Projets novateurs réalisés

Investigating the Health and Economic Benefits of Colostrum and Milk from Dairy Cattle Selected for Enhanced Immunity

Diseases of dairy cattle adversely affect meat and milk quality. Our research demonstrates that high immune response (HIR™) cattle have many health advantages, including better quality colostrum/milk. HIR™ technology is marketed by our partner Semex Inc as Immunity+. While many advantages of HIR™ exist, there is more to learn, particularly as it relates to colostrum. Colostrum is the first milk from the mother that protects the new born. HIR™ cows have enhanced specific antibody and pass this protection to their calves via colostrum. Apart from specific antibody there is also “natural” antibody that circulates without previous exposure to pathogens. Natural antibody has been under-investigated even though it is known to provide first-line defense. Various other natural defense molecules, known as defensins, also have not been investigated in the context of high immune responders. Examining natural antibody, vaccine response and defensins in colostrum/milk from high versus average immune responders will be the focus here.

Physiological assessment of cochlear and auditory nerve integrity in children suspected of auditory processing disorder – Year two

Nearly 2 % of school-aged children face difficulty in understanding speech in the presence of background noise. These children are often referred to audiology clinics for a central auditory processing (CAP) assessment. The purpose of the referral is to rule out an auditory processing disorder (APD). The American Speech-Language-Hearing Association recommends to include electrophysiological measures to assess the neural integrity in children sAPD. However, less than 15 % of audiologist include the electrophysiological measure in their battery of assessment. The aim of this project is to develop or improvise existing electrophysiological measures to detect auditory brainstem abnormalities in children sAPD. This will be achieved in collaboration with Vivosonic. Inc. Clinically available two-channel Vivosonic Integrity system will be used to record auditory evoked potentials (AEP) in APD children, typically developing children and adults. Findings of this study may provide novel information regarding the neural processing in APD children. TO BE CONT’D

Physiological assessment of cochlear and auditory nerve integrity in children suspected of auditory processing disorder

The American Speech-Language-Hearing Association (ASHA) recommends to include electrophysiological measures in their auditory processing disorder (APD) assessment battery. But few audiologist include electrophysiological assessment due to lack of evidence. There is strong evidence of auditory brainstem abnormality in these children. However, very less is understood about stimulus processing within the cochlea, auditory brainstem coding in noise (ipsilateral) and the thalmocortical functioning in APD children. As these evoked responses provide information regarding pre-neural processing, functioning of low spontaneous discharge rate (LSDR) fibers and upper-brainstem, respectively. With slight modification, these responses can be recorded using clinically available two-channel auditory evoked potential (AEP) system. In collaboration with Vivosonic. Inc, their existing AEP system will be improvised to record the electrocochleography, auditory brainstem responses in noise and the middle latency responses to a click and chirp stimulus. Evoked responses will be recorded from children sAPD, typically developing children and adults. The outcome of this project will provide novel information regarding the pre-neural and neural processing of acoustic stimuli in children sAPD. The collected data can be used in differential diagnosis of other auditory disorders such as auditory neuropathy.

Using LSA for Automatically Assessing Free Texts

To evaluate the content of free texts is a challenging task for human. Latent Semantic Analysis (LSA) can be used to automate this process. ShirWin Knowledge and Learning Systems Inc. is currently considering two instances of “free texts” assessment problems, one is automatic essay grading and the other is fact verification in a virtual learning environment . Both problems involve understanding the inner meaning of the free texts which can be successfully accomplished by using the LSA technique. The main objective of the proposed project is to verify the effectiveness of the LSA technology and conduct extensive experiments to provide solutions for the two problems. The performance of the LSA

models will be evaluated by measuring their correlation with the human-graded essays where better correlation will denote better effectiveness of the LSA technology.

Concussion Diagnosis: Improving clinical decision making in football

Diagnosing and managing concussions have become an increasing priority in sports medicine. The King-Devick test is a screening assessment of neurological functioning detecting impaired eye movements and saccades. During the 2016 Canadian Football League (CFL) season, all players will undergo pre-season (baseline) and post-injury testing with the King-Devick test in addition to the CFL’s standardized medical evaluation for concussion. This project will conduct a sensitivity and specificity analysis of the King-Devick test to evaluate its effectiveness in diagnosis concussions. It will be correlated with other well established concussion assessment tools such as the Sideline Concussion Assessment Test (SCAT). The utility of the King-Devick Test may enhance concussion diagnosis and management in professional football.

Signal in the network: public opinion polling using social media data

Can social media be used to make valid claims about public opinion? Skews in the usership of platforms such as Twitter and Facebook mean that the opinions of social media users usually do not reflect those of the population as whole. This project aims to develop a technique that corrects for the bias in social media data so as to make continuous, real-time, representative inferences about a target population. This project serves a case study focusing on the ability to predict political and electoral outcomes from social media. It aims to advance the scholarship in political methodology and contribute substantially to the research on political behaviour and electoral politics. It will also further the partner organization’s facility in predictive analytics using Big Data.

Deriving probiotics for male health

We are starting to understand a lot more about the bacteria in our intestinal tract which is called the microbiome. We think that these microorganisms are able to modulate the production of human hormones such as testosterone and actually produce some of these substances under specific conditions. We will look at the ability of beneficial probiotic strains to stimulate host or bacterial production in order to improve men’s health and ultimately would like to produce a probiotic product to do this for commercialisation. This will benefit the intern through microbiological investigations and the partner (Lallemand) who is a commercial producer of probiotics.

