Conception et validation d’un instrument de mesure de la colonne vertébrale en position assise et modélisation préliminaire du tronc pour la conception de dossiers

À ce jour, les dossiers de fauteuils, qu’ils soient de fauteuils roulants, de transports, d’automobiles ou de bureaux, sont limités à des séries génériques qui ne sont pas adaptées à tous les profils. Ils peuvent alors faire l’objet d’offres sur-mesure certes performantes, mais trop onéreuses pour la population. Dans d’autres domaines de pointe comme la course automobile ou l’aéronautique, les pilotes peuvent être soumis à des forces élevées au dos contre le dossier. Des produits ajustés aux besoins particuliers de ces activités sont pertinents. La conception sur-mesure peut être une solution pour répondre à ces attentes pour les milieux « classiques ». Cependant, elle reste coûteuse et donc moins accessible, et implique des méthodes plus contraignantes telles que le moulage ou l’utilisation de scanner 3D. Ainsi, il existe un besoin de développer une méthode de conception plus accessible grâce à des méthodes et outils de mesures innovants. La création d’un modèle géométrique paramétrable du dos à partir de mesures anthropométriques offrirait une assistance à la conception de dossier que l’on pourrait qualifier de semi-sur-mesure. Un tel modèle ajusté à chaque utilisateur permettrait de lui designer un dossier ajusté ou même lui prescrire un fauteuil approprié. Il est apparu, lors de la définition de la méthode de prise de mesures anthropométriques, qu’il est difficile de relever la courbure du dos d’une personne en position assise. Bien qu’il existe de nombreux outils pour mesurer ou caractériser la courbe de la colonne vertébrale, ceux-ci ne sont pas nécessairement utilisés sur une personne dans une bonne posture assise. Une nouvelle méthode ou un nouvel outil de mesure est nécessaire pour répondre à ce besoin. Ce projet porte donc sur la conception d’un outil de mesure et de positionnement de la colonne vertébrale en position assise. Pour répondre à cette problématique, le premier objectif de ce projet est la réalisation un nouvel outil de mesure : une chaise expérimentale pour installer l’utilisateur dans une bonne posture puis relever la courbure de sa colonne et mesurer son tronc. Le travail de validation de la chaise constitue la majeure partie de cette étude. Ainsi, la validation de la chaise de mesure réside dans sa capacité à positionner et à mesurer la courbe du dos. Notons que les besoins de positionnement varient en fonction du domaine d’étude des essais. La prise en compte de pathologies posturales et de personnes handicapées est écartée pour le moment et l’étude est effectuée sur des sujets sains, soit des membres de l’équipe de recherche, afin de valider la chaise et le modèle sur des cas simples. Enfin, ce projet apportera une avancée dans la modélisation du tronc, dans l’étude du positionnement assis et dans la conception des dossiers et des accessoires d’aides à la posture grâce à un protocole de prise de mesures anthropométriques simples et accessibles. Il permettra de répondre plus aisément aux besoins d’une plus grande population, et ce, dans de nombreux domaines d’application

Formation de NDMA par chloramination de micropolluants

International audienceL'utilisation des chloramines dans les procédés de production d'eau potable permet de limiter la formation de sous-produits de chloration tels que les trihalométhanes (THMs) et les acides haloacétiques (HAAs). Cependant, la chloramination entraîne la formation de N-nitrosamines, en particulier la N-nitrosodiméthylamine (NDMA), un sous-produit de désinfection non halogéné cancérigène pour l'homme. Les mécanismes de formation de la NDMA lors des traitements par chloramination ne sont que partiellement établis. L'étude montre que des composés azotés pouvant être rencontrés dans les eaux naturelles, par exemple des herbicides (diuron, isoproturon) ou des composés pharmaceutiques (ranitidine, mifépristone), peuvent être des précurseurs importants de NDMA. Il apparaît que les quantités importantes de NDMA formées à partir de ces composés (en particulier la ranitidine) ne peuvent pas être expliquées par les mécanismes de formation actuellement disponibles dans la littérature. De nouveaux mécanismes de formation impliquant les caractéristiques structurales des amines tertiaires doivent être envisagés

The importance of layout and configuration data for flexibility during commissionning and operation of the LHC machine protection systems

