Program abstracts

Cynthia Bruce, PhD, MTA
Associate Professor, Department of Creative Arts Therapies, Concordia University

The under-representation of disabled people in health professions has been documented in activist and scholarly sources that highlight, as a partial explanation, our collective struggle to imagine disabled individuals as anything other than receivers of care. Disabled students and professionals point to specific access barriers and suggest that health professions education programs need to engage seriously with accessibility as a necessary precondition of improved health equity. This presentation will explore, in the context of creative arts therapies education and training, how intentional focus on accessible teaching and learning environments that centre first voice expertise might create more inclusive pathways to health professions and reposition disabled people as givers, not simply receivers, of care.

Anan Chen, PhD
Assistant Professor, Department of Chemistry and Biochemistry, Concordia University

Plus-strand RNA viruses constitute the largest genetic class of eukaryotic viruses, including SARS-CoV-2, tumor-inducing HCV, debilitating CHIKV, lethal encephalitis viruses and many other emerging pathogens. A major target for understanding and thus controlling +RNA viruses is their genome replication complex, which rewires host endomembranes to form replication organelles—the central site of viral genome replication. Recent progress in cryo-electron tomography and structural modeling tools has shed light onto “crown”-like viral replication complexes, which assemble into pore-like structures on the membrane of replication organelles in different +RNA viruses. Our research reveals the function and mechanism of coronaviral molecular pore, which links viral RNA synthesis with export from the double-membrane vesicles. By integrating membrane biochemical analysis with cell-based assays, we determined the molecular composition and topology of the molecular pore-replicase complex. We developed new methods in isolating double-membrane vesicles and molecular pores, establishing a platform to study viral-host interaction and the pore structure among different +RNA viruses. A conserved ring of residues in the pore lining was also identified, forming a constraint for viral RNA transit through the pore. Leveraging this data, we are testing the concept of a new class of pore-targeting antivirals, which can be broadly effective against +RNA virus infection.

Laura Domínguez
PhD Candidate, Department of Chemistry and Biochemistry, Concordia University

Antibiotic resistance poses a growing threat to public health, contributing to millions of deaths every year. Within this broader challenge, nitrofurantoin remains an important antibiotic in clinical use, making it especially relevant to understand how bacteria respond to its effects. One of the primary stress responses triggered by nitrofurantoin is the SOS pathway, which is activated by DNA damage. RecA plays a central role in this pathway by promoting DNA repair and mutagenesis. The importance of this response is underscored by the fact that RecA-deficient strains exhibit up to 64-fold greater sensitivity to nitrofurantoin, highlighting a strong link between the SOS response and nitrofurantoin susceptibility.

This study investigates RecA’s role in the evolution of nitrofurantoin resistance and evaluates RecA inhibition as a therapeutic strategy. Using the Soft Agar Gradient Evolution (SAGE) system, we followed the evolution of resistance across 32 independent lineages of wild-type (WT) and ΔrecA E. coli. We performed whole-genome sequencing to identify mutations associated with resistance, as well as lineages that failed to evolve higher levels of resistance. We found that ΔrecA strains evolved significantly lower resistance levels than WT. We also found that canonical resistance pathways were not enough to achieve clinically relevant resistance levels in an SOS-deficient background. In addition, we identified alternative pathways that can contribute to nitrofurantoin resistance in the absence of a functional SOS response, along with the fitness cost associated with this evolutionary process. In parallel, we tested three reported RecA inhibitors for their ability to reduce nitrofurantoin resistance and found that chemical inhibition of RecA failed to reproduce the full hypersensitivity seen in genetic knockouts.

These findings reveal that targeting RecA represents a promising strategy to help preserve the clinical utility of nitrofurantoin and reduce the ability of bacteria to adapt during treatment. This work advances understanding of antibiotic resistance evolution and informs future approaches to constrain bacterial adaptation.

Karina Lebel, PhD
Professor, Department of Electrical and Computer Engineering,
University of Sherbrooke

Wearable sensing technologies increasingly allow us to quantify human movement across scales, yet technology alone does not ensure that what we measure is meaningful for health. In this talk, we will reflect on how movement sensing approaches, with a focus on inertial technology, must be chosen with careful attention to who the measurement is for, who will interpret and use the data, and why it matters in a given clinical context. Using examples spanning neurological disorders, individuals at risk of falls, and emerging rehabilitation paradigms, such as efforts to restore walking after spinal cord injury, we will illustrate how different questions call for different measurement compromises. Rather than focusing solely on sensor performance, we will consider issues of interpretability, trust, and realism when movement technologies leave the lab and enter clinical or real-world settings. Together, we will explore the potential, and potential pitfalls, of wearable technologies for movement assessment in health.

