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Identification of Signalling Pathways Regulating Autophagy in Response to Cellular Stress
No full textMacroautophagy (hereafter referred to as autophagy) is a key cellular degradative process that plays an important role in maintaining cellular homeostasis. Defects in autophagy are linked to a range of health conditions, including but not limited to metabolic disorders, inflammatory bowel diseases, and cancer. Despite decades of research, measurement of autophagy dynamics in rare cell populations and in vivo remains challenging due to the inherent limitations of existing tools. We developed a novel approach for autophagy measurement by monitoring the phosphorylation of ATG16L1 on serine 278 (pATG16L1ˢ²⁷⁸). We found that phospho-ATG16L1 is exclusively localized to nascent autophagosomes, and that its detection is not confounded by prolonged cellular stress or late-stage autophagy impairments, which often obscure autophagic analyses. We have developed and characterized a monoclonal antibody capable of specifically detecting endogenous phospho-ATG16L1 in mammalian cells. This highly versatile antibody enables its use in Western blotting, immunofluorescence, and immunohistochemistry assays for autophagy measurement.
In the context of metabolic disorders, we investigated the impact of chronic iron overload on the autophagy pathway. Iron overload is a clinical hallmark of metabolic syndrome, which is a collection of conditions often associated with insulin resistance and is known to lead to increased risk of developing cardiovascular disease and type 2 diabetes. We discovered that chronic iron overload induced major autophagy disruptions, as evidenced by the accumulation of defective autolysosomes and a significant depletion of free lysosomes in skeletal muscle cells. The autophagy defects, in turn, led to impairment of insulin-stimulated glucose uptake and disrupted insulin signaling. Mechanistically, we demonstrated that iron overload affected Akt-mediated suppression of tuberous sclerosis complex 2 (TSC2) and reduced Rheb-dependent activation of mechanistic target of rapamycin complex 1 (mTORC1) on autolysosomes. This dysregulation inhibited the autophagic‐lysosome regeneration, thereby contributing to the development of insulin resistance. Notably, restoring mTORC1 signaling to the autophagy machinery on mature autophagosomes, or removing excess iron, significantly replenished lysosomal pools and restored insulin sensitivity. This discovery uncovers the potential therapeutic pathways that could be targeted to improve insulin sensitivity in metabolic syndrome.
Additionally, we examined the process of ER-phagy, which is the selective degradation of the endoplasmic reticulum (ER) by autophagy. ER-phagy is critical for maintaining cellular homeostasis and is frequently targeted by pathogens to create a more favourable cellular environment for infection. We discovered that Salmonella Typhimurium utilizes a mechanism to inhibit ER-phagy by targeting the ER-phagy receptor FAM134B. This inhibition prevents FAM134B oligomerization, a key step in the ER-phagy pathway, leading to increased intracellular bacterial load post-invasion. In FAM134B knockout mice, we observed increased susceptibility to Salmonella infection, characterized by severe intestinal damage and elevated bacterial loads. Furthermore, we identified the bacterial effector SopF as the primary mediator of FAM134B inhibition, shedding light on how intracellular bacteria such as Salmonella could subvert innate immune defenses.
Together, these studies provide a comprehensive understanding of the complex regulatory networks that govern autophagosome biogenesis, maturation, and functionality. They also highlight the critical role of environmental factors in modulating autophagic activity and maintaining cellular homeostasis, revealing the dynamic interplay between intracellular mechanisms and external stimuli in the regulation of autophagy. Identifying novel therapeutic targets, such as phospho-ATG16L1 and FAM134B, offers promising avenues for developing interventions to restore autophagy and mitigate disease progression
Transdiagnostic internet cognitive behavioural therapy for anxiety and depressive symptoms in postnatal women: protocol of a randomized controlled trial
No full textAbstract Background Nearly 20% of women will be confronted with anxiety or depressive disorders during the perinatal period and this may lead to adverse outcomes for both mother and child. Cognitive behavioural therapy (CBT) is the psychological intervention with the most empirical support for the clinical management of anxiety and depressive disorders. Anxiety and depression frequently occur in women during the perinatal period, and there is growing evidence that internet-delivered CBT (iCBT) could be an acceptable and effective intervention. THIS WAY UP, an Australian digital mental health service, has developed a program for postnatal anxiety and depression. This study protocol aims to examine the acceptability and efficacy of a French-Canadian adaptation of the program. Methods/design The research team propose to conduct a mixed hybrid type 1 pragmatic randomized clinical trial and implementation study to replicate the findings of the trial conducted in Australia by Loughnan et al. (2019), as well as explore barriers and facilitators to potential large-scale implementation. Treatment and control conditions a) postnatal anxiety and depression iCBT program with three lessons to complete in a six-week period, added to treatment-as-usual (TAU); b) TAU. Participants will include French-speaking women with probable postnatal depression or anxiety as per the Generalized Anxiety Disorder-7 (GAD-7) or the Edinburgh Postnatal Depression Scale (EPDS). The primary outcome