The impact of job-demand-control-support on leptin and ghrelin as biomarkers of stress in emergency healthcare workers

Despite the available literature on the consequences of night shiftwork on stress and food intake, its impact on leptin and ghrelin has never been studied. We previously demonstrated that leptin and ghrelin were biomarkers related to stress, and acute stress-induced a decrease in leptin levels and an increase in ghrelin levels. We performed a prospective observational study to assess the influence of night work, nutrition, and stress on the levels of ghrelin and leptin among emergency healthcare workers (HCWs). We took salivary samples at the beginning of a day shift and/or at the end of a night shift. We also monitored stress using the job demand-control-support model of Karasek. We recorded 24-h food intake during the day shift and the consecutive night shift and during night work and the day before. We included 161 emergency HCWs. Emergency HCWs had a tendency for decreased levels of leptin following the night shift compared to before the dayshift (p = 0.067). Furthermore, the main factors explaining the decrease in leptin levels were an increase in job-demand (coefficient −54.1, 95 CI −99.0 to −0.92) and a decrease in job control (−24.9, −49.5 to −0.29). Despite no significant changes in ghrelin levels between shifts, social support was the main factor explaining the increase in ghrelin (6.12, 0.74 to 11.5). Food intake (kcal) also had a negative impact on leptin levels, in addition to age. Ghrelin levels also decreased with body mass index, while age had the opposite effect. In conclusion, we confirmed that ghrelin and leptin as biomarkers of stress were directly linked to the job demand-control-support model of Karasek, when the main cofounders were considered

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

Nonlinear system identification using Volterra series representation : application to audio systems

Cette thèse porte sur l’identification de systèmes non linéaires représentables en séries de Volterra, et son application à des systèmes sonores. Les séries de Volterra, qui permettent de représenter une large classe de systèmes non linéaires, correspondent à un développement en série organisé par ordre d'homogénéité par rapport à l’entrée: chaque terme homogène est caractérisé par un noyau convolutif dont l’ensemble fournit une "signature complète" du système représenté. Les travaux présentés reposent sur le développement d’une étape préalable de séparation des termes de la série pour améliorer l’identification des noyaux de Volterra. Par rapport aux méthodes déjà existantes de séparation en ordres homogènes, basées sur des relations d’amplitudes entre signaux tests, l'approche adoptée dans cette thèse consiste à exploiter les relations de phase entre signaux afin d'obtenir une méthode robuste. Cela est tout d’abord obtenu de manière abstraite pour le cas de signaux d’excitations complexes. De cette idée, plusieurs méthodes adaptées au cas des signaux réels sont développées. Ceci amène à définir de nouvelles catégories de signaux pour décrire la sortie d’une série de Volterra, regroupant les contributions selon leurs propriétés de phase. Les méthodes de séparation proposées sont testées et appliquées à une pédale d’effet de guitare. Ensuite, des méthodes d’identification spécifiques aux nouveaux types de signaux sont présentées. Enfin, une méthode d’estimation des paramètres d’une représentation d’état à non-linéarités polynomiales est développée. Celle-ci est appliquée à un haut-parleur électrodynamique, dont les caractéristiques non linéaires sont étudiées.This thesis addresses the identification of nonlinear systems that can be represented with Volterra series, and its application to audio systems. Volterra series give an input-output representation, approximated to within a given error, of any time-invariant continuous nonlinear system with fading memory. Technically, they correspond to a series expansion sorted by homogeneity order with respect to the input: each homogeneous term is characterized by a convolutive kernel whose set provides a "complete signature" of the modelled system. The works presented are based on the development of a preliminary step that consists in separating the series' terms to improve Volterra kernels' identification. Compared to existing homogeneous order separation methods, which are based on amplitude relationships between test signals, the approach chosen in this thesis is to exploit phase relationships between signals to obtain a robust method. This is first obtained in the theoretical case of complex excitation signals. From this idea, several methods suited to the use of real signals are developed. This leads to define new signals categories that describes the output of a Volterra series, sorting nonlinear contributions according to their phase properties. The proposed separation methods are applied and tested on a guitar pedal effect. Then, specific identification methods for the new types of signals are presented Finally, a method for estimating the parameters of a polynomial nonlinear state-space representation is developed. This is applied to an electrodynamic loudspeaker whose nonlinear characteristics are studied

Réseaux de transport et de distribution de gaz naturel

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Etudes universitaires: CJUE, 24 nov. 2022, aff. C-632/20, MCM c/ Centrala

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Les communaux et l'action publique européenne : entre invisibilité générale et protection a minima

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Un règlement européen ne nécessite aucune mesure de transposition pour être applicable

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Dispositif de lutte contre l'évasion fiscale et liberté de circulation des capitaux

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Les cent jours de présidence de Klaus Iohannis

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