Juliette Lemay 
PhD Candidate, Psychoeducation, Université Laval

Sabrina Sacco
PhD Candidate, Department of Psychology, Concordia University

Weight-related conditions, like overweight and obesity, are associated with a variety of physical and psychosocial health consequences. To improve health outcomes associated with pediatric overweight and obesity, behavioral weight management interventions are the first treatment approach. Physical health outcomes (e.g., weight change) are typically the primary focus when evaluating intervention effects, which limits our understanding of the potential impacts of such interventions on all aspects of one’s health, including psychosocial health outcomes. Using scoping reviews and mixed-method approaches, our research aims to gain a better understanding on i) the extent in which psychosocial health outcomes have been investigated across the literature, and ii) the psychosocial consequences of participating in behavioral interventions for pediatric overweight and obesity. Our findings suggest that there are inconsistencies in the assessment and reporting of psychosocial health outcomes. Our research also found that both positive and negative changes in psychosocial health outcomes are experienced in response to intervention participation.

Joyce Lui, PhD
Assistant Professor, Department of Psychology, Concordia University

Attention-deficit/hyperactivity disorder (ADHD) is highly heritable, with many parents and children experiencing ADHD within the same family. Parent ADHD has been associated with poorer treatment outcomes for children, yet most interventions focus on the child alone, highlight a gap in current care models. Treating both parent and child ADHD together may lead to better outcomes for the whole family.
This presentation describes findings from a hybrid effectiveness-implementation trial conducted in a pediatric primary care in the US. Families were assigned to receive either stimulant medication for the parent followed by Integrated Behavioural Parent Training (I-BPT), or I-BPT alone. Outcomes included child impairment, parent impairment, and parenting practices.
Quantitative findings indicate that combining parent medication with I-BPT was associated with faster improvements in both child and parent impairment, as well as faster gains in some parenting practices, compared to I-BPT alone. Qualitative findings highlight both opportunities and challenges for implementation in pediatric primary care. Themes suggest that framing care as supporting the whole family may help build trust and acceptability of the care model. At the same time, participants identified tensions between the intervention model and existing system capacity, including constraints related to billing, scheduling, and staffing. Further adaptation to I-BPT may also be needed to support parents with ADHD.
Together, findings suggest that treating parent ADHD may enhance the effectiveness of parenting interventions for families with ADHD. However, this model may not be readily implementable in pediatric primary care without adaptation to both intervention and system-level supports. Implications for integrated family mental health services will be discussed.

Panos Margaris, PhD
Assistant Professor, Department of Economics, Concordia University

We develop a life cycle model that features food consumption, exercise, and deviation from reference BMI, which represents local social norms, to rationalize spatial concentration and the educational gradient in body mass in the US. BMI is determined by caloric balance and affects health and medical spending, the probability of survival, and the level of utility. We find that social norms play an important role in the spatial and educational gradients observed in obesity, and moving an individual from a high to a low obesity region reduces average weight by more than 3 pounds. To demonstrate the policy relevance of the social norm, we introduce a GLP-1 treatment policy targeting individuals with the highest food preferences. We find substantial direct effects on average BMI, with reductions ranging from 1 to 6.3 pounds, depending on the region and targeting intensity. Importantly, we document meaningful spillover effects arising from endogenous adjustment of reference BMI that further amplify these effects and amount to 38–127% of the direct treatment effect. The BMI reductions translate into substantial life expectancy gains: treated individuals experience increases of 0.9-1.4 years depending on treatment intensity, while untreated individuals gain 0.03-0.24 years through spillover effects.

Carrie Martin
PhD Candidate, Concordia University

Shirley Pien-Berube
Health Navigator, Indigenous Health Centre of Tiohtià:ke

In this presentation, we will highlight the important work undertaken at the Indigenous Health Centre of Tiohtia:ke (IHCT) that has led to a holistic model of care for HIV, hep C and STBBI services. Grounded in culture, the IHCT’s sexual health and harm reduction services have been designed to meet the unique needs of the communities it serves, and throughout this presentation, we will walk you through how this was developed and implemented and how we continue to grow our services to meet new demand.

