A typology of goat farming in Reunion Island prior to the implementation of a breeding scheme adapted to the French overseas departments

In September 2008, The "Office de développement de l’économie agricole d’outre-mer" carried out an assignment in the five French overseas departments and territories to evaluate the demand for genetic improvement of breeding goats (Boué et al., 2008). This expertise concluded with an original proposal: testing the implementation of a common breeding scheme adapted to the 5 territories. As Reunion Island offers a favourable context for such a project, it was proposed to locate the selection nucleus there. For this purpose, a first assessment of the diversity of livestock systems was undertaken to understand farmer practices and breeding management orientations. We present here A typology of goats’ livestock systems stemming from a study realized in 2009 (Bouyssière, 2009) is thus presented in this paper

The Moka cattle, an element of the Reunion Island heritage to preserve

International audienc

Capacité d'adaptation et pratiques de trésorerie des éleveurs à l'île de la Réunion.

Analyse des pratiques de trésorerie des éleveurs réunionnais, à partir de données issues de deux suivis : un groupe de sept élevages entre 2001 et 2002 et un groupe de six élevages entre 2003 et 2004. L'accompagnement des élevages bovins réunionnais en terme de raisonnement sur les pratiques de trésorerie apparaît une voie à approfondir dans le contexte actuel d'évolution des politiques agricoles de l’Union Européenne et d’augmentation du prix des matières premières

Parcs éoliens du premier appel d’offres éolien en mer

L’année 2015 a permis de mener à bien la deuxième partie du programme d’évaluation archéologique des parcs éoliens du 1er appel d’offres initié en 2014. Le présent résumé fait état de l’ensemble des opérations menées en 2014 et en 2015, soit six opérations (OA 2524, 2525, 2772, 2773, 2777 et 2787) menées sur quatre départements, au large de Saint-Nazaire (44), Saint-Brieuc (22), Courseulles-sur-Mer (14) et Fécamp (76). Rappel du contexte d’intervention En avril 2012, le Gouvernement a retenu ..

Melanoma cells break down LPA to establish local gradients that drive chemotactic dispersal.

The high mortality of melanoma is caused by rapid spread of cancer cells, which occurs unusually early in tumour evolution. Unlike most solid tumours, thickness rather than cytological markers or differentiation is the best guide to metastatic potential. Multiple stimuli that drive melanoma cell migration have been described, but it is not clear which are responsible for invasion, nor if chemotactic gradients exist in real tumours. In a chamber-based assay for melanoma dispersal, we find that cells migrate efficiently away from one another, even in initially homogeneous medium. This dispersal is driven by positive chemotaxis rather than chemorepulsion or contact inhibition. The principal chemoattractant, unexpectedly active across all tumour stages, is the lipid agonist lysophosphatidic acid (LPA) acting through the LPA receptor LPAR1. LPA induces chemotaxis of remarkable accuracy, and is both necessary and sufficient for chemotaxis and invasion in 2-D and 3-D assays. Growth factors, often described as tumour attractants, cause negligible chemotaxis themselves, but potentiate chemotaxis to LPA. Cells rapidly break down LPA present at substantial levels in culture medium and normal skin to generate outward-facing gradients. We measure LPA gradients across the margins of melanomas in vivo, confirming the physiological importance of our results. We conclude that LPA chemotaxis provides a strong drive for melanoma cells to invade outwards. Cells create their own gradients by acting as a sink, breaking down locally present LPA, and thus forming a gradient that is low in the tumour and high in the surrounding areas. The key step is not acquisition of sensitivity to the chemoattractant, but rather the tumour growing to break down enough LPA to form a gradient. Thus the stimulus that drives cell dispersal is not the presence of LPA itself, but the self-generated, outward-directed gradient

Missing Data in Randomized Clinical Trials for Weight Loss: Scope of the Problem, State of the Field, and Performance of Statistical Methods

BACKGROUND: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive. CONCLUSION/SIGNIFICANCE: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis