Projets novateurs réalisés

Development of an Extensible Framework for Assessing Digital Health Innovation Hubs (DHI-HUB)

New information technologies are becoming an important part of the health care system. A priority both provincially and nationally is the establishment of an enhanced network of general practitioners using the latest information technologies to acquire, store and use patient information. This will involve deployment of person-centred digitally-enabled information technologies in a new structure known as Digital Health Innovation HUBs (DHI-HUBs). The hubs will provide an opportunity to test innovative health technologies in health care. In this project, we will develop a framework for evaluating the effectiveness and outcomes of DHI-HUBs. The research methods will include ideas from implementation science, health IT project management and the emerging field of health informatics. The approach to evaluation of an implementation of a set of innovative health technologies will be applied in the Okanagan region of Canada and will be designed to be generalizable to other health regions.

Caractérisation en bioréacteur de la dose efficace d’un nouveau probiotique destiné au porc pour limiter la colonisation par Salmonella et la dysbiose intestinale

Au Canada, l’industrie porcine représente une part importante de l’économie reliée à l’agriculture. Pour rester compétitive, elle doit améliorer sa rentabilité tout en conservant de hauts standards de salubrité. Pour ce faire, l’utilisation de probiotique pourrait limiter la contamination des porcs par la salmonelle, important pathogène alimentaire, tout en atténuant les troubles digestifs des cochons. Dans ce projet, un nouveau probiotique sera mis au point. Classiquement, les probiotiques sont rapidement testés sur des animaux. Pour limiter les coûts en termes de vies animales et économiques reliés à cette pratique, le présent projet de recherche utilisera un bioréacteur pour simuler l’environnement intestinal du porc afin de finement dessiner le nouveau probiotique qui aura pour vocation d’inhiber Salmonella et d’agir positivement sur les bactéries de l’intestin du porc. Ces résultats perm

Studies on uptake and translocation of patented active ingredients in plants

The Suncor/McMaster partnership is generating a pipeline of novel, green, agricultural chemicals to be applied as crop sprays. One of the challenges with treating plants by spraying leaves (foliar treatment) is targeting the transport of the active ingredients (AI) to specific parts of the plant. An example is preventing bacterial growth in the xylem, channels that carry water from the roots up the plant. The transport of AI on leaf surfaces to the xylem is difficult and possibly impossible in some plants.
The new McMaster/Suncor researcher will be developing methods to measure transport into plant tissues, including the xylem fibers and phloem tissues, and to enhance this transport by additives in the crop spray formulation.

Examining the effects of Neuropeptide Y5 receptor antagonsim onprimary tumor growth in murine model of breast cancer

Our laboratory has recently provided evidence that NPY is also involved in the progression of breast cancer. We have

demonstrated that breast cancer tumors have sympathetic nerves, NPY and NPY receptors. Also, we

have shown in cell culture studies, that when NPY binds to the Y5 receptor on breast cancer cells,

those cells will divide at a greater rate. Therefore, in the proposed project we will test whether treating

tumor bearing mice with a specific Y5 receptor blocker will slow tumor growth. Tumor bearing mice will be treated daily with a Y5 receptor blocker provided by Triphase Accelarator. Tumor growth will be monitored during a two month period.

Innovating Corrosion Measurement for Your Vehicle

From 2014-2018, Krown Corporation, a pioneer in corrosion treatment, partnered with University of Windsor Faculty of Engineering researchers to conduct a comprehensive assessment on how to measure and assess the degree of corrosion on a vehicle, so that it may be communicated to the vehicle owner. This preliminary research demonstrated that a corrosion metric, and the method developed to measure corrosion, show excellent promise to assess and communicate the impacts of corrosion and further research is critical to refining the metric so that it can be applied intelligently on a broad scale yet be usable and understandable to both users of the metric and consumers of vehicles. Hence, the proposed research will include refining the results by expanding significantly the data set, and then developing an intelligent means of interpreting the corrosion present to produce high quality, consistent assessments of the state of vehicle corrosion.

New Approaches to Mine Closure in Nunavik, Québec

Mine closure is the final stage of a mine’s lifecycle and can have complex social, economic, and cultural impacts on nearby communities. These impacts include population decline, reduced services, household stress, ecological change, and reduced access to land-based activities. These impacts become more likely when communities are not engaged with during the closure planning process. Glencore Raglan is attempting to mitigate these issues through the Raglan Mine Closure Sub-committee, which is made up of both company employees and community representatives from Salluit and Kangiqsujuaq. Their goal is to collaboratively develop a closure plan that meets community needs. Through the Mitacs Accelerate program, students from Memorial University of Newfoundland are working with this sub-committee to aid its progress by: (a) tracking and evaluating its work, and (b) conducting comparative analyses of mine closure plans and mine remediation sites from across Northern Canada to inform the development of Raglan’s closure plan. This project will contribute to knowledge about best practices for community engaged mine closure planning and will ensure that the next iteration of Raglan’s closure plan more effectively meets community needs and centres Inuit voices.