Simon Matoori, PhD
Assistant professor, Faculty of Pharmacy, Université de Montréal

Drug delivery systems have traditionally been used to control the release kinetics of drugs. However, their controlled release properties can also be utilized to modulate the diffusion of analytes, analyte-sensing molecules, and interferences. In this seminar, I will demonstrate how these properties of delivery systems can be leveraged to develop novel diagnostic materials. In particular, I will present the development of an ammonia-sensing polymersome microreactor. High phase transition temperature polymersomes exhibit selective permeability for small uncharged molecules such as ammonia, a common biomarker in liver disease, and are thus suitable for blood ammonia sensing. This system was validated in an IRB-approved study and combined with a portable fluorometer for point-of-care use. While these polymersomes are highly selective for ammonia, we showed that this technology can be used to sense analytes beyond ammonia. Combining the polymersomes with ammonia-generating enzymes such as urease, the polymersomes can be used to detect the ammonia generated by the enzymatic breakdown of urea, and thus provide an indirect readout on the blood urea concentration. Ammonia-sensing polymersomes underline the high versatility of drug delivery systems, and their usefulness for diagnostic applications.

Altynai Pankratov
PhD Candidate, Department of Economics, Concordia University

During the COVID-19 pandemic, retirement rates in the United States rose sharply, with about 2 million excess retirements in the first year alone. This paper examines two channels behind that surge: heightened health risk and financial preparedness. Using the Health and Retirement Study (2016--2020), I compare transitions into retirement before and during the first year of the pandemic for workers aged 55--74. The results show that the retirement response to the pandemic was highly heterogeneous. In the pooled sample, a 10 pp increase in the frailty index is associated with an additional 4.1 pp increase in retirement during the pandemic. This effect is stronger among workers aged 65--74 (6.3 pp), and non-remote workers (4.8 pp), and is especially pronounced in the top earnings group, where the corresponding increase reaches about 7.4 pp. These patterns suggest that the pandemic retirement surge reflected the interaction of health vulnerability and financial preparedness, with especially strong effects among older and higher-earning workers.

Catherine Richardson, PhD
Professor, School of Community and Public Affairs, Concordia University

In this presentation, Cathy Richardson will discuss her work across contexts explaining how she applies dignity-centered frameworks. This talk will explore dignity, resistance to mistreatment and the professional crafting of dignity-based social responses to people who have been harmed.

Natalya Watson
PhD Candidate, Department of Physics, Concordia University

From diseases caused by mucus membrane malformation to novel hydrogel development, biologically speaking, mucus is far more interesting than a stuffy nose. Experimentation on this abundant yet unique substance poses several unexpected challenges, including rapid degradation of gel properties and heterogeneity of samples. Molecular modelling of mucosal systems avoids many of these challenges, however, it presents many of its own. Mucus primarily consists of mucin proteins possessing long glycosylated backbones and dynamic disulfide linkage domains, which are too large and too flexible to be simulated at atomistic resolution. Mucin proteins must be truncated and approximated computationally to be feasibly modelled. Our group is tackling this problem by developing models of gut mucus at multiple scales of coarse-graining. We are developing a chemically-specific representation of the MUC2 mucin using the Martini force field to understand the effects of glycosylation on disulfide linkage formation. We also recently developed a lower-resolution bead-string polymer model and computational pipeline for simulating MUC2 in LAMMPS and Python. The system showed no gelation across all parameters tested. We suggest that adding reactive disulfide crosslinks is the most crucial next step toward modelling a complete system. Molecular modelling of mucin systems provides access to high-resolution dynamic data that is not attainable using conventional experimental methods. Presented here are the preliminary data and methodology we take to tackle this problem.

Christopher Yee Wong, PhD
Assistant Professor, Department of Mechanical, Industrial and Aerospace Engineering (MIAE), Concordia University

Integrating autonomous robotic assistants into domestic and healthcare settings can help people with disabilities and support elderly independence where these robots may offer direct physical assistance, e.g., helping users move around or providing rehabilitation. To ensure utility and social acceptance, these interactions must be both physically and emotionally safe, intuitive, and comfortable for users. My core research goal is to advance robot cognition for highly physical interactions between humans and robots by considering not only the human physical state, but the human emotional state as well. My work spans the practical domain, such as developing new interaction and classification methods for physical manipulation of robots through touch, to the social domain where we examine the social and emotional barriers for the adoption of robotic assistants, and finally a combination where we model how robot actions directly affect the human emotional response.