College Choice Mechanism: The Respect of the Vagueness of Choices

Taking as a starting point the theory of matching applied in the case of a problem of college admissions, where one is interested only to strict preference profiles for students and colleges, a part of the literature has been oriented towards profiles of priorities for colleges. In this paper we will assume that students have also their own priorities to which is associated some 'fuzzy'. This vagueness designates the preference of an individual (resp. college) for a college relative to parameters that characterize the latter one (resp. individual). Thus, we talk about fuzzy priorities. Our purpose is to analyze this aspect and to propose a real-life mechanism which will take into consideration the fuzzy priority profiles of both students and colleges, in order to achieve the best possible matching that is stable, strategy-proof, Pareto efficient and fair.Education, Priorities, Preferences, Fuzzy, Algorithm, Matching

The chemical ecology of Harmonia axyridis

peer reviewedIn the recent SI of BioControl and resultant book from this working group (Roy et al., 2012), we contributed a review paper on the chemical ecology of the invasive aphidophagous ladybird Harmonia axyridis (Sloggett et al., 2011). This paper focused on both the pure and applied aspects of this subject, including sections on: (1) chemical defence; (2) foods, feeding and reproduction; (3) H. axyridis chemistry, humans and human activity, and (4) future research perspective

Tyrosine-based rivastigmine-loaded organogels in the treatmant of Alzheimer's disease

Faculté de PharmacieOrganogels can be prepared by immobilizing an organic phase into a threedimensional network coming from the self-assembly of a low molecular weight gelator molecule. In this work, an injectable subcutaneous organogel system based on safflower oil and a modified-tyrosine organogelator was evaluated in vivo for the delivery of rivastigmine, an acetylcholinesterase (AChE) inhibitor used in the treatment of Alzheimer’s disease. Different implant formulations were injected and the plasmatic drug concentration was assayed for up to 35 days. In parallel, the inhibition of AChE in different brain sections and the biocompatibility of the implants were monitored. The pharmacokinetic profiles were found to be influenced by the gel composition, injected dose and volume of the implant. The sustained delivery of rivastigmine was accompanied by a significant prolonged inhibition of AChE in the hippocampus, a brain structure involved in memory. The implant induced only a minimal to mild chronic inflammation and fibrosis, which was comparable to poly(D,L-lactide-co-glycolide) in situ-forming implants. These findings suggest that tyrosine-based organogels could represent an alternative approach to current formulations for the sustained delivery of cholinesterase inhibitors.IRS

Evolution of dementia diagnosis over time (1988-2013): Evidence from French and English cohorts. Implication for secular trends analyses.

INTRODUCTION: The aims of this study are to examine the evolution of clinical dementia diagnosis over 3 decades and to investigate secular trends of dementia. METHODS: Four cohorts covering a period from 1988 to 2013 were used: the Personnes Agées Quid and Three-City-Bordeaux studies, and the Cognitive Function and Aging Study (CFAS) I and II. Mini-Mental State Examination scores at clinical diagnosis were evaluated over a 24-year follow-up period in French studies. An algorithmic approach was applied to CFAS I and II to provide dementia prevalence and incidence estimates. RESULTS: A significant increase of the Mini-Mental State Examination score at diagnosis was observed until 2000 and a significant decrease after. We reported a prevalence of 8.8% for CFAS I (1990-1993) compared with a prevalence of 6.5% in CFAS II (2008-2011). The 2-year incidence rate was estimated at 31.2/1000 (95% confidence interval = 28.0-34.8) for CFAS I and 15.0/1000 (95% confidence interval = 13.5-16.7) for CFAS II. DISCUSSION: Applying a stable algorithm to different cohorts across time can provide a robust method for time trends estimation.Includes MRC grants

Deep Learning Body Region Classification of MRI and CT examinations

Standardized body region labelling of individual images provides data that can improve human and computer use of medical images. A CNN-based classifier was developed to identify body regions in CT and MRI. 17 CT (18 MRI) body regions covering the entire human body were defined for the classification task. Three retrospective databases were built for the AI model training, validation, and testing, with a balanced distribution of studies per body region. The test databases originated from a different healthcare network. Accuracy, recall and precision of the classifier was evaluated for patient age, patient gender, institution, scanner manufacturer, contrast, slice thickness, MRI sequence, and CT kernel. The data included a retrospective cohort of 2,934 anonymized CT cases (training: 1,804 studies, validation: 602 studies, test: 528 studies) and 3,185 anonymized MRI cases (training: 1,911 studies, validation: 636 studies, test: 638 studies). 27 institutions from primary care hospitals, community hospitals and imaging centers contributed to the test datasets. The data included cases of all genders in equal proportions and subjects aged from a few months old to +90 years old. An image-level prediction accuracy of 91.9% (90.2 - 92.1) for CT, and 94.2% (92.0 - 95.6) for MRI was achieved. The classification results were robust across all body regions and confounding factors. Due to limited data, performance results for subjects under 10 years-old could not be reliably evaluated. We show that deep learning models can classify CT and MRI images by body region including lower and upper extremities with high accuracy.Comment: 21 pages, 2 figures, 4 table

Mesenchymal Stromal Cell Therapy in Ischemia/Reperfusion Injury.

Ischemia/reperfusion injury (IRI) represents a worldwide public health issue of increasing incidence. IRI may virtually affect all organs and tissues and is associated with significant morbidity and mortality. Particularly, the duration of blood supply deprivation has been recognized as a critical factor in stroke, hemorrhagic shock, or myocardial infarction, as well as in solid organ transplantation (SOT). Pathophysiologically, IRI causes multiple cellular and tissular metabolic and architectural changes. Furthermore, the reperfusion of ischemic tissues induces both local and systemic inflammation. In the particular field of SOT, IRI is an unavoidable event, which conditions both short- and long-term outcomes of graft function and survival. Clinically, the treatment of patients with IRI mostly relies on supportive maneuvers since no specific target-oriented therapy has been validated thus far. In the present review, we summarize the current literature on mesenchymal stromal cells (MSC) and their potential use as cell therapy in IRI. MSC have demonstrated immunomodulatory, anti-inflammatory, and tissue repair properties in rodent studies and in preliminary clinical trials, which may open novel avenues in the management of IRI and SOT