Évaluation de l'influence de la variabilité naturelle du climat et des changements climatiques anthropiques sur les extrêmes hydrométéorologiques

La capacité maximale des infrastructures d’eaux est conçue à partir des séries historiques d’extrêmes hydrométéorologiques et sur l’hypothèse que le climat est stationnaire. Toutefois, le consensus scientifique pointe vers un réchauffement planétaire causé par l’influence humaine, ayant des répercussions à long terme sur les précipitations et les crues extrêmes. De plus, plusieurs travaux récents indiquent que la variabilité naturelle du climat a le potentiel de masquer les effets de ces changements climatiques anthropiques, donnant une illusion de stationnarité du climat. Ainsi, l’objectif de cette thèse a pour but d’améliorer la compréhension des impacts de cette variabilité naturelle et des changements climatiques sur les extrêmes hydrométéorologiques. Dans un premier lieu, la variabilité naturelle a été explorée à travers six indices climatiques importants (p. ex. : El Niño) influençant le climat en Amérique du Nord. Bien que ceux-ci aient démontré un certain potentiel de prédiction au niveau de la variabilité saisonnière des moyennes de températures et de précipitations, ils se sont trouvés beaucoup moins prometteurs au niveau de la variabilité des extrêmes hydrométéorologiques. La combinaison de ces indices climatiques n’a résulté qu’en une faible valeur prédictive de la variabilité des crues et précipitations extrêmes. Dans un second lieu, la variabilité naturelle des précipitations moyennes et extrêmes a été examinée à l’aide de grands ensembles de simulations climatiques. Ces travaux ont permis de dresser un portait plus clair de son influence sur la détection du signal des changements climatiques. À l’échelle locale (p. ex. : une station météorologique), la variabilité naturelle dominera vraisemblablement le signal des changements climatiques des precipitations extrêmes jusqu’à la fin du 21e siècle. Toutefois, à l’échelle régionale (p. ex. : plusieurs stations météorologiques), la détection du signal des changements climatiques serait plus rapide et robuste. Globalement, la variabilité naturelle a la capacité d’entraver la detection des changements climatiques sur les précipitations moyennes et extrêmes jusqu’à la moitié, voire même la fin du siècle, pour plusieurs régions de la planète. Les grands ensembles de simulations climatiques ont aussi été utilisés pour évaluer l’impact des changements climatiques sur la probabilité de récurrence des événements hydrométéorologiques extrêmes. D’abord, les changements projetés pour la pluie 100 ans d’une durée d’une heure jusqu’à cinq jours entre les périodes de 1980-1999 et 2080-2099 ont été étudiés à l’aide de deux ensembles à l’échelle globale et un ensemble à l’échelle régionale couvrant le nord-est de l’Amérique du Nord et l’Europe. Les résultats des trois ensembles suggèrent que les événements de précipitation extrêmes, correspondant à la période de retour 100 ans de la période de référence, deviendront environ de quatre à cinq (deux à quatre) fois plus fréquents en moyenne pour le nord-est de l’Amérique du Nord (l’Europe). De plus, les résultats suggèrent qu’en général, une période de retour plus élevée et/ou une durée plus courte entraineront des augmentations relatives plus importantes. Ensuite, les changements projetés dans les crues extrêmes ont été investigués plus spécifiquement pour 3 567 bassins versants de grande taille (> 500 km2) en Amérique du Nord. Les résultats suggèrent des patrons spatiaux très distincts en termes d’augmentation et de diminution de la crue 100 ans. Les changements les plus importants se résument en une diminution des crues générées par la fonte de la neige dans les bassins versants situés en haute latitude et/ou haute altitude et une augmentation pour les bassins versants situés dans le sud-est des États-Unis et sur la côte ouest, où les précipitations sont la principale cause des crues. Finalement, des pistes de stratégies d’adaptation face aux changements climatiques ont été discutées à la suite de ces travaux. Ces dernières, de concert avec les conclusions de cette thèse, pourraient aider davantage les ingénieurs et les preneurs de décision à justifier l’implémentation de mesures d’adaptation permettant de mieux protéger le milieu bâti et les populations vulnérables

