identifier le Canada comme le chef de file de cette perception novatrice de la trace en Amérique du Nord.

The human hearing system can perform complex tasks like filtering, normalization, sound source localization and separation. However, there are also fundamental limitations to our auditory perception. For instance, people have trouble determining whether a sound originates from the back or front without moving their heads in spatial sound localization, and human auditory range is typically limited to between 20Hz and 20KHz. To make matters worse, as people age, their high-frequency sensitivity, the ability to understand conversations in noisy environments and to localize sounds degrade over time. Existing hearing aid solutions target people with hearing impairments and rely on costly dedicated hardware and lengthy calibration processes administered by specialists. By harnessing the ever-increasing processing power of mobile devices and the advancement of machine learning, we aim to develop a novel virtual & augmented acoustic reality (VAAR) framework that delivers customizable and personalized auditory experiences on commodity devices. VAAR puts users in control of manipulating binaural sounds to not only mitigate hearing losses but also expand the limits of their auditory perception in general.

Toward this overarching goal, the specific thrusts of the research program include, i) self-administered audiometric and head-related-transfer-function measurements on commodity devices, ii) binaural 3D sound localization and spatialization, iii) development of a multifunctional research platform for binaural VAAR, and iv) auditory-attention guided spatial filtering and selective amplification. Working closely with audio engineers, our team of researchers with recognized and diverse expertise in mobile computing, machine learning, signal processing, auditory neural science and experimental psychology, will take an interdisciplinary approach by integrating human factors in engineering design. For user study and experimental validation, we will utilize advanced psychoacoustic testing facilities including an acoustically treated sound booth and a variable acoustic lab built to NC10 standards. The research is novel in that it enables continual learning and adaptation of acoustic profiles based on user inputs and contexts. It will generate significant economic and social impacts in the entertainment and healthcare industries through the development of VAAR technologies that are accessible to all people, regardless of age, disability or socio-economical status.

Multicellular beings are composed of populations of specialized cells that share the same genetic blueprint yet differ in their physiology and function. Each cell presents a characteristic signature of gene expression that is a result of normal development, differentiation and its environment that can be measured using RNA sequencing. The recent advent of methods for single cell sequencing (scSeq) has greatly improved our understanding of tissue composition and disease aetiology, whilst facilitating the identification of new cell types. Despite these outcomes, scSeq methods present significant restrictions beyond the need for technical specialists and expensive equipment. These include the static and uniform sampling of cellular populations, the analytical limitations inherent to different sequencing platforms and the substantial cost of commercial consumables, among others. This project seeks to spawn the next generation of scSeq technologies by harmonizing our expertise in micro-fluidics, bespoke molecular barcoding, nanopore sequencing and artificial intelligence. Specifically, we will (i) design molecular barcodes for nanopore sequencing that are optimized for real-time signal processing and classification; (ii) adapt recently developed open-source micro-fluidics protocols for high-throughput droplet-based cellular encapsulation to our custom barcoding strategy; (iii) develop rapid unsupervised clustering algorithms premised on the classification of raw electric signals; (iv) implement a real-time iterative gene expression classification algorithm to assign single-cell barcodes with cell types; and (v) leverage adaptive sampling to selectively enrich molecules during nanopore sequencing based on their barcode and predicted cell-type. This work will pioneer the use of adaptive sequencing in single-cells, allowing researchers to `zoom' into specific cells, such as immune or cancer cells, without prior experimental enrichment, known to introduce artifacts. We will also measure gene expression in real-time, reducing turnaround times and enabling new diagnostic applications. Moreover, custom barcoding will increase the efficiency of nanopore sequencing and improve the precision of scSeq. Finally, the use of open-source protocols and portable, accessible sequencers can reduce the associated costs by an order of magnitude, which will facilitate decentralized usage and facilitate uptake in smaller labs and lower income communities.

Indigenous peoples have constructed different types of structures for various purposes for thousands of years. However, in recent history, the design and the research related to building design has been governed by colonial ways of knowing. Even current structures designed by Indigenous artists and architects are still confined by existing prescriptive design codes (i.e. building codes) to qualify the structure as safe. Recently, Indigenous architects are voicing the need to design spaces to be inclusive of Indigenous people, but this endeavour is not without challenges. In a recent interview, Indigenous architect Wanda Dalla Costa described Canadian architects as being "... so constricted and strapped by colonial processes-whether it is in the budgets, hierarchies, methodologies, or lack of Indigenous concepts (ways of being, connecting, and doing)." This raises the question: "What kind of innovative and inclusive structures could be developed if designers, engineers, and architects re-integrated Indigenous ways of knowing to research building design?"

This project seeks to develop a methodology that integrates Indigenous ways of knowing as a fundamental underlying principle to develop new technologies for building systems. This goal will be accomplished through the following objectives:

-Explore new architectural systems that are designed using Indigenous concepts through conversations and collaborations with members of Indigenous communities, which are not constrained by existing building codes or regulations

-Investigate the ability to fabricate novel structural elements designed with Indigenous concepts using additive manufacturing and high strength materials (e.g. metals & alloys)

-Evaluate the structural integrity and safety of additively manufactured components and elements integrated in structural systems

There are significant challenges associated with decolonising our research methods, assumptions, and implementation of structural systems. Nevertheless, the project has the potential for significant impact in several domains. The project will develop new knowledge materials science, manufacturing, and structural analysis. Moreover, by starting a dialogue around integrating Indigenous design concepts rather than advocating for a single specific design, the research outcomes of this project have the potential to have a social and cultural impact for both settlers and hundreds of Indigenous communities across Canada.

The world's population is growing and demand for food is outpacing production, resulting in a significant food security challenge on a global scale. Agriculture is thus in need of new technologies that (1) increase the rate of production of novel crop varieties; (2) enable the immediate and faithful propagation of desired crop traits; and (3) provide incentives to farmers and industry to work together as innovators for crop breeding. These 3 criteria are fulfilled by apomixis, a naturally occurring form of asexual seed production in plants which presents a key technology for crop variety improvement. An apomictic mother plant produces seeds with embryos that are genetic clones of herself through several modifications of the sexual reproductive pathway. The introduction of apomixis into crop plants would enable the permanent fixation of any heterozygous genotype in a single generation, thereby enabling breeding programs to access complex phenotypic traits which are presently impossible to fix using traditional methods. The impact on breeding programs would be enormous, as the fixation of traits demonstrating heterosis in a single generation would permit the rapid development of superior crop varieties adapted to changing environmental conditions, diverse farming niches and systems, and evolving markets. We have made several important new discoveries (e.g. apomixis-specific gene variation) and tools (intergeneric crosses between apomictic and sexual plants) in the apomictic plant genus Boechera (a wild Brassicaceae). Together with industry and producers, these tools are being used to induce the expression of one or all the components of apomixis in Canola. Our current research has demonstrated that apomixis is expressed by multiple factors related to its components apomeiosis, parthenogenesis, and pseudogamy. These factors must be simultaneously introduced into the host plant, and here we request funding to engineer a supernumerary chromosome of endogenous or artificial origin (i.e. mini-chromosomes) which will be used to selectively induce apomixis in Canola, and other Brassica crops. Mini-chromosomes typically remain separate from the host chromosomes, and allow the integration of many genes simultaneously without risking random sites effects. Furthermore, mini-chromosomes are transmissible to the next generation through meiosis and stable during mitotic and meiotic divisions in the absence of selection.