Clinically isolated syndromes and multiple sclerosis: prospective clinical and MRI follow up after 30 years and features at earlier time-points

This thesis is based on a 30-year follow-up study of a cohort of people who initially presented, in the 1980’s, with clinically isolated syndromes (CIS), suggestive of relapse-onset multiple sclerosis (MS). The main aims were: 1) to study the very long-term outcome of the cohort, with particular attention on those who have fared well over time, 2) review the idea and definition of ‘benign’ MS, a controversial entity, and 3) to identify any potential early clinical and radiological features, of 30-year outcome. MS is a very heterogenous condition and biomarkers of long-term prognostication remain limited. With the increasing range of disease modifying therapies available, it is important that treatment decisions should, as far as possible, involve a personalized risk-benefit analysis. At 30 years, I found that the clinical outcomes of the cohort were diverse. Approximately a third remained CIS, and two thirds developed MS. Within the MS group, who were largely untreated, ~40% remained ambulatory, ~35% had developed significant disability, and 20% had died related to their MS. Comparisons between the ambulatory MS group and CIS group, showed that the groups were not significantly different across several clinical measures. In this cohort, the strongest early predictors of 30-year outcomes identified were radiological features. The presence of MRI white matter lesions in specific locations in the brain, within one year of presentation, were able to predict 30-year clinical outcomes with accuracies in the 70-75% range. These results could potentially be applied in a clinical setting and help inform treatment decisions

Immunomodulatory effects of 17-O-acetylacuminolide in RAW264.7 cells and HUVECs : involvement of MAPK and NF-κB pathways

The terpenoid 17-O-acetylacuminolide (AA) was shown to inhibit the production of several inflammatory mediators. However, the mechanisms by which this compound elicited its anti-inflammatory activity remain to be elucidated. In this study, we analyzed the effects of AA on inflammatory gene expression in two different cell types with primordial importance in the inflammatory processes-endothelial cells and macrophages. In human umbilical vein endothelial cells, AA inhibited the expression of inflammatory proteins including the adhesion molecules intercellular adhesion molecule 1; vascular cell adhesion molecule 1; and E-selectin, as well as the release of the chemokine interleukin-8. Additionally, AA hindered the formation of capillary-like tubes in an in vitro model of angiogenesis. AA's effects in endothelial cells can be attributed at least in part to AA's inhibition of tumor necrosis factor alpha-induced nuclear factor of kappa light polypeptide gene enhancer in B-cells (NF-kappa B)'s translocation. Also, in lipopolysaccharide-stimulated macrophage-like RAW264.7 cells, AA was able to downregulate the expression of the genes cyclooxygenase 2, inducible nitric oxide synthase, interleukin-6, and chemokine (C-C motif) ligand 2. Moreover, AA inhibited the phosphorylation of nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor-alpha (I kappa B alpha), I kappa B kinase (IKK), and the mitogen-activated protein kinases JNK, ERK, and p38. In conclusion, the present results further support the anti-inflammatory potential of AA in different models of inflammation

Resilience among Single Adult Female Refugees in Hamilton, Ontario

Single adult females remain among the most vulnerable of all refugee populations. However, there is a lack of research on supporting and empowering these women. There is a new interest in identifying factors that reinforce resilience and, ultimately, adjustment to the host country. In line with the current work on resilience, semi-structured, in-depth, personal interviews with single refugee women were conducted in the city of Hamilton, Ontario. A grounded theory approach revealed participants’ perspectives on the support received from religious or cultural communities, non-governmental organizations, and the government in terms of their perceived contribution to adaptation. Both informal and formal support, along with individual characteristics, were found to be crucial for reinforcing resilience among these refugees, reflective of a collective resilience model that moves beyond individual and community resilience. Future research should aim to investigate the perspectives of those who did not receive social support from shelters as well as to assess the efficacy of current refugee support services.Les femmes adultes célibataires demeurent parmi les plus vulnérables des groupes de réfugiés. On remarque cependant un manque de recherches sur le soutien et l’autonomisation de ces femmes. Il y a par ailleurs un nouvel intérêt pour l’identification des facteurs augmentant la résilience et par conséquent la capacité d’ajustement au pays d’accueil. En lien avec ces travaux sur la résilience, des entrevues individuelles approfondies et semi-structurées avec des femmes réfugiées célibataires ont été eff ectuées à Hamilton en Ontario. L’approche basée sur la théorie a mis en lumière leur point de vue sur le soutien qu’elles reçoivent des communautés culturelles et religieuses et des organisations gouvernementales et non-gouvernementales, plus particulièrement au niveau de leur adaptation. Le soutien formel et informel, en plus des caractéristiques personnelles, s’avèrent être des facteurs importants pour l’amélioration de leur résilience, illustrant un modèle de résilience qui va au-delà de la résilience individuelle et des communautés. Les recherches à venir devraient examiner la perception des réfugiés qui n’ont pas reçu de soutien social et évaluer l’effi cacité des services actuels de soutien aux réfugiés