measures will be the GAD-7 and the EPDS. Secondary outcome measures will comprise self-reported instruments to evaluate psychological distress, quality of life, mother–child experience, and treatment experience. Qualitative interviews with participants and health professionals will provide insights on acceptability and delivery of the iCBT program. Statistical analysis Statistical analysis will follow intent-to-treat principles. A mixed model regression approach will be used to account for between- and within-subject variations in the analysis of the effects of iCBT compared to TAU only intervention. Discussion The study will generate important data of efficacy and acceptability to patients, clinicians, and decision-makers to inform the scaling-up of the postnatal iCBT intervention in Canada. Trial registration ClinicalTrials.gov: NCT06778096, prospectively registered on 2025/01/16
Becoming a Public Action Subject: Articulatory Practices and Political Subjectivity in Mexico's Ateneo Nacional de la Juventud
No full textThis doctoral thesis presents a comprehensive analysis of the emergence of collective identities and social organization among youth for political participation, specifically focusing on Ateneo Nacional de la Juventud, an organization led by young Mexicans. The research sought to understand how collective identity emerged and impacted the members of this organization, employing the theoretical perspective of post-Marxism and the sociology of public action. The study delves into the articulatory practices carried out by Ateneistas to establish itself as a political subject participating in public action and explores the evolution of the Ateneista subjectivity. It also places a significant emphasis on the role of digital social networks in the organization's processes, reflecting the increasing influence of technology on social organizations.
Theoretical and empirical literature reviews on youth and civil society organizations (CSOs) have been conducted to contextualize the study within the current socio-economic system of late capitalism. The need to redefine youth within the context of late capitalism is addressed, emphasizing the impact of globalization, job insecurity, and educational extension on the lives of young individuals. The study also underscores the active participation of young people in the social and political sphere to improve their living conditions, emphasizing the role of social organizations in generating critical awareness and providing a frame of reference for youth engagement. This thesis aims to contribute a nuanced understanding of youth participation in the social and political sphere, particularly through digital social networks, and its implications for social change in a moment where social movements have detached from the workers' movement. The findings will inform and stimulate theoretical debates on youth studies, post-Marxism and the sociology of public action. Additionally, it offers practical insights for youth organizations like Ateneo that seek to empower individuals to influence positive social transformations
Structural brain differences in school-aged children who are HIV-exposed uninfected
No full textAbstract Background Antiretroviral therapy (ART) has dramatically reduced perinatal HIV transmission, leading to a growing population of children who are HIV-exposed but uninfected (CHEU). While the neuroanatomic developmental impacts of in utero HIV and ART exposure have been studied in young children, long-term effects on school-aged children are poorly understood, prompting this investigation. Methods Fifty-eight CHEU and 38 children who are HIV-unexposed, uninfected (CHUU), 6–12 years old, were recruited through hospitals and community groups in Ontario, Canada. From T1-weighted magnetic resonance images, volume, cortical thickness, and gray-/white-matter tissue volume were extracted. Multiple linear regression models controlling for sex, age, household income, and total brain volume were fit to assess differences by in utero HIV exposure, with additional sex-stratified analyses to uncover sex-specific effects. Results Compared with CHUU, CHEU showed total brain volumes that were significantly smaller by 49.7cm3 (95% CI [− 95.66, − 3.67]) and cortices thinner by 0.08 mm (95% CI [− 0.13, − 0.02]). In male CHEU, three regions displayed volumetric age-exposure interactions: the bilateral pars opercularis at 0.36 cm3/year (95% CI [0.10, 0.62]), left rolandic operculum at 0.22 cm3/year (95% CI [0.04, 0.39]) and left precentral gyrus at 0.71 cm3/year (95% CI [0.22, 1.21]), suggesting delayed maturation in those regions. Bilateral frontal lobe cortical thickness was reduced by 0.07 mm in CHEU (95% CI [− 0.14, − 0.006]), most pronounced in the left orbital middle frontal gyrus with a reduction of 0.20 mm among male CHEU (95% CI [− 0.32, − 0.07]). An age-exposure interaction of 0.06 cm3/year in bilateral amygdala volume (95% CI [− 0.11, − 0.01]) suggested reduced growth or altered developmental trajectory among CHEU, whereas male CHEU showed bilateral hippocampal volumes diminished by 0.21 cm3 (95% CI [− 0.40, − 0.01]). Conclusions These findings suggest that in utero HIV and ART exposure have broad neuroanatomic developmental impacts, particularly in boys, with significant differences in brain regions critical for motor function, expressive language, memory, and emotion. These structural differences align with previously reported motor and language deficits and highlight the importance of early intervention and tailored support strategies for CHEU
AI for Inside Ballot Box: Four Steps to Take Protect Elections and Defend Democracy
No full textRecent examples from Brazil, Romania, Gabon, di US, and oda countries don show say di way politicians dey use AI fit spoil elections and shake democracy.
