29 research outputs found
Author response: Early hemodynamic predictors of good outcome and reperfusion injury after endovascular treatment
No full textSeasonality in cholera dynamics: A rainfall-driven model explains the wide range of patterns in endemic areas
No full textSeasonal patterns in cholera dynamics exhibit pronounced variability across geographical regions, showing single or multiple peaks at different times of the year. Although multiple hypotheses related to local climate variables have been proposed, an understanding of this seasonal variation remains incomplete. The historical Bengal region, which encompasses the full range of cholera’s seasonality observed worldwide, provides a unique opportunity to gain insights on underlying environmental drivers. Here, we propose a mechanistic, rainfall-temperature driven, stochastic epidemiological model which explicitly accounts for the fluctuations of the aquatic reservoir, and analyze with this model the historical dataset of cholera mortality in the Bengal region. Parameters are inferred with a recently developed sequential Monte Carlo method for likelihood maximization in partially observed Markov processes. Results indicate that the hydrological regime is a major driver of the seasonal dynamics of cholera. Rainfall tends to buffer the propagation of the disease in wet regions due to the longer residence times of water in the environment and an associated dilution effect, whereas it enhances cholera resurgence in dry regions. Moreover, the dynamics of the environmental water reservoir determine whether the seasonality is unimodal or bimodal, as well as its phase relative to the monsoon. Thus, the full range of seasonal patterns can be explained based solely on the local variation of rainfall and temperature. Given the close connection between cholera seasonality and environmental conditions, a deeper understanding of the underlying mechanisms would allow the better management and planning of public health policies with respect to climate variability and climate change
Human papillomavirus in cervical adenocarcinoma. An in situ hybridization study.
No full textTwenty cervical adenocarcinomas (CACs) in women aged 22 to 71 were investigated by in situ hybridization (ISH) with 6, 11, 16, 18, 31, 35 and 51 HPV biotinylated probes. Two cases, one adenocarcinoma and one adenosquamous carcinoma (in women aged 28 and 40 respectively) showed focal nuclear positivity to 16 HPV Probe in some neoplastic glands. We used ISH, rather than other hybridization techniques, in order to exclude a positivity to viral DNA, due to adjacent squamous epithelium, either normal or metaplastic, and in squamous foci within adenosquamous tumors. Reviewing the literature, we found 33 out of 98 CACs positive to viral DNA by ISH (33.6%). In spite of the differences found from author to author, a relationship between adenocarcinomas of the uterine cervix and HPV infection seems to be possible, as was demonstrated for CIN and invasive cervical carcinomas. These data could explain why the incidence of this neoplasia has tended to increase over the last few years, mainly in younger patients
Integrating Information Sources for Inland Waters - A New Global Framework for Lakes Modelling and Monitoring
No full textLike islands, lakes are not only unique geographical features, but also ecological concepts on their own. Their exceptional variability has been studied numerous times, yet no unique framework capable of reproducing the wide range of lake dynamics observed in various regions of the World has been formulated. Increasingly facing external pressures, inland waters adaptation and changes have to be understood and monitored efficiently in order to provide timely, scientifically credible, and policy-relevant environmental information, to ultimately assist stakeholders in evidence-based decision-making and sustainable management. Such monitoring capabilities are of great importance for the management and surveillance of the necessary measures to prevent lakes deterioration, as stated by the EU Water Framework Directive, or the United Nations’ Post 2015 agenda. Those are only two among the numerous recent political actions aiming at sustainably securing the ecosystem services provided by lakes on a regional to global scale, using new approaches for water management tailored to local conditions. Over the last decades, various research communities addressed this problem using different information sources, such as in-situ measurements, remote sensing observations and mathematical models. The challenge of this thesis is to couple those information sources through adapted data assimilation algorithms. The coupling