Work group inclusion : test of a scale and model

We develop a theoretically based 10-item measure of work group inclusion comprised of two components (belongingness and uniqueness) and use this measure to empirically test the nomological network of work group inclusion developed by Shore et al. In Phase 1, we use two samples of full-time employees to develop and refine items as well as establish content validity. In Phase 2, we demonstrate convergent, discriminant, and incremental validity with both conceptually related and unrelated constructs. In Phase 3, we use data from an additional sample of employees and supervisors to test criterion-related validity and mediation by examining the multilevel relationships between inclusion and important antecedents and outcomes. Across the three phases of our study, the results demonstrate support not only for the factor structure, reliability, and validity of our work group inclusion measure but also for a theoretical model in which the construct of inclusion has important implications for individuals and organizations

Inclusive leadership : realizing positive outcomes through belongingness and being valued for uniqueness

We introduce a theoretically-grounded conceptualization of inclusive leadership and present a framework for understanding factors that contribute to and follow from inclusive leadership within work groups. We conceptualize inclusive leadership as a set of positive leader behaviors that facilitate group members perceiving belongingness in the work group while maintaining their uniqueness within the group as they fully contribute to group processes and outcomes. We propose that leader pro-diversity beliefs, humility, and cognitive complexity increase the propensity of inclusive leader behaviors. We identify five categories of inclusive leadership behaviors that facilitate group members' perceptions of inclusion, which in turn lead to member work group identification, psychological empowerment, and behavioral outcomes (creativity, job performance, and reduced turnover) in the pursuit of group goals. This framework provides theoretical grounding for the construct of inclusive leadership while advancing our understanding of how leaders can increase diverse work group effectiveness

AV2Wav: Diffusion-Based Re-synthesis from Continuous Self-supervised Features for Audio-Visual Speech Enhancement

Speech enhancement systems are typically trained using pairs of clean and noisy speech. In audio-visual speech enhancement (AVSE), there is not as much ground-truth clean data available; most audio-visual datasets are collected in real-world environments with background noise and reverberation, hampering the development of AVSE. In this work, we introduce AV2Wav, a resynthesis-based audio-visual speech enhancement approach that can generate clean speech despite the challenges of real-world training data. We obtain a subset of nearly clean speech from an audio-visual corpus using a neural quality estimator, and then train a diffusion model on this subset to generate waveforms conditioned on continuous speech representations from AV-HuBERT with noise-robust training. We use continuous rather than discrete representations to retain prosody and speaker information. With this vocoding task alone, the model can perform speech enhancement better than a masking-based baseline. We further fine-tune the diffusion model on clean/noisy utterance pairs to improve the performance. Our approach outperforms a masking-based baseline in terms of both automatic metrics and a human listening test and is close in quality to the target speech in the listening test. Audio samples can be found at https://home.ttic.edu/~jcchou/demo/avse/avse_demo.html.Comment: Submitted to ICASSP 202

Languages, Learning & Inclusion

This book was created as part of the ADDEPT - Autonomy, Diversity & Disability: Everyday Practices of Technology funded by ARC Linkage Project LP190100099. The digital narratives were co-created with participants across a set of online, face-to-face workshops in addition to focus groups and follow-up one-to-one interviews. Each of the participants with the project team to examine, explore and create visual digital accessible books of their personal experiences with everyday technologies and share the impact upon their lives. The impact is positive and also, at times, negative with significant challenges due to the biases with AI technology design, especially for people with disabilities who are from minority diverse backgrounds and have access to few resources to fund comprehensive assistive technologies. Over a period of two years of working, research participants were able to critically engage with AI technologies and create these books to publicly disseminate their diverse experiences to enable others to learn from them

Few-Shot Spoken Language Understanding via Joint Speech-Text Models

Recent work on speech representation models jointly pre-trained with text has demonstrated the potential of improving speech representations by encoding speech and text in a shared space. In this paper, we leverage such shared representations to address the persistent challenge of limited data availability in spoken language understanding tasks. By employing a pre-trained speech-text model, we find that models fine-tuned on text can be effectively transferred to speech testing data. With as little as 1 hour of labeled speech data, our proposed approach achieves comparable performance on spoken language understanding tasks (specifically, sentiment analysis and named entity recognition) when compared to previous methods using speech-only pre-trained models fine-tuned on 10 times more data. Beyond the proof-of-concept study, we also analyze the latent representations. We find that the bottom layers of speech-text models are largely task-agnostic and align speech and text representations into a shared space, while the top layers are more task-specific