Due to the large stored energies in both magnets and particle beams, the Large Hadron Collider (LHC) requires a large inventory of machine protection systems, as e.g. powering interlock systems, based on a series of distributed industrial controllers for the protection of the more than 10'000 normal and superconducting magnets. Such systems are required to be at the same time fast, reliable and secure but also flexible and configurable to allow for automated commissioning, remote monitoring and optimization during later operation. Based on the generic hardware architecture of the LHC machine protection systems presented at EPAC 2002 [2] and ICALEPS 2003, the use of configuration data for protection systems in view of the required reliability and safety is discussed. To achieve the very high level of reliability, it is required to use a coherent description of the layout of the accelerator components and of the associated machine protection architecture and their logical interconnections. Mechanisms to guarantee coherency of data and repositories and secure configuration of safety critical systems are presented. This paper focuses on the first system being commissioned, the complex magnet powering system, to become fully operational before first injection of beam into the LHC

To Each Optimizer a Norm, To Each Norm its Generalization

We study the implicit regularization of optimization methods for linear models interpolating the training data in the under-parametrized and over-parametrized regimes. Since it is difficult to determine whether an optimizer converges to solutions that minimize a known norm, we flip the problem and investigate what is the corresponding norm minimized by an interpolating solution. Using this reasoning, we prove that for over-parameterized linear regression, projections onto linear spans can be used to move between different interpolating solutions. For under-parameterized linear classification, we prove that for any linear classifier separating the data, there exists a family of quadratic norms ||.||_P such that the classifier's direction is the same as that of the maximum P-margin solution. For linear classification, we argue that analyzing convergence to the standard maximum l2-margin is arbitrary and show that minimizing the norm induced by the data results in better generalization. Furthermore, for over-parameterized linear classification, projections onto the data-span enable us to use techniques from the under-parameterized setting. On the empirical side, we propose techniques to bias optimizers towards better generalizing solutions, improving their test performance. We validate our theoretical results via synthetic experiments, and use the neural tangent kernel to handle non-linear models

Identification of NF-κB Modulation Capabilities within Human Intestinal Commensal Bacteria

The intestinal microbiota plays an important role in modulation of mucosal immune responses. To seek interactions between intestinal epithelial cells (IEC) and commensal bacteria, we screened 49 commensal strains for their capacity to modulate NF-κB. We used HT-29/kb-seap-25 and Caco-2/kb-seap-7 intestinal epithelial cells and monocyte-like THP-1 blue reporter cells to measure effects of commensal bacteria on cellular expression of a reporter system for NF-κB. Bacteria conditioned media (CM) were tested alone or together with an activator of NF-κB to explore its inhibitory potentials. CM from 8 or 10 different commensal species activated NF-κB expression on HT-29 and Caco-2 cells, respectively. On THP-1, CM from all but 5 commensal strains stimulated NF-κB. Upon challenge with TNF-α or IL-1β, some CM prevented induced NF-κB activation, whereas others enhanced it. Interestingly, the enhancing effect of some CM was correlated with the presence of butyrate and propionate. Characterization of the effects of the identified bacteria and their implications in human health awaits further investigations

Projected impacts of climate change on viticulture over French wine regions using downscaled CMIP6 multi-model data

Climate change is a major challenge for the French wine industry. Climatic conditions in French vineyards have already changed and will continue to evolve impacting viticulture. This study aims to analyse the evolution of agro- and eco-climatic indices based on phenology simulation of French wine-growing regions. This evolution was analysed on a recent-past period (1962–1991 to 1992–2021) using SAFRAN climate data and on a future projected period (1985–2014 to 2041–2070) with two SSP trajectories (SSP2-4.5 and SSP5-8.5). A set of 19 CMIP6 climate models downscaled at 8 km grid resolution over France coupled with three phenological and a water balance model were used. Phenological model parameters and training system characteristics were adapted to each region to match as much as possible current practices. Temperatures during the growing season have increased by +1 °C to +2.1 °C since the second half of the 20th century and could rise to +3.7 °C in regions around the Mediterranean by 2070. The inter-model variance concerning the precipitation is high, a significant change (decrease) in precipitation during the grapevine growing season is observed only for the regions of western France (Oceanic climate) over the period 2040–2071 with the SSP5 trajectory. All simulated phenological stages have shifted toward earlier dates. Their occurrence should be even earlier by 2070 with an average advance of up to 22 days for the mid-veraison of Pinot noir in eastern France. The theoretical maturity date (sugar content) should also be advanced from 19 to 30 days depending on the considered region and SSP. Thermal conditions closer to the photosynthetic optimum should promote onset by the early second half of the 21st century. The increase in both the number of hot days and grapevine water deficit during the period of fruit development should impact grape production in quality and quantity in all wine-growing regions. Spring frost projections show no significant change in risk for the second half of the 21st century, compared to current conditions

Altered Humoral Immune Responses and IgG Subtypes in NOX2-Deficient Mice and Patients: A Key Role for NOX2 in Antigen-Presenting Cells