of those three data sources aims at providing a new, reliable, flexible, and global modelling framework for inland waters monitoring across Switzerland, Europe and possibly expanding to other lakes of the World. The development of this framework will consider both hydrodynamic and water quality models with one- and three-dimensional domains. Year-long in-situ campaigns will complement existing field data, including setups on permanent stations. Remote sensing products consist in the approved AVHRR surface temperature dataset and cutting-edge Sentinel-2 chlorophyll observations. In terms of system operations, the framework will be operated in real-time for several Swiss lakes, with short-term forecasting of hydrodynamic and water quality properties, available online, and open to the public. The impacts of such system are expected at public, governmental and scientific levels. For the latter, this project aims at contributing to advances in aquatic research by (i) identifying and studying mesoscale processes such as up- downwellings, horizontal distribution of ecological properties, and (ii) assessing the variability of lake responses to climate change, in terms of warming and ice cover.APHY
Seasonality in cholera dynamics : A rainfall-driven model explains the wide range of patterns of an infectious disease in endemic areas
No full textAn explanation for the spatial variability of seasonal cholera patterns has remained an unresolved problem in tropical medicine. No simple and unified theory based on local climate variables has been formulated, leaving our understanding of seasonal variations of cholera outbreaks in different regions of the world incomplete. A mechanistic model for the Bengal region, which encompasses the variety of seasonal patterns worldwide, may provide a unique opportunity to gain insights on the conditions and factors responsible for endemicity around the globe, and therefore, to also revise our understanding of the ecology of Vibrio cholerae. Through the analysis of a unique historical dataset, we propose the first mechanistic, rainfall-driven, SIR-based stochastic model we are aware of for the population dynamics of cholera, capable of capturing the full range of seasonal patterns in this large estuarine region. Parameter inference was implemented via new statistical methods that allow the computation of maximum-likelihood estimates for partially observed Markov processes through sequential Monte-Carlo. The results indicate that the hydrological regime is a decisive driver determining the seasonal dynamics of cholera. It was found that rainfall and longer water residence times tend to buffer the propagation of the disease in wet regions due to a dilution effect, while also enhancing cholera incidence in dry regions. This indicates that overall water levels matter and appear to determine whether the seasonality is unimodal or bimodal, as well as whether it is pre-, post-, or in-phase with the monsoon. We present evidence that the environmental reservoir is responsible for the persistence of the disease, and therefore its endemicity. Given the undeniable interplay between the seasonality of cholera and the environment, a deeper understanding of the underlying mechanisms could allow for the better management and planning of public health policies with respect to climate. In terms of disease prevention and mitigation strategies this is of paramount importance today, as changes in the population dynamics of infectious diseases are expected in response to fast anthropogenic climate change.ECHOSIE-S
Hydrologic data assimilation for an operational flood forecasting & monitoring system
No full textSIE-SPL-LC
From observations to 3D forecasts: Data assimilation for high resolution lakes monitoring
No full textLake mesoscale processes have no secrets for artists, they have some for scientists and policy-makers. In the introduction to this dissertation, we saw that poets and painters depict the lake with rich variability. This vision conflicts with conventional approaches inferring the lake's bio-physical status from a few in-situ measurements with limited spatio-temporal coverage. Yet it reflects upon true physical processes, capable of disrupting the misleading lentic nature of lakes, the essential ecosystem services they provide, and even citizens' safety. Recent overarching policies now aim at securing those services, using novel approaches like numerical simulations and remote sensing observations. Harnessing the potentiality of in-situ, remote sensing data and model simulations, this thesis developed an end-to-end framework delivering reliable synoptic lake information, at high spatial and temporal resolution.
