Intérêt économique et sur l’exposition aux antibiotiques de la gestion de la cétose subclinique et du traitement préventif Kexxtone©

La cétose subclinique est une pathologie dominante des vaches laitières en début de lactation. Elle est associée à une augmentation de la majorité des troubles sanitaires de la vache en peripartum et à une baisse des performances. Kexxtone© est un bolus intra-ruminal de monensin à administrer 3 semaines avant vêlage sur les vaches à risque de cétose subclinique. Il permet réduire le risque de cétose subclinique. Cette étude vise à objectiver l’intérêt économique du traitement Kexxtone© et son impact sur la consommation d’antibiotiques. Une modélisation stochastique a été développée sous Scilab, avec 10 000 itérations par cas, et une centaine de scénarios différents. Un traitement préventif avec Kexxtone© est économiquement intéressant lorsque l’éleveur cible correctement les vaches à traiter. Il augmente systématiquement l’exposition aux antibiotiques totaux mais diminue l’exposition aux antibiotiques curatifs, dont les antibiotiques critiques. Il permet de stabiliser l’utilisation d’antibiotiques critiques lorsque la prévalence de vaches à risque de cétose augmente dans un troupeau

Manipulating the ferroelectric polarization state of BaTiO 3 thin films

International audienceControlling the ferroelectric polarization at macroscopic or microscopic levels is crucial in the framework of the development of ferroelectric materials used in yet challenging photo-electrochemical (PEC) cells and spintronic applications. We report here on polarization methods allowing to electrically polarize prototypical samples of BaTiO 3 (001) films. Epitaxial single crystalline layers were grown up to a thickness of 25 nm by atomic oxygen assisted molecular beam epitaxy on 1 at.% Nb doped SrTiO 3 (001) single crystals. The samples were both microscopically and macroscopically polarized using Piezoresponse Force Microscopy and electrochemical poling in an electrolyte respectively. In addition we demonstrate the possibility to retrieve a quasi-native mixed ferroelectric polarization state after annealing. These polarization methods may be applied to many other ferroelectric thin films

Local electronic structure and photoelectrochemical activity of partial chemically etched Ti-doped hematite

International audienceThe direct conversion of solar light into chemical energy or fuel through photoelectrochemical water splitting is promising as a clean hydrogen production solution. Ti-doped hematite (Ti:α-Fe 2 O 3) is a potential key photoanode material, which despite its optimal band gap, excellent chemical stability, abundance, non-toxicity and low cost, still has to be improved. Here we give evidence of a drastic improvement of the water splitting performances of Ti-doped hematite photoanodes upon a HCl wet-etching. In addition to the topography investigation by atomic force microscopy, a detailed determination of the local electronic structure has been carried out in order to understand the phenomenon and to provide new insights in the understanding of solar water splitting. Using synchrotron radiation based spectromicroscopy (X-PEEM), we investigated the X-ray absorption spectral features at the L 3 Fe edge of the as grown surface and of the wet-etched surface on the very same sample thanks to patterning. We show that HCl wet etching leads to substantial surface modifications of the oxide layer including increased roughness and chemical reduction (presence of Fe 2+) without changing the band gap. We demonstrate that these changes are profitable and correlated to the drastic changes of the photocatalytic activity

Complex systems in Ecology: a guided tour with large Lotka-Volterra models and random matrices

Ecosystems represent archetypal complex dynamical systems, often modelled by coupled differential equations of the form $$\frac{d x_i}{d t} = x_i \varphi_i(x_1,\cdots, x_N)\ ,$$ where $N$ represents the number of species and $x_i$, the abundance of species $i$. Among these families of coupled diffential equations, Lotka-Volterra (LV) equations $$\frac{d x_i}{d t} = x_i ( r_i - x_i +(\Gamma \mathbf{x})_i)\ ,$$ play a privileged role, as the LV model represents an acceptable trade-off between complexity and tractability. Here, $r_i$ represents the intrinsic growth of species $i$ and $\Gamma$ stands for the interaction matrix: $\Gamma_{ij}$ represents the effect of species $j$ over species $i$. For large $N$, estimating matrix $\Gamma$ is often an overwhelming task and an alternative is to draw $\Gamma$ at random, parametrizing its statistical distribution by a limited number of model features. Dealing with large random matrices, we naturally rely on Random Matrix Theory (RMT). The aim of this review article is to present an overview of the work at the junction of theoretical ecology and large random matrix theory. It is intended to an interdisciplinary audience spanning theoretical ecology, complex systems, statistical physics and mathematical biology

Closing a gap in tropical forest biomass estimation : taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees = 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot- level error (in %) from [-23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far- from- negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost

Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia

Bacterial factors favoring the unprecedented multidrug-resistant tuberculosis (MDR-TB) epidemic in the former Soviet Union remain unclear. We utilized whole genome sequencing and Bayesian statistics to analyze the evolutionary history, temporal emergence of resistance and transmission networks of MDR; Mycobacterium tuberculosis; complex isolates from Karakalpakstan, Uzbekistan (2001-2006). One clade (termed Central Asian outbreak, CAO) dating back to 1974 (95% HPD 1969-1982) subsequently acquired resistance mediating mutations to eight anti-TB drugs. Introduction of standardized WHO-endorsed directly observed treatment, short-course in Karakalpakstan in 1998 likely selected for CAO-strains, comprising 75% of sampled MDR-TB isolates in 2005/2006. CAO-isolates were also identified in a published cohort from Russia (2008-2010). Similarly, the presence of mutations supposed to compensate bacterial fitness deficits was associated with transmission success and higher drug resistance rates. The genetic make-up of these MDR-strains threatens the success of both empirical and standardized MDR-TB therapies, including the newly WHO-endorsed short MDR-TB regimen in Uzbekistan

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees  1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://www.biogeosciences.net

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570