SCRIPTORIUM (Université de Moncton)
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Improving the Functionality of Lentil–Casein Protein Complexes through Structural Interactions and Water Kefir-Assisted Fermentation
No full textHighly nutritious lentil proteins (LP) have recently attracted interest in the food industry. However, due to their low solubility, extensive application of LP is severely limited. This study describes a new and successful method for overcoming this challenge by improving the nutritional–functional properties of LP, particularly their solubility and protein quality. By combining protein complexation with water kefir-assisted fermentation, the water solubility of native LP (~58%) increases to over 86% upon the formation of lentil–casein protein complexes (LCPC). Meanwhile, the surface charge increases to over −40 mV, accompanied by alterations in secondary and tertiary structures, as shown by Fourier-transform infrared and UV-vis spectra, respectively. In addition, subjecting the novel LCPC to fermentation increases the protein digestibility from 76% to over 86%, due to the reduction in micronutrients that have some degree of restriction with respect to protein digestibility. This approach could be an effective and practical way of altering plant-based proteins.udemauteur: Carole Tranchan
Régulation de l'expression des cadhérines chez les cellules de sertoli du testicule
Full text linkLes cellules de Sertoli sont des cellules de soutien importantes pour l’établissement de la structure de la gonade, la quantité des cellules germinales et la spermatogénèse. Les cellules de Sertoli forment aussi la barrière-hémato testiculaire (BHT) qui est composée de plusieurs types de jonctions et des protéines d’adhésion, y compris des cadhérines. La CDH3 (P-cadhérine) est exprimée chez les cellules de Sertoli à partir de la vie fœtale et diminue après la naissance, tandis que la CDH2 (N-cadhérine) est exprimée de manière stable pendant tous les stades du développement des cellules de Sertoli. La délétion de Cdh2 spécifiquement chez les cellules de Sertoli perturbe la structure du testicule et des tubules séminifères, ce qui affecte la spermatogénèse et mène à une sous-fertilité. Plusieurs hormones comme la FSH, la testostérone, l’hormone thyroïdienne, l’activine et l’inhibine participent à la régulation de la prolifération et de la différenciation des cellules de Sertoli et également à la régulation des protéines jonctionnelles y compris des cadhérines. Parmi les facteurs de transcription, la famille AP-1 est un médiateur de plusieurs voies de signalisation importantes pour la prolifération et la différenciation des cellules de Sertoli et la régulation des jonctions testiculaires. Les profils d’expression des membres AP-1 sont corrélés avec celui de CDH3 chez les cellules de Sertoli. D’ailleurs, des membres de la famille AP-1 participent à la régulation d’autres protéines d’interaction comme GJA1 et NECTIN2 dans plusieurs types cellulaires du testicule. D’où vient l’hypothèse de mon projet : des membres de la famille AP-1 peuvent réguler l’expression des cadhérines chez les cellules de Sertoli. Pour valider ou invalider cette hypothèse, j’ai formulé deux objectifs. Le premier objectif est de caractériser la régulation transcriptionnelle de Cdh3 par des membres de la famille AP-1 chez les cellules de Sertoli. Le deuxième objectif est de définir les mécanismes de régulation transcriptionnelle de l’expression de Cdh2 par des membres de la famille AP-1 chez les cellules de Sertoli. Pour la méthodologie, les analyses bio-informatiques sur l’expression des gènes chez les cellules de Sertoli, sur les marqueurs épigénétiques et l’accessibilité de la chromatine v du testicule des souris ont été faites pour émettre des hypothèses et supporter les résultats obtenus. Afin de caractériser la régulation transcriptionnelle de Cdh2 et Cdh3, plusieurs types d’expériences ont été menés dans les lignées de cellules de Sertoli TM4 et 15P-1. Les régions promotrices de Cdh2 et Cdh3 ont été insérées dans des plasmides rapporteurs afin d’être utilisées pour les analyses de rapporteurs de luciférase avec les plasmides d’expression des membres AP-1. L’immunoprécipitation de la chromatine, les délétions du promoteur en 5’ et la mutagénèse dirigée du promoteur ont été faites pour identifier les régions et les éléments de régulation responsables de l’activation des promoteurs d’intérêt. Les knockdowns par ARNs d’interférence des membres de la famille AP-1, suivis par des immunobuvardages de type Western Blot, ont été faits pour déterminer l’importance des facteurs AP-1 dans l’expression de CDH2 et CDH3. Les cellules de Sertoli TM4 et 15P-1 ont été traitées avec des activateurs et inhibiteurs de voies de signalisations pour essayer de trouver les voies de signalisation régulant l’expression de CDH2 et CDH3. Pour le premier objectif, j’ai trouvé que les facteurs JUNB et FOSL2 sont importants pour le maintien de l’expression de CDH3 chez les cellules de Sertoli 15P-1. Ces deux facteurs coopèrent pour réguler l’expression de Cdh3 en se liant à un élément de régulation AP-1 à -47 bp dans la région proximale du promoteur Cdh3. Pour le deuxième objectif, j’ai montré que le facteur JUNB maintient l’expression de CDH2 chez les cellules de Sertoli TM4. JUNB régule l’expression de CDH2 en se liant à trois éléments de régulation AP-1 à -884 bp, -600 bp et -420 bp du promoteur Cdh2. Le promoteur Cdh2 est également activé par d’autres membres de la famille AP-1 chez les cellules de Sertoli TM4. En conclusion, les facteurs JUNB et FOSL2 régulent directement l’expression de CDH3 chez les cellules de Sertoli 15P-1, tandis que JUNB régule l’expression de CDH2 chez les cellules de Sertoli TM4.thesis: Ph. D. (sciences de la vie) Université de Moncton 202