In lakes, three-dimensional hydrodynamic models are the only information source capable of resolving transport and mixing, and forecasting their dynamics. However, they still rely on large observational datasets for their complex parameterizations and for constraining their uncertainties. This thesis addressed such challenges by (i) implementing an automated model calibration framework alleviating the need for expert knowledge, and by (ii) developing a data assimilative scheme capable of reducing and quantifying model uncertainties by incorporating satellite and in-situ data. Both yielded remarkable results: the former returned parametric values diminishing models Root Mean Square Error by up to 47 %, while the latter cut it further down by 54 %. Furthermore, the data assimilation enhanced the spatial coherence and magnitude of imperfectly resolved physical processes, and provided system uncertainties. Finally, this thesis delivered a practical outcome of its findings by developing an online pre-operational three-dimensional lake monitoring and forecasting system: meteolakes.ch. For two years, Meteolakes has been disseminating spatially explicit real-time lake information and data products to more than hundred thousand end-users. This pioneering platform has been featured in numerous media (newspapers, radio, television), public events, museum exhibitions, and benefited scientific, lake professionals, and public communities. A pinnacle of this research has been its early-warning and forecasting capabilities, which anticipated numerous mesoscale physical phenomena in Lake Geneva, such as upwellings, gyres, and strong currents. Two of those events, which impacted public and commercial activities, are illustrated in this dissertation. From observations and models to societal benefit, we created here a long value chain for water management.
At the crossroads of scientific, computational and observational advances, this research paves the route for understanding lakes' delicate imbalance. By producing data society can use, it opens novel frontiers for interdisciplinary research on previously elusive lake physical processes, and their implications on the everyday life of people.APHY
Meteolakes: An operational online three-dimensional forecasting platform for lake hydrodynamics
No full textEnvironmental management depends on high-quality monitoring and its meaningful interpretation. The combination of local weather dynamics, regional anthropogenic stresses and global environmental changes make the evaluation of monitoring information in dynamic freshwater systems a challenging task. While the lake ecosystems gather many complex biogeochemical interactions, they remain constrained by the same physical environment of mixing and transport. It is therefore crucial to obtain high quality physical system insight. Three-dimensional hydrodynamic models are perfectly suited for providing such information. However, these models are complex to implement, and their use is often limited to modellers. Here, we aim to provide model output via a user-friendly platform to a broad audience ranging from scientists to public and governmental stakeholders.We present a unified approach merging the apparently diverse interests through meteolakes.ch, an online platform openly disseminating lake observations and three-dimensional numerical simulations in near real-time with short-term forecasts and data assimilation. Meteolakes is scalable to a broad range of devices, modular and distributed, hence allowing its expansion to other regions and hardware infrastructures. Since 2016, the platform has continuously provided timely synoptic lake information to more than 250,000 users. This web-based system was built not only to provide guidance to scientists in the design and analysis of field experiments and to foster interdisciplinary lake studies, but also to assist governmental agencies and professionals in the long-term policy and planning of water resources management. Finally, our system aimed at promoting awareness and understanding of the complexity of lakes and providing information to the public through user-friendly, interfaces. This article details the design and operation of such a platform and its products. Applications are demonstrated by examples of a recent upwelling and a storm event. Both cases illustrate how Meteolakes help scientists in their quest for process understanding as well as water professionals and civil society in providing specific warnings. (C) 2020 The Authors. Published by Elsevier Ltd.APHY
Le Lac de Zurich en Ligne - Prévisions hydrodynamiques 3D en temps-réel sur meteolakes.ch. Aqua & Gas - Fachzeitschrift für Gas, Wasser und Abwasser
No full textLes lacs constituent d’importantes ressources en eau potable en Suisse, château d’eau de l’Europe. Pourtant, ils sont souvent négligés dans le cycle hydrologique global. Menacés à la fois à l’échelle globale par les changements climatiques, ainsi qu’à l’échelle locale par divers facteurs anthropogéniques (e. g. déversement de polluants, engrais, pollution thermique, etc.), la réaction de ces écosystèmes doit être comprise et anticipée afin de sécuriser durablement les services écosystémiques essentiels qu’ils fournissent (e. g. captage d’eau potable, pêche, sources/ puits de chaleur [1]). De telles capacités prédictives et de surveillance peuvent uniquement être acquises par l’utilisation de modèles hydrodynamique tridimensionnels exploités en temps réel.APHY
Coupling Inland Water Remote Sensing, In situ Data and Models
No full textCoupling Inland Water Remote Sensing, In situ Data and ModelsAPHY