Using Deep Convolutional Neural Networks to predict compound-target interactions

Getting a new drug from the laboratory into the market is a lengthy and costly process which takes on average 12 years and over US$350 million to accomplish. It is composed of roughly 3 phases: (1) pre-clinical research, (2) clinical studies, and (3) the new drug application review. In this work, we propose an artificial intelligence system which will shorten the time it takes for pharmaceutical companies to identify novel drugs (compounds) for a given target (usually a protein or a protein complex). Our proposed system will predict the interactions between compounds and targets based on their 3D structure, and will be based on a large-scale and publically available database (ChEMBL) which contains information on 11,019 targets and more than 1.5 million compounds. We expect that our “learning from examples” approach, compared to the more traditional approach of manual engineering, will allow our system to better “understand” the structure of compounds and targets, and therefore, better predict their interactions.

Development of dual antibody therapies for cancer

Cancer is a devastating disease defined by genetic changes that result in the activation of proteins that encourage cell growth or prevent cell death. Modern oncology aims to specifically target these tumour-promoting proteins, which has the secondary benefit of leaving normal cells unharmed, unlike chemotherapy. Recently, a number of drugs that specifically block tumour-promoting proteins have been produced, yet the results are underwhelming: most targeted therapies show an initial benefit, followed by the development of resistance. To combat resistance, targeted therapies are often combined in multi-drug regimens, though these strategies are biased towards using existing drugs. Our approach aims to first identify new ‘helper’ drug targets that, when blocked, improve the efficacy of first generation targeted therapies being developed at the Centre for the Commercialization of Antibodies and Biologics (CCAB). Our second aim is to develop drugs that block the identified targets by engineering versions of naturally-occurring human proteins – antibodies – that bind the targets. These antibodies will be tested for their ability to increase targeted therapy efficacy, hopefully establishing novel approaches for cancer treatment and positively impacting the development of CCAB cancer drugs.

Designing novel algorithms for capturing and analyzing user experience in 4G networks

Fourth Generation networks (4G), mainly Long Term Evolution (LTE) technologies are going to be deployed in large scale starting from 2011. To leverage the benefits of this huge market opportunity, service and content providers need to deliver data capacity and Quality of Service (QoS) similar to existing wire line solutions. But, assuring good QoS over wireless links to the 4G mobile users would be an extremely challenging task. From this perspective, tools and solutions to service-level assurance for 4G networks will be in great demand. Hence, developing a software based framework for service quality assurance of 4G services is very important, because of the still evolving LTE standards and services. Having a software based framework, which the proposed project focuses on, will give complete flexibility for upgrade of the solution, as the standard and mobile services evolve.

Towards a sustainable anti-biofilm technology based on natural materials

Biofilms, surface-adherent microbial populations with enhanced tolerance to antibiotics and disinfectants, are widely-known contamination sources in environmental, industrial and medical settings. Novel approaches for the prevention and remediation of biofilms using nontoxic materials are urgently required. Interestingly, natural polysaccharides and nanopowders have anti-biofilm properties. We will develop a sustainable anti-biofilm technology using PhytoSpherix™ (Mirexus), a natural nanosized polysaccharide extracted from corn. High water dispensability and hydrating ability, paired with a capability to form ultra-thin-films, make PhytoSpherix™ an exceptional candidate anti-biofilm agent. Preliminary work has demonstrated that chemically-modified PhytoSpherix™ limits biofilm growth and enhances susceptibility to diverse antimicrobials. In the proposed project, we will employ Pseudomonads (ubiquitous spoilage bacteria and pathogen in industrial and medical settings) and Cyanobacteria (photosynthetic bacteria in aqueous environments) to study anti-biofilm properties of PhytoSpherix™ particles. For this purpose, we will perform laboratory experiments and use a variety of high resolution microscopy and spectroscopy techniques, which will yield critical insight into the mechanism of PhytoSpherix™ anti-biofilm properties and provide basis for the rationale design of novel anti-biofilm regimens. Licensing PhytoSpherix™-based formulations to industry will enable Mirexus to generate early revenue streams, hire more staff, further invest in R&D, and build a manufacturing plant – all in Canada.

iCity Urban Informatics for Sustainable Metropolitan Growth

The visualization/decision support work encompassed by this application addresses key elements of the upgrade path for that strategic part of IBM Canada’s smarter cities product and service portfolio– as urban transport systems evolve, their escalating complexity requires more advanced visualization tools and practices. The specific project proposed for development within the MITACS brief is:• development of a high-quality interactive 3D “”smart”” model of the Toronto Waterfront area bounded by Queen street to the north, Lake Ontario to the south, Shaw street to the west, and the Don river to the east.• the smart model will include a detailed 3D model of all buildings, streets, curbs, vegetation, street furniture, with elements either linked to current open data resources or actually procedurally generated on the fly on the basis of geodata.• the smart model and its ancillary information assets will be implemented separately in StoryFacets, Betaville, and CityEngine• the Betaville and StoryFacets implementations of the smart model will undergo user testing and iterative development with a broad range of users, recruited specifically to provide for variety of skill levels and engagement types: expert users of related professional tools, engaged citizens and advocates, decision-makers reliant on urban data visualizations.