Strengthening Social Capital to Address Isolation and Loneliness in Long-Term Care Facilities During the COVID-19 Pandemic: Systematic Review of Research on Information and Communication Technologies
No full textBackground: The COVID-19 pandemic has disproportionately and severely affected older adults, namely those living in long-term care facilities (LTCFs). Aside from experiencing high mortality rates, survivors were critically concerned by social isolation and loneliness (SIL). To address this serious public health concern and stay connected with LTCF residents, information and communication technology (ICT) platforms (eg, video calls) were used as an alternative to maintaining social interactions amid the visiting restriction policy. Objective: This paper aimed to synthesize the effects of ICT-related communication interventions using SMS text messaging or chat, video, voice mail, or photo to address SIL in LTCF residents during the COVID-19 pandemic. Methods: In total, 2793 references published in English and French in 2019 and onward were obtained from 10 relevant databases: PsycINFO-Ovid, Ovid-MEDLINE, CINAHL-EBSCO, Cochrane Library, Web of Science, Scopus, DirectScience, Communication & Mass Media Complete, IEEE Xplore, and ACM Digital Library. A 2-person screening approach was used, and the studies were screened independently and blindly. A narrative synthesis was performed to interpret the results of the included studies, and their quality was appraised. Results: In total, 4 studies were included in the review. ICT-related applications were used to ensure connectedness to address SIL. ICT interventions consisted mainly of videoconferencing, intergroup video call sessions between residents, and chatting (SMS text messages and phone calls). Roughly 3 classes of mediating ICT tools were used: video calls using software applications (eg, Skype); robot systems embedding video telephones; and ordinary telecommunication such as telephone, internet, social media platforms, and videoconferencing. This review has included the role of humanoid robots in LTCFs as an innovation avenue because of their multipurpose use (eg, communication tools and remotely operable). Conclusions: Remote social capitalization through ICT applications has become an avenue to reduce SIL among LTCF residents. This review examined a social connection approach that will remain relevant and even be fostered after the COVID-19 pandemic. As families remain the main stakeholders of LTCFs, this study’s findings could inform policy makers and frontline managers to better shape programs and initiatives to prevent or reduce SIL in LTCFs.udemauteur: Stéphanie Colli
Transformer models used for text-based question answering systems
No full textThe question answering system is frequently applied in the area of natural language processing (NLP) because of the wide variety of applications. It consists of answering questions using natural language. The problem is, in general, solved by employing a dataset that consists of an input text, a query, and the text segment or span from the input text that provides the question’s answer. The ability to make human-level predictions from data has improved significantly thanks to deep learning models, particularly the Transformer architecture, which has been state-of-the-art in text-based models in recent years. This paper reviews studies related to the use of transformer models in the implementation of question-answering (QA) systems. The paper’s first focus is on the attention and transformer models. A brief description of the architectures is presented by classifying them into models based on encoders, decoders, and on both Encoder-Decoder. Following that, we examine the most recent research trends in textual QA datasets by highlighting the architecture of QA systems and categorizing them according to various criteria. We survey also a significant set of evaluation metrics that have been developed in order to evaluate the models’ performance. Finally, we highlight solutions built to simplify the implementation of Transformer models.udemauteur: Moulay Akhlouf
Les émotions au coeur du leadership: des compétences émotionnelles pour diriger
No full textL’avènement de la crise sanitaire a exacerbé la complexité du quotidien des directions d’établissement d’enseignement dont le travail était déjà exigeant sur le plan émotionnel. Ces leaders doivent plus que jamais gérer sainement leurs propres émotions, tout en se préoccupant de celles vécues par les élèves, les parents et leur personnel, et ce, en maintenant la mission de l’école. L’objectif de cet ouvrage est de soutenir les directions dans leur développement professionnel en proposant une réflexion et des pistes d’action sur les émotions vécues en contexte de travail.