MAT-701: PREDICTING THE COMPRESSIVE STRENGTH OF ULTRA-LIGHTWEIGHT CONCRETE BY AN ARTIFICIAL NEURAL NETWORK

Ultra-lightweight concrete (ULWC) has potential applications for floating structures and architectural elements because of its dry density coming in at under 1000 kg/m3. The objective was to develop an artificial neural network (ANN) to aid the ULWC designer according to his needs. Boundary conditions were set for each material and 13 constraints based on the water binder ratio, density, air content, binder and aggregate content. The ANN predicted the compressive strength with a comfortable margin of error, with the gap encountered being attributed to variability in workability. Precise constraints and boundary conditions are needed to ensure a lower variability in workability. The ANN, coupled with a genetic algorithm, can generate millions of mixes for a given compressive strength in a short amount of time. The designer is able to choose mixes according to additional needs, such as the carbon footprint, absolute density, polymer content, cost, etc

Drug-protein binding: a critical review of analytical tools

The extent of drug binding to plasma proteins, determined by measuring the free active fraction, has a significant effect on the pharmacokinetics and pharmacodynamics of a drug. It is therefore highly important to estimate drug-binding ability to these macromolecules in the early stages of drug discovery and in clinical practice. Traditionally, equilibrium dialysis is used, and is presented as the reference method, but it suffers from many drawbacks. In an attempt to circumvent these, a vast array of different methods has been developed. This review focuses on the most important approaches used to characterize drug-protein binding. A description of the principle of each method with its inherent strengths and weaknesses is outlined. The binding affinity ranges, information accessibility, material consumption, and throughput are compared for each method. Finally, a discussion is included to help users choose the most suitable approach from among the wealth of methods presented. Figure Range of binding constants (log Ka) assessable by the main separative and non-separative analytical tools used to characterize drug-protein interactions. ED: equilibrium dialysis, UF: ultrafiltration, PAMPA: parallel artificial membrane permeability assay, HPAC/ZE: high-performance affinity chromatography/zonal elution approach, HPAC/FA: high-performance affinity chromatography/frontal analysis approach, ACE: affinity capillary electrophoresis (mobility shift assay), CE/FA: capillary electrophoresis/frontal analysis, Spectro.: spectroscopic assays, ITC: isothermal titration calorimetry, comp.: competition studies, titration: titration studies, DSC: differential scanning calorimetry, SPR: surface plasmon resonance-based assay

Large scale composting model

One way to treat the organic wastes accordingly to the environmental policies is to develop biological treatment like composting. Nevertheless, this development largely relies on the quality of the final product and as a consequence on the quality of the biological activity during the treatment. Favourable conditions (oxygen concentration, temperature and moisture content) in the waste bed largely contribute to the establishment of a good aerobic biological activity and guarantee the organic matter stabilisation with limitation and control of odorous and greenhouse effect gaseous emissions. Several approaches (0D biochemical reducing, see Pommier et al. 2007, effective 1D modelling coupling transport and biochemical) have been made to understand the behaviour of such systems. In this paper we will present a 2D numerical model using Darcy scale equations for heat and mass transport coupled with a biochemical reactive scheme. Then, we will solve that system (using experimental measurements on reactivity and transport coefficients) with a commercial code (COMSOL TM). The model described here is based on the biological model presented in Trémier et al 2005 coupled with an upscale transport model detailed in Hénon 2008 which takes into account the major components of the gas phase: N₂, O₂, CO₂ and also H₂O. This is a crucial point because of: - The reaction rate, depending on the moisture content (humidity comes from the initial condition of the sludge but also from the reactive scheme because reactions produce water), - heat content, very sensitive to the evaporation rate in the sludge. It has been shown in Pujol et al 2011 that the impact of drying could be important on the reactivity but also that the pseudo component air could not be sufficient to represent the drying in the sludge. The process studied was a closed reactor composting process (180 m³ rectangular box) with positive forced aeration. The air was blown from the bottom of the reactor, via two ventilation pipes. In the upper part of the reactor, air was sucked and led to a biofilter treatment system. The treated waste was a mixture of sewage sludge and bulking agent that was composted during four weeks without turning. Several informations were recorded during the treatment like temperature evolutions at different locations (see Henon et al. 2009 for more details about the temperature recording). We have validated this code by comparing the temperatures obtained through the simulations with those recorded during the experiments. After this step of validation and a discussion on final composition of the organic matter in the experiments compared to the ones estimated by simulations, we have used this numerical model as an optimization tool. Modifying the initial, boundary and operating conditions we have been able to determine the best conditions to this particular composting process. A whole set of conditions is discussed in the paper