Non-Viral Approach to Immunotherapy with Engineered Polymers

A new therapy was developed in order to combat cancers by stimulating our immune system to fight agents the cancer cells in the body. The activated immune system is more efficient to fight the cancer cells than the common drugs, but stimulating the immune system is very expensive and labour-intensive with the currently developed protocols. This project will develop a cost-effective way to stimulate immune system to fight cancers. We will use advanced biomaterials and immune stimulatory genes in order to achieve this. Our proposal is mush less labour intensive then the current protocols to stimulate immune system. Successful completion of the project will reduce the burden of immune-therapy on healthcare system and make the treatment available to a large population of patients.

Morphological investigation of adhesive blends and its effect on multilayer coating performance

In the pipeline industry, the heat shrink sleeves (HSS) are the protective layer usually composed of two layers, namely, an adhesive layer and a crosslinked backing layer such as polypropylene (PP) or polyethylene (PE). In order to maintain the desired properties of HSS, each of the layers must maintain their properties during processing, storage, and installation. In partnership with Canusa-CPS, the proposed research aims at addressing the relationships between the morphological structure and interfacial strength of the adhesive layers with their performance. Combining the characterization, rheological and mechanical analysis, the proposed study will correlate the mechanical performance of the adhesives to their material, design and morphological parameters. The research will be beneficial to our partner in developing a new generation of adhesives.

Rôle de la voie de signalisation Notch lors de la réponse des lymphocytes T CD8

Dans le domaine de la santé, l’étude de l’immunologie et des maladies infectieuses est un sujet de recherche important, car certaines maladies, tel que le VIH et le cancer, restent incurables à ce jour. Nos recherches s’intéressent à la réponse immunitaire adaptative et plus particulièrement aux lymphocytes T CD8, un type de globule blanc. Dans le cas particulier des infections chroniques et des cancers, il y a une persistance de la maladie à long terme provoquer entre autres par la présence continue de l’inflammation et de l’antigène ce qui mène progressivement à un état d’épuisement des lymphocytes T CD8 et un mauvais contrôle de ces maladies. Mon but est d’étudier les événements moléculaires impliqués dans la mise en place de l’épuisement des lymphocytes T CD8 dans un contexte d’infection chronique, afin de développer de nouvelles stratégies thérapeutiques pour combattre les infections chroniques et le cancer. Notre laboratoire s’intéresse particulièrement au rôle de la voie de signalisation Notch lors de la réponse des lymphocytes T CD8. Des résultats préliminaires suggèrent que la voie Notch joue un rôle important dans la prévention de l’épuisement des lymphocytes T CD8.

Metal Nitride Complexes with Non-innocent Carbene-phenolate Ligands for Hydrocarbon Amination

Organic feedstock chemicals such as those from extracted from natural gas and petroleum refinement are employed as fuels, however their abundance and relative inexpensive makes them attractive candidates as starting materials for other useful chemicals. This remains a difficult yet highly desired task for chemists, as these compounds are notoriously unreactive. We plan to develop catalysts; metal-containing compounds designed to facilitate feedstock transformation for use as viable reagents. Our approach is to synthesize these catalysts based on the active sites of certain metalloenzymes capable of facilitating these reactions elegantly at mild conditions. The key lies in the careful design of the surrounding framework bonded to the metal centre- the ligand. In most cases, the ligand does not participate in the electronic modifications in the overall catalyst, however our ligands (and those exemplified by the enzymes) are designed to shuttle electrons to and from the metal centre, greatly enhancing catalytic activity. Through a variety of approaches, this this project will result in the creation of new materials for the effective conversion of organic feedstocks.

Infrared imager

This project will develop the enabling technologies for next generation infrared sensors. Although infrared imaging was

historically developed for military applications, the biggest opportunities for growth are in commercial markets. Infrared

imaging is recognized as an important green technology because of its numerous applications in environmental

monitoring, thermography, process control, and inspection and maintenance of industrial equipment. Commercial vision

applications include surveillance, automotive and maritime safety, and fire?fighting. The proposed project represents an

important opportunity for Canada to contribute to these areas or growing importance. The main technical hurdles

addressed in this project include the development wafer?level vacuum packaging of microbolometers, low?temperature

3D?integration with electronics, cost?efficient deposition of high quality temperature sensitive thin film structures, and

optical efficiency. This project is in collaboration with Teledyne DALSA, developers of advanced imaging and semiconductor

technologies, with the Université de Sherbrooke and the École Polytechnique de Montréal.

Automatic weld seam positioning on sheet metal enclosures by semi-supervised deep learning

Deep learning in computer vision has set new standards in mobile and web-based applications. The power of learning-based computer vision has also tremendous potential in machine vision. Traditionally, machine vision in manufacturing employs analytic solutions often resulting in excellent accuracy but poor robustness. The goal of this project is to increase robustness of a vision-based measurement process in sheet metal manufacturing using deep learning. The ability to accommodate variations in manufacturing enables a manufacturer to provide customized solutions in a more time efficient and cost effective way. One of the major challenges in machine vision is the lack of appropriate large-size training data for supervised learning. This project will train a deep learning algorithm based on all kind of data including expert-labelled images, existing results of a machine vision algorithm and unlabeled images. The project is to provide an effective solution for the industrial partner and general research results.