Chronic granulomatous disease (CGD) is a primary immunodeficiency resulting from loss of function mutations in the reactive oxygen species generating phagocyte NADPH oxidase (NOX2). CGD patients are prone to infection, but also have an increased susceptibility to autoimmune diseases. The aim of this study was to investigate the role of NOX2 in the regulation of specific immunity. In both CGD patients and NOX2-deficient mice, we observed an alteration in the basal proportions of IgG subtypes. Upon immunization with curdlan—a dectin 1 agonist—NOX2-deficient mice showed increased production of IgG2c compared to controls, and restimulation of lymph node-derived cells led to increased production of IFNγ, but not IL-5, indicative hallmark of an enhanced Th1 response. T cell activation was increased in NOX2-deficient mice and a similar trend was observed in vitro when T cells were co-cultured with NOX2-deficient bone marrow-derived cells. In contrast, no difference in T cell activation was observed when NOX2-deficient T cells were co-cultured with wild-type BMDC. Following stimulation of NOX2-deficient dendritic cells (DCs), no difference in costimulatory molecules was observed, while there was an increase in the release of Th1-driving cytokines. In summary, both CGD patients and CGD mice have an altered IgG subtype distribution, which is associated with an increased IFNγ production. Thus, NOX2 within DCs appears to be an important regulator at the interface of innate and specific immunity, especially after activation of the dectin 1 pathway, limiting immune activation and the development of autoimmunity

Absence of triadin, a protein of the calcium release complex, is responsible for cardiac arrhythmia with sudden death in human

Catecholaminergic polymorphic ventricular tachycardia (CPVT) is an inherited arrhythmogenic disease so far related to mutations in the cardiac ryanodine receptor (RYR2) or the cardiac calsequestrin (CASQ2) genes. Because mutations in RYR2 or in CASQ2 are not retrieved in all CPVT cases, we searched for mutations in the physiological protein partners of RyR2 and CSQ2 in a large cohort of CPVT patients with no detected mutation in these two genes. Based on a candidate gene approach, we focused our investigations on triadin and junctin, two proteins that link RyR2 and CSQ2. Mutations in the triadin (TRDN) and in the junctin (ASPH) genes were searched in a cohort of 97 CPVT patients. We identified three mutations in triadin which cosegregated with the disease on a recessive mode of transmission in two families, but no mutation was found in junctin. Two TRDN mutations, a 4 bp deletion and a nonsense mutation, resulted in premature stop codons; the third mutation, a p.T59R missense mutation, was further studied. Expression of the p.T59R mutant in COS-7 cells resulted in intracellular retention and degradation of the mutant protein. This was confirmed after in vivo expression of the mutant triadin in triadin knock-out mice by viral transduction. In this work, we identified TRDN as a new gene responsible for an autosomal recessive form of CPVT. The mutations identified in the two families lead to the absence of the protein, thereby demonstrating the importance of triadin for the normal function of the cardiac calcium release complex in humans

Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

Background Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery. Methods In this multinational retrospective observational study we enrolled adult participants (aged $\ge$18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year followup after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI. Findings10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75$\bullet$3%) were female, 2530 (24$\bullet$7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2$\bullet$8 kg/m${}^2$ (95% CI 2$\bullet$6-3$\bullet$0) and mean RMSE BMI was 4$\bullet$7 kg/m${}^2$ (4$\bullet$4-5$\bullet$0), and the mean difference between predicted and observed BMI was-0$\bullet$3 kg/m${}^2$ (SD 4$\bullet$7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery. InterpretationWe developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions.Comment: The Lancet Digital Health, 202

Inter-laboratory mass spectrometry dataset based on passive sampling of drinking water for non-target analysis

Non-target analysis (NTA) employing high-resolution mass spectrometry is a commonly applied approach for the detection of novel chemicals of emerging concern in complex environmental samples. NTA typically results in large and information-rich datasets that require computer aided (ideally automated) strategies for their processing and interpretation. Such strategies do however raise the challenge of reproducibility between and within different processing workflows. An effective strategy to mitigate such problems is the implementation of inter-laboratory studies (ILS) with the aim to evaluate different workflows and agree on harmonized/standardized quality control procedures. Here we present the data generated during such an ILS. This study was organized through the Norman Network and included 21 participants from 11 countries. A set of samples based on the passive sampling of drinking water pre and post treatment was shipped to all the participating laboratories for analysis, using one pre-defined method and one locally (i.e. in-house) developed method. The data generated represents a valuable resource (i.e. benchmark) for future developments of algorithms and workflows for NTA experiments