Fast log P determination by ultra-high-pressure liquid chromatography coupled with UV and mass spectrometry detections

Ultra-high-pressure liquid chromatography (UHPLC) systems able to work with columns packed with sub-2μm particles offer very fast methods to determine the lipophilicity of new chemical entities. The careful development of the most suitable experimental conditions presented here will help medicinal chemists for high-throughput screening (HTS) log P oct measurements. The approach was optimized using a well-balanced set of 38 model compounds and a series of 28 basic compounds such as β-blockers, local anesthetics, piperazines, clonidine, and derivatives. Different organic modifiers and hybrid stationary phases packed with 1.7-μm particles were evaluated in isocratic as well as gradient modes, and the advantages and limitations of tested conditions pointed out. The UHPLC approach offered a significant enhancement over the classical HPLC methods, by a factor 50 in the lipophilicity determination throughput. The hyphenation of UHPLC with MS detection allowed a further increase in the throughput. Data and results reported herein prove that the UHPLC-MS method can represent a progress in the HTS-measurement of lipophilicity due to its speed (at least a factor of 500 with respect to HPLC approaches) and to an extended field of application. Figure The UHPLC approach described here greatly enhanced the time required for log P determination (5' min by compound using UV detection) and, at least, 8 compounds measured in a 5' run when Mass Spectrometry detection in used. These developments offer to medicinal chemists a high-throughput method to estimate the lipophilicity of NCE

Analytical tools for the physicochemical profiling of drug candidates to predict absorption/distribution

The measurement of physicochemical properties at an early phase of drug discovery and development is crucial to reduce attrition rates due to poor biopharmaceutical properties. Among these properties, ionization, lipophilicity, solubility and permeability are mandatory to predict the pharmacokinetic behavior of NCEs (new chemical entities). Due to the high number of NCEs, the analytical tools used to measure these properties are automated and progressively adapted to high-throughput technologies. The present review is dedicated to experimental methods applied in the early drug discovery process for the determination of solubility, ionization constants, lipophilicity and permeability of small molecules. The principles and experimental conditions of the different methods are described, and important enhancements in terms of throughput are highlighted. Figure Scheme of the Drug Research Proces

Guide de lutilisation pédagogique des médias sociaux

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A dualistic model of primary anal canal adenocarcinoma with distinct cellular origins, etiologies, inflammatory microenvironments and mutational signatures: implications for personalised medicine.

Primary adenocarcinoma of the anal canal is a rare and aggressive gastrointestinal disease with unclear pathogenesis. Because of its rarity, no clear clinical practice guideline has been defined and a targeted therapeutic armamentarium has yet to be developed. The present article aimed at addressing this information gap by in-depth characterising the anal glandular neoplasms at the histologic, immunologic, genomic and epidemiologic levels. In this multi-institutional study, we first examined the histological features displayed by each collected tumour (n = 74) and analysed their etiological relationship with human papillomavirus (HPV) infection. The intratumoural immune cell subsets (CD4, CD8, Foxp3), the expression of immune checkpoints (PD-1, PD-L1), the defect in mismatch repair proteins and the mutation analysis of multiple clinically relevant genes in the gastrointestinal cancer setting were also determined. Finally, the prognostic significance of each clinicopathological variable was assessed. Phenotypic analysis revealed two region-specific subtypes of anal canal adenocarcinoma. The significant differences in the HPV status, density of tumour-infiltrating lymphocytes, expression of immune checkpoints and mutational profile of several targetable genes further supported the separation of these latter neoplasms into two distinct entities. Importantly, anal gland/transitional-type cancers, which poorly respond to standard treatments, displayed less mutations in downstream effectors of the EGFR signalling pathway (i.e., KRAS and NRAS) and demonstrated a significantly higher expression of the immune inhibitory ligand-receptor pair PD-1/PD-L1 compared to their counterparts arising from the colorectal mucosa. Taken together, the findings reported in the present article reveal, for the first time, that glandular neoplasms of the anal canal arise by HPV-dependent or independent pathways. These etiological differences leads to both individual immune profiles and mutational landscapes that can be targeted for therapeutic benefits