Many countries no ready for di AI wahala: plenty no get law wey go guide AI use for elections, political parties never agree on fair way to use AI, and most places no sabi how to fight AI attacks wey fit spoil their democracy.
We dey recommend dis four actions: government suppose update election rules (like to ban fake AI-generated content), political parties suppose get code of conduct wey go guide how dem go use AI for politics, election authorities suppose set up independent teams wey go stop and respond to AI -related wahala, and for international level, governments suppose create International AI Electoral Trustkeepers plus protocols to handle cross-border interference.Dis project happen thanks to di support of Fonds de recherche du Québec, CEIMIA, di Canada CIFAR Chair in AI and Human Rights for Mila, and di University of Ottawa Research Chair in Technology and Society. E also get help from Délégation du Québec à Rome and SIOI wey support di retreat arrangement
Quando l’intelligenza artificiale interferisce con le elezioni: Quattro azioni per salvaguardare l’integrità elettorale e sostenere la democrazia
No full textEsempi recenti di Brasile, Romania, Gabon, Stati Uniti e altri Paesi mostrano come l’uso dell’IA da parte di attori politici possa danneggiare l’integrità elettorale e la democrazia.
Le nazioni sono spesso impreparate ad affrontare le sfide legate all’IA: molte non hanno regole che disciplinino l’IA nelle elezioni, i partiti politici non si sono accordati su pratiche elettorali eque nell’era dell’IA e la maggior parte delle giurisdizioni non è in grado di contrastare efficacemente gli attacchi alle proprie istituzioni democratiche.
Raccomandiamo quattro azioni: i governi dovrebbero aggiornare le norme elettorali (ad esempio, per proibire contenuti ingannevoli generati dall’IA); i partiti politici dovrebbero adottare un codice di condotta con linee guida chiare sull’uso politico responsabile dell’IA; le autorità elettorali dovrebbero istituire team indipendenti per prevenire e rispondere ai disagi causati dall’IA; a livello internazionale, i governi dovrebbero istituire dei fiduciari elettorali internazionali per l’IA e protocolli per affrontare le interferenze transfrontaliere.Questo progetto è stato intrapreso grazie al contributo del Fonds de recherche du Québec, del CEIMIA, della Chaire Canada-CIFAR en IA et droits de la personne presso Mila, e della Chaire de recherche de l’Université d’Ottawa en technologie et société, e con l’aiuto della Delegazione del Québec a Roma e della SIOI per l’organizzazione del ritiro
Le Programme REL de la Bibliothèque de l’Université d’Ottawa : rapport d’évaluation
No full textLancé en 2020, le Programme REL de la Bibliothèque de l’Université d’Ottawa cherche d’abord à sensibiliser les membres du corps professoral aux coûts du matériel de cours commercial pour les inciter à plutôt choisir des ressources gratuites en libre accès pour alléger le fardeau financier des apprenantes et apprenants et ainsi favoriser l’accès aux connaissances. De plus, compte tenu du manque persistant de ressources pédagogiques en français en contexte minoritaire, le programme (en particulier sa subvention) vise également à encourager la production de ressources éducatives libres dans cette langue.
Le Programme REL a fait l’objet d’une évaluation pour juger de sa pertinence, de son efficacité et de son efficience. Cet exercice coïncide avec la cinquième et dernière année du programme et a pour but de déterminer si les ressources humaines et financières investies ont mené aux résultats immédiats et intermédiaires anticipés et de proposer des améliorations advenant la mise en œuvre d’autres initiatives REL à l’Université d’Ottawa
On New Advances in Nonparametric Bayesian Priors and Their Applications
No full textBayesian nonparametric inference requires the construction of priors on infinite-dimensional spaces, such as the space of cumulative distribution functions. Well-known priors on this space include the Dirichlet process and the two-parameter Poisson–Dirichlet process. In this thesis, we explore a distinctive functional of the Poisson point process, known as the negative binomial process. While the increments of the negative binomial process are not independent, they become conditionally independent given an underlying gamma variable. We propose a novel point process representation for the negative binomial process, which extends the Poisson-Kingman distribution and its associated random discrete probability measure. The new proposed family of the discrete random probability measures which is defined by normalizing the points of the negative binomial process provides a new set of useful priors for Bayesian nonparametric models with more flexibility compared to the random discrete probability measure which are obtained by normalizing the points of a Poisson point process. We illustrate how this family encompasses several well-known priors, such as the Dirichlet process, the normalized positive α-stable process, and the Poisson–Dirichlet process. Using the same gamma Lévy measure, we derive an extension of the Dirichlet process along with an almost sure approximation. Additionally, leveraging our negative binomial process representation, we develop a new series representation for the Poisson–Dirichlet process. Through simulations, we demonstrate how adopting priors from this family can enhance the performance of Bayesian nonparametric hierarchical models.
