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Le présent article est consacré à la controverse sur la composition des pantoufles dans le conte Cendrillon ou la petite pantoufle de verre de Charles Perrault. A l'origine de cette controverse, Balzac fait parler un de ses personnages (un pelletier) qui propose de remplacer "verre" par "vair " (petit-gris, écureuil) et qui pense ainsi corriger ce qui lui semble être une erreur. La présente contribution propose une lecture qui permet de déceler une logique de substitution dans le texte de Perrault, logique qui suit le long des deux chaînes sémantiques "mère (morte) – cendre – vair" et "verre – grâce – marraine".
Activation of TRPC6 channels is essential for lung ischaemia–reperfusion induced oedema in mice
(2012)
Lung ischaemia–reperfusion-induced oedema (LIRE) is a life-threatening condition that causes pulmonary oedema induced by endothelial dysfunction. Here we show that lungs from mice lacking nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (Nox2y/−) or the classical transient receptor potential channel 6 (TRPC6−/−) are protected from LIR-induced oedema (LIRE). Generation of chimeric mice by bone marrow cell transplantation and endothelial-specific Nox2 deletion showed that endothelial Nox2, but not leukocytic Nox2 or TRPC6, are responsible for LIRE. Lung endothelial cells from Nox2- or TRPC6-deficient mice showed attenuated ischaemia-induced Ca2+ influx, cellular shape changes and impaired barrier function. Production of reactive oxygen species was completely abolished in Nox2y/− cells. A novel mechanistic model comprising endothelial Nox2-derived production of superoxide, activation of phospholipase C-γ, inhibition of diacylglycerol (DAG) kinase, DAG-mediated activation of TRPC6 and ensuing LIRE is supported by pharmacological and molecular evidence. This mechanism highlights novel pharmacological targets for the treatment of LIRE.
TMEM70 is involved in the biogenesis of mitochondrial ATP synthase and mutations in the TMEM70 gene impair oxidative phosphorylation. Herein, we report on pathology and treatment of ATP synthase deficiency in four siblings. A consanguineous family of Roma (Gipsy) ethnic origin gave birth to 6 children of which 4 were affected presenting with dysmorphic features, failure to thrive, cardiomyopathy, metabolic crises, and 3-methylglutaconic aciduria as clinical symptoms. Genetic testing revealed a homozygous mutation (c.317-2A>G) in the TMEM70 gene. While light microscopy was unremarkable, ultrastructural investigation of muscle tissue revealed accumulation of swollen degenerated mitochondria with lipid crystalloid inclusions, cristae aggregation, and exocytosis of mitochondrial material. Biochemical analysis of mitochondrial complexes showed an almost complete ATP synthase deficiency. Despite harbouring the same mutation, the clinical outcome in the four siblings was different. Two children died within 60 h after birth; the other two had recurrent life-threatening metabolic crises but were successfully managed with supplementation of anaplerotic amino acids, lipids, and symptomatic treatment during metabolic crisis. In summary, TMEM70 mutations can cause distinct ultrastructural mitochondrial degeneration and almost complete deficiency of ATP synthase but are still amenable to treatment.
Assessing the uncertainties of simulation results of ecological models is becoming increasingly important, specifically if these models are used to estimate greenhouse gas emissions on site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure, and (iv) accurateness of measurements (e.g., soil-atmosphere greenhouse gas exchange) which are used for model testing and development.
The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO) and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used.
Our approach shows that by means of the joint parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange. In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of an calibration set (6 yr) and an independent validation set of 4 yr. The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Root-mean-squared error (RMSE) NO: 2.4 to 18.95 g N ha−1 d−1, N2O: 0.14 to 21.12 g N ha−1 d−1, CO2: 5.4 to 11.9 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes still limited to accurately predict observed seasonal variations in fluxes.
Assessing the uncertainties of simulation results of ecological models is becoming of increasing importance, specifically if these models are used to estimate greenhouse gas emissions at site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure and (iv) accurateness of measurements (e.g. soil-atmosphere greenhouse gas exchange) which are used for model testing and development.
The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO), and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used.
Our approach showed that by means of the joined parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange.
In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of the calibration set (6 yr) and an independent validation set of 4 yr.
The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Residual mean squared error (RMSE) NO: 2.5 to 21.3 g N ha−1 d−1, N2O: 0.2 to 21.4 g N ha−1 d−1, CO2: 5.8 to 12.6 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes limited to accurately predict observed seasonal variations in fluxes.
Hintergrund: Ab Frühjahr 2020 kam es zur weltweiten Verbreitung von SARS-CoV‑2 mit der heute als erste Welle der Pandemie bezeichneten Phase ab März 2020. Diese resultierte an vielen Kliniken in Umstrukturierungen und Ressourcenverschiebungen. Ziel unserer Arbeit war die Erfassung der Auswirkungen der Pandemie auf die universitäre Hals-Nasen-Ohren(HNO)-Heilkunde für die Forschung, Lehre und Weiterbildung. Material und Methoden: Die Direktorinnen und Direktoren der 39 Universitäts-HNO-Kliniken in Deutschland wurden mithilfe einer strukturierten Online-Befragung zu den Auswirkungen der Pandemie im Zeitraum von März bis April 2020 auf die Forschung, Lehre und die Weiterbildung befragt. Ergebnisse: Alle 39 Direktorinnen und Direktoren beteiligten sich an der Umfrage. Hiervon gaben 74,4 % (29/39) an, dass es zu einer Verschlechterung ihrer Forschungstätigkeit infolge der Pandemie gekommen sei. Von 61,5 % (24/39) wurde berichtet, dass pandemiebezogene Forschungsaspekte aufgegriffen wurden. Von allen Kliniken wurde eine Einschränkung der Präsenzlehre berichtet und 97,5 % (38/39) führten neue digitale Lehrformate ein. Im Beobachtungszeitraum sahen 74,4 % der Klinikdirektoren die Weiterbildung der Assistenten nicht gefährdet. Schlussfolgerung: Die Ergebnisse geben einen Einblick in die heterogenen Auswirkungen der Pandemie. Die kurzfristige Bearbeitung pandemiebezogener Forschungsthemen und die Einführung innovativer digitaler Konzepte für die studentische Lehre belegt eindrücklich das große innovative Potenzial und die schnelle Reaktionsfähigkeit der HNO-Universitätskliniken, um auch während der Pandemie ihre Aufgaben in der Forschung, Lehre und Weiterbildung bestmöglich zu erfüllen.
Endometriosis represents nowadays a real burden for the patients as well as for the physicians, as it requires surgical and/or medical treatment, often long – termed and repeated. Moreover, the high costs necessary to diagnose and treat endometriosis represent a real economic burden, being comparable to other chronic diseases like diabetes or rheumatoid arthritis. Therefore, the physicians dealing with this disease should take into account not only the efficacy of the treatment, but also the economic aspects and patients compliance.
The present paper analyses the efficiency of progestins (lynestrenol and medrogestone) in endometriosis as a cost – effective, but forgotten medical therapy of the disease. Our study underlines the good tolerability of progestins, as they have limited side effects, the compliance of patients being high. They are also low-cost medications, which could represent an effective alternative method in the endometriosis treatment, especially in less – developed countries that cannot afford the higher therapeutic costs.