En plus de s’ancrer dans la littérature actuelle, ce livre se fonde sur une recherche dans laquelle sont étudiées les émotions impliquées dans l’actualisation du leadership des directions d’établissement d’enseignement du Québec. En cohérence avec le vécu de ces gestionnaires, une attention particulière est portée à l’anxiété, la colère et la joie. Les deux phases de cette recherche constituent les principales assises empiriques des propositions pratiques présentes dans ce livre. La première reprend les données collectées par questionnaires auprès d’un vaste échantillon de directions et de membres de leurs personnels. La seconde phase permet d’identifier et d’observer dans le cadre de leur travail réel des directions « exemplaires » ayant de bonnes compétences émotionnelles. Ce livre s’adresse à tous les acteurs du milieu de l’éducation qui cherchent à mieux comprendre l’influence des émotions vécues en position de leadership. Des pistes de réflexion et d’action pour l’actualisation du leadership par les émotions y sont proposées.udemauteur: Caterina Mampri
Explainable COVID-19 Detection Based on Chest X-rays using and End-to-End RegNet Architecture
No full textCOVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the worst pandemics in recent history. The identification of patients suspected to be infected with COVID-19 is becoming crucial to reduce its spread. We aimed to validate and test a deep learning model to detect COVID-19 based on chest X-rays. The recent deep convolutional neural network (CNN) RegNetX032 was adapted for detecting COVID-19 from chest X-ray (CXR) images using polymerase chain reaction (RT-PCR) as a reference. The model was customized and trained on five datasets containing more than 15,000 CXR images (including 4148COVID-19-positive cases) and then tested on 321 images (150 COVID-19-positive) from Montfort Hospital. Twenty percent of the data from the five datasets were used as validation data for hyperparameter optimization. Each CXR image was processed by the model to detect COVID-19. Multi-binary classifications were proposed, such as: COVID-19 vs. normal, COVID-19 + pneumonia vs. normal, and pneumonia vs. normal. The performance results were based on the area under the curve (AUC), sensitivity, and specificity. In addition, an explainability model was developed that demonstrated the high performance and high generalization degree of the proposed model in detecting and highlighting the signs of the disease. The fine-tuned RegNetX032 model achieved an overall accuracy score of 96.0%, with an AUC score of 99.1%. The model showed a superior sensitivity of 98.0% in detecting signs from CXR images of COVID-19 patients, and a specificity of 93.0% in detecting healthy CXR images. A second scenario compared COVID-19 + pneumonia vs. normal (healthy X-ray) patients. The model achieved an overall score of 99.1% (AUC) with a sensitivity of 96.0% and specificity of 93.0% on the Montfort dataset. For the validation set, the model achieved an average accuracy of 98.6%, an AUC score of 98.0%, a sensitivity of 98.0%, and a specificity of 96.0% for detection (COVID-19 patients vs. healthy patients). The second scenario compared COVID-19 + pneumonia vs. normal patients. The model achieved an overall score of 98.8% (AUC) with a sensitivity of 97.0% and a specificity of 96.0%. This robust deep learning model demonstrated excellent performance in detecting COVID-19 from chest X-rays. This model could be used to automate the detection of COVID-19 and improve decision making for patient triage and isolation in hospital settings. This could also be used as a complementary aid for radiologists or clinicians when differentiating to make smart decisions.udemauteur: Mohamed Chetoui; Moulay Akhlouf
DCTable: A Dilated CNN with Optimizing Anchors for Accurate Table Detection
