Les traumatismes vertebro-medullaires par chute de la hauteur d’un arbre a propos de 73 cas au Mali.

Introduction Les chutes du haut d’un arbre sont des accidents graves et fréquents au MALI.Objectif Analysez les facteurs épidémiologiques, étiologiques et circonstanciels des chutes de la hauteur des arbres Matériels et méthodes Il s’agit d’une étude prospective continue d’octobre 2007 à septembre 2009 à l’hôpital Gabriel Touré de Bamako (Mali). Elle a concerné tous les cas de chute du haut d’un arbre pendant cette période.Résultats Au cours de cette étude, nous avons recensé 73 patients dont les âges étaient compris entre 5 et 65 ans. Les couches socioprofessionnelles les plus atteintes ont été les cultivateurs et les bergers aux conditions socioéconomiques défavorables. Pendant les mois de décembre à mai 79,45% (58 patients) des patients ont été enregistrés. Cette période correspondait à la traite des fruits et à la saison sèche avec le manque de pâturages pour les animaux. L’intervention chirurgicale a concerné 32 patients. La mortalité a été de 12,32% (9 patients) tous traumatisés cervicaux.Conclusions Les accidents par chutes d’arbres sont en rapport avec les conditions socio-économiques et climatiques au Mali.Mots clés : Arbre, Accident, Chute, Mali, Rachis, Traumatism

Fitting the Gamma-Ray Spectrum from Dark Matter with DMFIT: GLAST and the Galactic Center Region

We study the potential of GLAST to unveil particle dark matter properties with gamma-ray observations of the Galactic center region. We present full GLAST simulations including all gamma-ray sources known to date in a region of 4 degrees around the Galactic center, in addition to the diffuse gamma-ray background and to the dark matter signal. We introduce DMFIT, a tool that allows one to fit gamma-ray emission from pair-annihilation of generic particle dark matter models and to extract information on the mass, normalization and annihilation branching ratios into Standard Model final states. We assess the impact and systematic effects of background modeling and theoretical priors on the reconstruction of dark matter particle properties. Our detailed simulations demonstrate that for some well motivated supersymmetric dark matter setups with one year of GLAST data it will be possible not only to significantly detect a dark matter signal over background, but also to estimate the dark matter mass and its dominant pair-annihilation mode.Comment: 37 pages, 16 figures, submitted to JCA

Direct versus indirect detection in mSUGRA with self-consistent halo models

We perform a detailed analysis of the detection prospects of neutralino dark matter in the mSUGRA framework. We focus on models with a thermal relic density, estimated with high accuracy using the DarkSUSY package, in the range favored by current precision cosmological measurements. Direct and indirect detection rates are computed implementing two models for the dark matter halo, tracing opposite regimes for the phase of baryon infall, with fully consistent density profiles and velocity distribution functions. This has allowed, for the first time, a fully consistent comparison between direct and indirect detection prospects. We discuss all relevant regimes in the mSUGRA parameter space, underlining relevant effects, and providing the basis for extending the discussion to alternative frameworks. In general, we find that direct detection and searches for antideuterons in the cosmic rays seems to be the most promising ways to search for neutralinos in these scenarios.Comment: 26 pages, 9 figure

Knowledge of dental academics about the COVID-19 pandemic: a multi-country online survey.

BACKGROUND: COVID-19 is a global pandemic affecting all aspects of life in all countries. We assessed COVID-19 knowledge and associated factors among dental academics in 26 countries. METHODS: We invited dental academics to participate in a cross-sectional, multi-country, online survey from March to April 2020. The survey collected data on knowledge of COVID-19 regarding the mode of transmission, symptoms, diagnosis, treatment, protection, and dental treatment precautions as well as participants' background variables. Multilevel linear models were used to assess the association between dental academics' knowledge of COVID-19 and individual level (personal and professional) and country-level (number of COVID-19 cases/ million population) factors accounting for random variation among countries. RESULTS: Two thousand forty-five academics participated in the survey (response rate 14.3%, with 54.7% female and 67% younger than 46 years of age). The mean (SD) knowledge percent score was 73.2 (11.2) %, and the score of knowledge of symptoms was significantly lower than the score of knowledge of diagnostic methods (53.1 and 85.4%, P <  0.0001). Knowledge score was significantly higher among those living with a partner/spouse than among those living alone (regression coefficient (B) = 0.48); higher among those with PhD degrees than among those with Bachelor of Dental Science degrees (B = 0.48); higher among those seeing 21 to 30 patients daily than among those seeing no patients (B = 0.65); and higher among those from countries with a higher number of COVID-19 cases/million population (B = 0.0007). CONCLUSIONS: Dental academics had poorer knowledge of COVID-19 symptoms than of COVID-19 diagnostic methods. Living arrangements, academic degrees, patient load, and magnitude of the epidemic in the country were associated with COVD-19 knowledge among dental academics. Training of dental academics on COVID-19 can be designed using these findings to recruit those with the greatest need

Knowledge of dental academics about the COVID-19 pandemic: a multi-country online survey

Background: COVID-19 is a global pandemic affecting all aspects of life in all countries. We assessed COVID-19 knowledge and associated factors among dental academics in 26 countries. Methods: We invited dental academics to participate in a cross-sectional, multi-country, online survey from March to April 2020. The survey collected data on knowledge of COVID-19 regarding the mode of transmission, symptoms, diagnosis, treatment, protection, and dental treatment precautions as well as participants’ background variables. Multilevel linear models were used to assess the association between dental academics’ knowledge of COVID-19 and individual level (personal and professional) and country-level (number of COVID-19 cases/ million population) factors accounting for random variation among countries. Results: Two thousand forty-five academics participated in the survey (response rate 14.3%, with 54.7% female and 67% younger than 46 years of age). The mean (SD) knowledge percent score was 73.2 (11.2) %, and the score of knowledge of symptoms was significantly lower than the score of knowledge of diagnostic methods (53.1 and 85.4%, P &lt; 0.0001). Knowledge score was significantly higher among those living with a partner/spouse than among those living alone (regression coefficient (B) = 0.48); higher among those with PhD degrees than among those with Bachelor of Dental Science degrees (B = 0.48); higher among those seeing 21 to 30 patients daily than among those seeing no patients (B = 0.65); and higher among those from countries with a higher number of COVID-19 cases/million population (B = 0.0007). Conclusions: Dental academics had poorer knowledge of COVID-19 symptoms than of COVID-19 diagnostic methods. Living arrangements, academic degrees, patient load, and magnitude of the epidemic in the country were associated with COVD-19 knowledge among dental academics. Training of dental academics on COVID-19 can be designed using these findings to recruit those with the greatest need

Perceived preparedness of dental academic institutions to cope with the COVID-19 pandemic: a multi-country survey

Dental academic institutions are affected by COVID-19. We assessed the perceived COVID19 preparedness of these institutions and the characteristics of institutions with greater perceived preparedness. An international cross-sectional survey of dental academics was conducted from March to August 2020 to assess academics’ and institutional attributes, perceived preparedness, and availability of infection prevention and control (IPC) equipment. Principal component analysis (PCA) identified perceived preparedness components. Multilevel linear regression analysis assessed the association between perceived preparedness and fixed effect factors (academics’ and institutions’ attributes) with countries as random effect variable. Of the 1820 dental academics from 28 countries, 78.4% worked in public institutions and 75.2% reported temporary closure. PCA showed five components: clinic apparel, measures before and after patient care, institutional policies, and availability of IPC equipment. Significantly less perceived preparedness was reported in lower-middle income (LMICs) (B = −1.31, p = 0.006) and upper-middle income (UMICs) (B = −0.98, p = 0.02) countries than in high-income countries (HICs), in teaching only (B = −0.55, p &lt; 0.0001) and in research only (B = −1.22, p = 0.003) than teaching and research institutions and in institutions receiving ≤100 patients daily than those receiving &gt;100 patients (B = −0.38, p &lt; 0.0001). More perceived preparedness was reported by academics with administrative roles (B = 0.59, p &lt; 0.0001). Academics from low-income countries (LICs) and LMICs reported less availability of clinic apparel, IPC equipment, measures before patient care, and institutional policies but more measures during patient care. There was greater perceived preparedness in HICs and institutions with greater involvement in teaching, research, and patient care

Analyzing and Biasing Simulations with PLUMED

This chapter discusses how the PLUMED plugin for molecular dynamics can be used to analyze and bias molecular dynamics trajectories. The chapter begins by introducing the notion of a collective variable and by then explaining how the free energy can be computed as a function of one or more collective variables. A number of practical issues mostly around periodic boundary conditions that arise when these types of calculations are performed using PLUMED are then discussed. Later parts of the chapter discuss how PLUMED can be used to perform enhanced sampling simulations that introduce simulation biases or multiple replicas of the system and Monte Carlo exchanges between these replicas. This section is then followed by a discussion on how free-energy surfaces and associated error bars can be extracted from such simulations by using weighted histogram and block averaging techniques

Using metadynamics to explore complex free-energy landscapes

Metadynamics is an atomistic simulation technique that allows, within the same framework, acceleration of rare events and estimation of the free energy of complex molecular systems. It is based on iteratively \u2018filling\u2019 the potential energy of the system by a sum of Gaussians centred along the trajectory followed by a suitably chosen set of collective variables (CVs), thereby forcing the system to migrate from one minimum to the next. The power of metadynamics is demonstrated by the large number of extensions and variants that have been developed. The first scope of this Technical Review is to present a critical comparison of these variants, discussing their advantages and disadvantages. The effectiveness of metadynamics, and that of the numerous alternative methods, is strongly influenced by the choice of the CVs. If an important variable is neglected, the resulting estimate of the free energy is unreliable, and predicted transition mechanisms may be qualitatively wrong. The second scope of this Technical Review is to discuss how the CVs should be selected, how to verify whether the chosen CVs are sufficient or redundant, and how to iteratively improve the CVs using machine learning approaches