Variations inter journalières dans la structure des communautés de poissons : implications pour le développement de modèles de qualité d'habitats

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Optimization of temporal versus spatial replication in the development of habitat use models to explain among-reach variations of fish density estimates in rivers

Abstract: We evaluated the effects of temporal variation of fish density estimates on the explanatory power of habitat use models. Fish density estimates were obtained using visual surveys (10 visits) in eighteen 100 m reaches over a 7-week period. Physical attributes of reaches were estimated. Field data were used to develop a simulation domain (10 000 reaches) that reflected the spatio-temporal variability of fish density estimates and physical attributes. Simulations indicated that for a sampling effort of approximately 200 surveys, the number of reaches surveyed (25 to 200) and the number of surveys per reach (1 to 8) affected the adjusted R 2 of models by 5% to 42%. The established practice of sampling a maximized number of reaches once did not appear necessarily optimal for developing habitat use models. Analysis of temporal coefficients of variation suggests that species within the same family may require a similar survey design. Hence, for salmonids, it may be more appropriate to sample more reaches once, and for cyprinids, it may be more optimal to repeatedly sample fewer reaches

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

ABSTRACT: SIGNIFICANCE: The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise and reagents may become less specific to the virus. AIM: We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. The machine learning (ML) models involved could be frequently updated to include spectral information about variants without needing to develop new reagents. APPROACH: We present a workflow for collecting, preparing, and imaging dried saliva supernatant droplets using a non-invasive, label-free technique-Raman spectroscopy-to detect changes in the molecular profile of saliva associated with COVID-19 infection. RESULTS: We used an innovative multiple instance learning-based ML approach and droplet segmentation to analyze droplets. Amongst all confounding factors, we discriminated between COVID-positive and COVID-negative individuals yielding receiver operating coefficient curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity and 75% specificity) and females (84% sensitivity and 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. CONCLUSION: These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases

Intraoperative Stimulation Mapping in Neurosurgery for Anesthesiologists—Part 1: The Technical Nuances

Brain mapping has evolved tremendously in the past decade, fueled by advances in functional neuroimaging technology in neuro-oncology and epilepsy surgery. Despite this, wide anatomic-functional interindividual variability and intraoperative brain shift continue to challenge neurosurgeons performing surgery within or near eloquent brain regions. As such, intraoperative direct cortical and subcortical stimulation mapping remains the gold standard for localizing eloquent brain regions with precision for a safe and tailored resection. Intraoperative stimulation mapping (ISM) allows for maximizing the extent of resection while minimizing postoperative neurological deficits, resulting in better patient outcomes. Understanding the technical nuances of ISM is imperative for the anesthesiologist to provide better anesthetic management tailored to the surgery and stimulation mapping planned. A comprehensive search was performed on electronic databases to identify articles describing intraoperative cortical and subcortical mapping, language, and motor mapping. In the first part of this narrative review, we summarize the salient technical aspects of ISM and the common neurophysiological tasks assessed intraoperatively relevant to the anesthesiologist

Data from: Modelling habitat distributions for multiple species using phylogenetics

In this paper, we describe an empirical approach to model community structure using phylogenetic signals. That approach combines information about the species (i.e. traits and phylogeny) with information about the habitat (i.e. environmental conditions and spatial distribution of sampling sites) and their interactions to predict the species responses (e.g. the local densities). As an application, we use the approach to model fish densities in rivers. In the model, the different species and size classes were described using a functional trait, body length, and phylogenetic eigenvectors maps whereas the sites were described using water velocity, depth, substrate composition, macrophyte cover, degree-days, total phosphorus, and spatial eigenvector maps. The model (estimated using a regularised Poisson-family Generalised Linear Modelling approach) fitted the data well (likelihood-based R2adj=0.512) and showed fair predictive power (likelihood-based cross-validation R2=0.283) to predict the density of fish pertaining to 48 species totalling 143 combinations of species and size classes in 15 unregulated Canadian rivers. Using the model as a baseline to estimate the effect of flow regulation on community composition, we found that, with few exceptions, the densities of most fish species were lower in regulated than in unregulated rivers. Phylogenetics have been proposed to study community structure, but this is, to our knowledge, the first time phylogenetic information is used explicitly for numerical habitat modelling. We expect that models of that type will be in increasing demand now that development projects are routinely assessed through impact studies

Data and R language file to replicate all analyses and results

Contains all data tables and phylogenetic trees in addition to the R code, allowing one to replicate the analysis shown in the paper. The R file is annotated

Colchicine reduces lung injury in experimental acute respiratory distress syndrome.

The acute respiratory distress syndrome (ARDS) is characterized by intense dysregulated inflammation leading to acute lung injury (ALI) and respiratory failure. There are no effective pharmacologic therapies for ARDS. Colchicine is a low-cost, widely available drug, effective in the treatment of inflammatory conditions. We studied the effects of colchicine pre-treatment on oleic acid-induced ARDS in rats. Rats were treated with colchicine (1 mg/kg) or placebo for three days prior to intravenous oleic acid-induced ALI (150 mg/kg). Four hours later they were studied and compared to a sham group. Colchicine reduced the area of histological lung injury by 61%, reduced lung edema, and markedly improved oxygenation by increasing PaO2/FiO2 from 66 ± 13 mmHg (mean ± SEM) to 246 ± 45 mmHg compared to 380 ± 18 mmHg in sham animals. Colchicine also reduced PaCO2 and respiratory acidosis. Lung neutrophil recruitment, assessed by myeloperoxidase immunostaining, was greatly increased after injury from 1.16 ± 0.19% to 8.86 ± 0.66% and significantly reduced by colchicine to 5.95 ± 1.13%. Increased lung NETosis was also reduced by therapy. Circulating leukocytosis after ALI was not reduced by colchicine therapy, but neutrophils reactivity and CD4 and CD8 cell surface expression on lymphocyte populations were restored. Colchicine reduces ALI and respiratory failure in experimental ARDS in relation with reduced lung neutrophil recruitment and reduced circulating leukocyte activation. This study supports the clinical development of colchicine for the prevention of ARDS in conditions causing ALI