5 research outputs found
SCHIZOPHRÉNIE : Accompagner un itinérant dans son traitement
Pour information, contactez Mark Bédard au mark.bedard@umontréal.caRemerciements pour les conseils donnés: 1) Dominique Saheb, M. Ps., Psychologue, Clinicienne et chargée de cours à la Faculté de l'éducation permanente de l'Université de Montréal 2) Mathieu Gattuso, Ph.D., Psychologue, Leduc Ressources Humaines 3) Philippe Vincent, B. Pharm., M. Sc., Professeur adjoint de clinique à la faculté de pharmacie de l'Université de MontréalTravail réalisé dans le cadre du cours PHA2415Nous, étudiants en pharmacie de l'Université de Montréal, sommes heureux de vous présenter le résultat de notre implication dans un projet d’envergure communautaire portant sur les maladies mentales. Plus précisément, ce guide se penche sur l’étude des relations entre l’itinérance et la schizophrénie. En révisant la littérature, nous avons été en mesure de déterminer la portée de votre travail sur les itinérants. Une enquête faite auprès des sans-abris de la région de Montréal-Centre et de Québec montre une prévalence notable de personnes souffrant de schizophrénie chez les sans-abris qui ont recours aux centres d’aide. Selon cette enquête, l’intervention de première ligne devrait miser sur un meilleur encadrement des personnes victimes de troubles mentaux pour éviter qu’ils se retrouvent sans abri.Cet outil vise à apporter une aide considérable au travail d'intervenants sociaux d'organismes communautaires de Montréal travaillant avec une clientèle itinérante. Détaillant les symptômes de la maladie ainsi que les approches possibles par rapport au traitement de la schizophrénie, ce document vous offrira l’opportunité de mieux comprendre l’individu ayant un diagnostic de schizophrénie. De plus, il vous donnera aussi des outils pour mieux l’accompagner dans son traitement et favoriser sa motivation. C’est un guide pratique se voulant visuel et simple pour une utilisation quotidienne efficace
Controlling the mass bias introduced by anionic and organic matrices in silicon isotopic measurements by MC-ICP-MS
info:eu-repo/semantics/publishe
Automated screening of potential organ donors using a temporal machine learning model
Abstract Organ donation is not meeting demand, and yet 30–60% of potential donors are potentially not identified. Current systems rely on manual identification and referral to an Organ Donation Organization (ODO). We hypothesized that developing an automated screening system based on machine learning could reduce the proportion of missed potentially eligible organ donors. Using routine clinical data and laboratory time-series, we retrospectively developed and tested a neural network model to automatically identify potential organ donors. We first trained a convolutive autoencoder that learned from the longitudinal changes of over 100 types of laboratory results. We then added a deep neural network classifier. This model was compared to a simpler logistic regression model. We observed an AUROC of 0.966 (CI 0.949–0.981) for the neural network and 0.940 (0.908–0.969) for the logistic regression model. At a prespecified cutoff, sensitivity and specificity were similar between both models at 84% and 93%. Accuracy of the neural network model was robust across donor subgroups and remained stable in a prospective simulation, while the logistic regression model performance declined when applied to rarer subgroups and in the prospective simulation. Our findings support using machine learning models to help with the identification of potential organ donors using routinely collected clinical and laboratory data
MFG-E8 Reduces Aortic Intimal Proliferation in a Murine Model of Transplant Vasculopathy
Transplant vasculopathy is characterized by endothelial apoptosis, which modulates the local microenvironment. Milk fat globule epidermal growth factor 8 (MFG-E8), which is released by apoptotic endothelial cells, limits tissue damage and inflammation by promoting anti-inflammatory macrophages. We aimed to study its role in transplant vasculopathy using the murine aortic allotransplantation model. BALB/c mice were transplanted with fully mismatched aortic transplants from MFG-E8 knockout (KO) or wild type (WT) C57BL/6J mice. Thereafter, mice received MFG-E8 (or vehicle) injections for 9 weeks prior to histopathological analysis of allografts for intimal proliferation (hematoxylin and eosin staining) and leukocyte infiltration assessment (immunofluorescence). Phenotypes of blood leukocytes and humoral responses were also evaluated (flow cytometry and ELISA). Mice receiving MFG-E8 KO aortas without MFG-E8 injections had the most severe intimal proliferation (p p = 0.003) and decreased systemic CD4+ and CD8+ T-cell activation (p p < 0.01). Thus, the analarmin MFG-E8 appears to be an important protein for reducing intimal proliferation in this murine model of transplant vasculopathy. MFG-E8 effects are associated with intra-allograft macrophage reprogramming and systemic T-cell activation dampening
Diatom silicon isotopes as a proxy for silicic acid utilisation: a Southern Ocean core top calibration
Despite a growing body of work that uses diatom δ30Si to reconstruct past changes in silicic acid utilisation, few studies have focused on calibrating core top data with modern oceanographic conditions. In this study, a microfiltration technique is used to divide Southern Ocean core top silica into narrow size ranges, separating components such as radiolaria, sponge spicules and clay minerals from diatoms. Silicon isotope analysis of these components demonstrates that inclusion of small amounts of non-diatom material can significantly offset the measured from the true diatom δ30Si. Once the correct size fraction is selected (generally 2–20 μm), diatom δ30Si shows a strong negative correlation with surface water silicic acid concentration (R2 = 0.92), highly supportive of the qualitative use of diatom δ30Si as a proxy for silicic acid utilisation. The core top diatom δ30Si matches well with mixed layer filtered diatom δ30Si from published in situ studies, suggesting little to no effect of either dissolution on export through the water column, or early diagenesis, on diatom δ30Si in sediments from the Southern Ocean. However, the core top diatom δ30Si shows a poor fit to simple Rayleigh or steady state models of the Southern Ocean when a single source term is used. The data can instead be described by these models only when variations in the initial conditions of upwelled silicic acid concentration and δ30Si are taken into account, a caveat which may introduce some error into quantitative reconstructions of past silicic acid utilisation from diatom δ30Si