In the literature, the term negative binomial process has been used to describe several distinct stochastic processes, each playing a significant role in probability theory and statistics, particularly in Bayesian nonparametric analysis. However, the presence of multiple, and at times conflicting, definitions has led to considerable ambiguity. This thesis addresses this issue by systematically reviewing the various definitions and clarifying their distinctions. The aim is to provide a comprehensive overview that helps practitioners recognize the differences between these processes and avoid potential misunderstandings. Furthermore, for one of the definitions of the negative binomial process, we present an extension from the univariate case to a bivariate form.
We also examine the Liouville distribution, a well-known conjugate prior for the multinomial distribution, which addresses certain limitations of the Dirichlet distribution, particularly its tendency to induce negative correlations. We construct a discrete random probability measure based on a random vector following a Liouville distribution and establish its weak limit to define the proposed Liouville process. This process takes the form of a spike-and-slab model, where the slab is represented by a Dirichlet process and the spike corresponds to a single point drawn from its mean. These components are combined through a random convex mixture, with weights governed by the Liouville distribution. By placing the Liouville process as a prior over the space of probability measures, we derive both its posterior and predictive distributions
Navigating Legal Boundaries: The Role of NGO Workers in Supporting Immigrant Survivors of D/IPV and Mediating Police Interventions in Ontario
No full textThis thesis explores the challenges NGO workers in Ontario face as they navigate police interventions in cases of D/IPV involving immigrants. Using a qualitative approach grounded in interviews, this thesis examines how workers' legal consciousness is shaped by professional obligations, structural constraints, and cultural contexts, informing their engagement with the legal system. While participants critiqued systemic shortcomings, such as law enforcement's lack of cultural sensitivity and trauma-informed practices, they simultaneously relied on police interventions during crises. This reliance reflects a structural necessity stemming from resource limitations and hegemonic norms that prioritize reactive measures over preventative alternatives. The findings highlight the complex relationship between NGOs, their clients, and law enforcement, highlighting the challenges of addressing systemic barriers while advocating for culturally responsive practices. By situating these dynamics within a broader socio-legal framework, this research contributes to understanding how structural power and resource dependency shape frontline responses to D/IPV
Detection, Categorization and Repair of Flaky Tests Using Large Language Models
No full textSoftware testing is critical for ensuring software dependability. However, some test cases, known as flaky tests, exhibit non-deterministic behavior, passing or failing inconsistently even with the same source code version. These flaky tests create significant overhead in software development, requiring developers to rerun tests or debug code unnecessarily. Traditional approaches for detecting flaky tests involve rerunning them multiple times, a process that is computationally expensive and impractical for large test suites. Machine learning (ML) models have been proposed as a scalable alternative to predict flaky tests without reruns. However, existing ML-based techniques often rely on production code or project-specific features, limiting their generalizability across diverse projects. Furthermore, the use of predefined feature sets results in suboptimal accuracy when applied to realistic datasets. To address these challenges, we propose two novel, black-box, large language model-based solutions: (a) Flakify: A flaky test predictor that relies solely on the source code of test cases, eliminating the need for access to production code or predefined feature sets. Flakify uses CodeBERT, a pre-trained language model, and demonstrates superior performance on two benchmark datasets. It achieves F1-scores of 79% and 73% using cross-validation and per-project validation on the FlakeFlagger dataset, and 98% and 89% on the IDoFT dataset. Flakify outperforms the state-of-the-art solution (FlakeFlagger) by 10 and 18 percentage points in precision and recall, respectively. (b) FlakyFix: A framework designed to predict the required fix for flaky tests by classifying them into 13 distinct fix categories based solely on test code analysis. By leveraging code models and few-shot learning, FlakyFix accurately predicts most fix categories. To further enhance flaky test repairs, we augment GPT 3.5 Turbo prompts with predicted fix category labels. Our experimental results show that 51% to 83% of GPT-suggested repairs pass, with only 16% of the test code needing further modifications for the remaining cases. These two approaches significantly reduce the overhead associated with rerunning flaky tests and provide an efficient method for predicting and repairing flaky tests, making them more suitable for real-world industrial applications