No full textWith the widespread use of deep learning in leading systems, it has become the mainstream in the table detection field. Some tables are difficult to detect because of the likely figure layout or the small size. As a solution to the underlined problem, we propose a novel method, called DCTable, to improve Faster R-CNN for table detection. DCTable came up to extract more discriminative features using a backbone with dilated convolutions in order to improve the quality of region proposals. Another main contribution of this paper is the anchors optimization using the Intersection over Union (IoU)-balanced loss to train the RPN and reduce the false positive rate. This is followed by a RoI Align layer, instead of the ROI pooling, to improve the accuracy during mapping table proposal candidates by eliminating the coarse misalignment and introducing the bilinear interpolation in mapping region proposal candidates. Training and testing on a public dataset showed the effectiveness of the algorithm and a considerable improvement of the F1-score on ICDAR 2017-Pod, ICDAR-2019, Marmot and RVL CDIP datasets.udemauteur: Moulay Akhlouf
Spinosad‐associated modulation of select cytochrome P450s and glutathione S‐transferases in the Colorado potato beetle, Leptinotarsa decemlineata
No full textThe Colorado potato beetle (Leptinotarsa decemlineata (Say)) is an insect pest that threatens potato crops. Multiple options exist to limit the impact of this pest even though insecticides remain a primary option for its control. Insecticide resistance has been reported in Colorado potato beetles and a better understanding of the molecular players underlying such process is of utmost importance to optimize the tools used to mitigate the impact of this insect. Resistance against the insecticide spinosad has been reported in this insect and this work thus aims at exploring the expression of targets previously associated with insecticide response in Colorado potato beetles exposed to this compound. Amplification and quantification of transcripts coding for cytochrome P450s and glutathione S-transferases were conducted via qRT-PCR in insects treated with varying doses of spinosad and for different time duration. This approach notably revealed differential expression of CYP6a23 and CYP12a5 in insects exposed to low doses of spinosad for 4 h as well as modulation of CYP6a13, CYP6d4, GST, GST1, and GST1-Like in insects treated with high doses of spinosad for the same duration. RNAi-based targeting of CYP4g15 and CYP6a23 was associated with marked reduction of transcript expression 7 days following dsRNA injection and reduction of the former had a marked impact on insect viability. In general, results presented here provide novel information regarding the expression of transcripts relevant to spinosad response in Colorado potato beetles and reveal a novel target to consider in the development of RNAi-based strategies aimed at this potato pest.udemauteur: Pierre Bastarache; Raed Bouafoura; Enock Omakele; Pier Jr Mori
The impacts of capacity-building in seniors on territorial development and aging in place: A perceptual analysis of the case of Saint-Quentin in New Brunswick
No full textIn Canada, New Brunswick is a province particularly affected by the aging of its population. This phenomenon raises many social, economic and territorial issues and challenges. Capacity-building for elders goes some way to mitigating the effects. However, what is more specifically its contribution to aging in place and territorial development ? The objective of this article is to assess the perception of local dynamism with regard to the management of an aging population from different components related to the capacity-building of seniors. The case of the small town of St-Quentin, New Brunswick, holds our attention. Our demonstration is based on seven elements related to capacity-building, namely : participation, empowerment, relational life and social capital, sense of identity, resilience and networking. This exploratory case study examined the actors from the angle of social representations using four methods : semi-structured interviews, holding a focus group, conducting individual interviews with seniors and organizing a dissemination activity. The results show that capacity-building has beneficial effects on community vitality and improving the quality of life of the elderly. However, the model has its limits due to conditions inherent to the environment, but also to exogenous factors over which seniors have little control, hence the need for the Government of New Brunswick to put in place a territorial aging strategy.udemauteur: Majella Simard; Mario Pari