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Background The percentage of women

Dans le cadre de cet article, nous voudrions démontrer qu’il est possible de renouveler l’enseignement des Fables grâce à une étude écopoétique, qui permettrait d’aborder autrement, par le prisme d’une langue et d’une pensée anciennes, nos préoccupations contemporaines en matière d’écologie. À partir d’une sélection d’une quarantaine de fables, nous proposerons plusieurs axes de réflexion afin de mettre en évidence la conscience écologique – ou plus précisément paléo-écologique – à l’œuvre dans le corpus lafontainien. La Fontaine parle de souffrance animale, d’anthropisation, de perturbation des écosystèmes… Si les mots ne sont pas les mêmes, les termes que La Fontaine déploie dans sa poésie (« demeure », « naturel », etc.) servent bien à parler du rapport de l’humain au vivant.

Abstract The molecular mechanisms induced by hypoxia are misunderstood in non-small cell lung cancer (NSCLC), and above all the hypoxia and RASSF1A/Hippo signaling relationship. We confirmed that human NSCLC (n = 45) as their brain metastases (BM) counterpart are hypoxic since positive with CAIX-antibody (target gene of Hypoxia-inducible factor (HIF)). A severe and prolonged hypoxia (0.2% O2, 48 h) activated YAP (but not TAZ) in Human Bronchial Epithelial Cells (HBEC) lines by downregulating RASSF1A/kinases Hippo (except for NDR2) regardless their promoter methylation status. Subsequently, the NDR2-overactived HBEC cells exacerbated a HIF-1A, YAP and C-Jun-dependent-amoeboid migration, and mainly, support BM formation. Indeed, NDR2 is more expressed in human tumor of metastatic NSCLC than in human localized NSCLC while NDR2 silencing in HBEC lines (by shRNA) prevented the xenograft formation and growth in a lung cancer-derived BM model in mice. Collectively, our results indicated that NDR2 kinase is over-active in NSCLC by hypoxia and supports BM formation. NDR2 expression is thus a useful biomarker to predict the metastases risk in patients with NSCLC, easily measurable routinely by immunohistochemistry on tumor specimens.

An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the Local and Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst three are research-grade SCMs designed for fog simulation, and the LESs are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number concentration (CDNC) conditions. The main SCM bias appears to be toward the overdevelopment of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parameterisation, as it is to the underlying aerosol or CDNC.

Despite growing attention, antibiotics (such as streptomycin, oxytetracycline or kasugamycin) are still used worldwide for the control of major bacterial plant diseases. This raises concerns on their potential, yet unknown impact on antibiotic and multidrug resistances and the spread of their genetic determinants among bacterial pathogens. Antibiotic resistance genes (ARGs) have been identified in plant pathogenic bacteria (PPB), with streptomycin resistance genes being the most commonly reported. Therefore, the contribution of mobile genetic elements (MGEs) to their spread among PPB, as well as their ability to transfer to other bacteria, need to be further explored. The only well-documented example of ARGs vector in PPB, Tn5393 and its highly similar variants (carrying streptomycin resistance genes), is concerning because of its presence outside PPB, in Salmonella enterica and Klebsiella pneumoniae, two major human pathogens. Although its structure among PPB is still relatively simple, in human- and animal-associated bacteria, Tn5393 has evolved into complex associations with other MGEs and ARGs. This review sheds light on ARGs and MGEs associated with PPB, but also investigates the potential role of antibiotic use in resistance selection in plant-associated bacteria.

Introduction: Prenatal ultrasound (US) anomalies are detected in around 5%–10% of pregnancies. In prenatal diagnosis, exome sequencing (ES) diagnostic yield ranges from 6% to 80% depending on the inclusion criteria. We describe the first French national multicenter pilot study aiming to implement ES in prenatal diagnosis following the detection of anomalies on US.Patients and methods: We prospectively performed prenatal trio-ES in 150 fetuses with at least two US anomalies or one US anomaly known to be frequently linked to a genetic disorder. Trio-ES was only performed if the results could influence pregnancy management. Chromosomal microarray (CMA) was performed before or in parallel.Results: A causal diagnosis was identified in 52/150 fetuses (34%) with a median time to diagnosis of 28 days, which rose to 56/150 fetuses (37%) after additional investigation. Sporadic occurrences were identified in 34/56 (60%) fetuses and unfavorable vital and/or neurodevelopmental prognosis was made in 13/56 (24%) fetuses. The overall diagnostic yield was 41% (37/89) with first-line trio-ES versus 31% (19/61) after normal CMA. Trio-ES and CMA were systematically concordant for identification of pathogenic CNV.Conclusion: Trio-ES provided a substantial prenatal diagnostic yield, similar to postnatal diagnosis with a median turnaround of approximately 1 month, supporting its routine implementation during the detection of prenatal US anomalies.

The work presented in this article studies the impact of cloud condensation nuclei (CCN) activation for fog forecasting and improves its parameterization in the LIMA (Liquid, Ice, Multiple Aerosols) two‐moment microphysical scheme, building upon the Local And Non‐local Fog EXperiment (LANFEX) field campaign observations, specifically the intensive observation period (IOP) 1 and the DEMISTIFY intercomparison. Large‐eddy simulations were performed with the Meso‐NH model, first using a prognostic supersaturation allowing us to compute the number of activated CCN at each time step, and then with the usual saturation adjustment hypothesis and a diagnostic maximum supersaturation. The prognostic supersaturation method provided very good results, similar to those from earlier simulations of this case using a bin scheme, and was thus used as a reference. In contrast, the diagnostic maximum supersaturation method strongly overestimated droplet numbers and produced a too‐thick fog. Thus, improvements to the maximum supersaturation diagnostic were proposed, by (1) revising the temperature tendency and (2) accounting for pre‐existing cloud droplets in the activation parameterization. These improvements resulted in a simulation in good agreement with observations and the reference simulation, and are promising for use in numerical weather prediction systems with a lower resolution and/or a longer time step. [ABSTRACT FROM AUTHOR]

An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the Local and Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst three are research-grade SCMs designed for fog simulation, and the LESs are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number concentration (CDNC) conditions. The main SCM bias appears to be toward the overdevelopment of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parameterisation, as it is to the underlying aerosol or CDNC.

ABSTRACT The clone Staphylococcus capitis NRCS-A is responsible for late-onset sepsis in neonatal intensive care units (NICUs) worldwide. Over time, this clone has evolved into three subgroups that are increasingly adapted to the NICU environment. This study aimed to decipher the mechanisms involved in NRCS-A persistence in NICUs. Twenty-six S. capitis strains belonging to each of the three NRCS-A clone subgroups and two other non-NRCS-A groups from neonates (alpha clone) or from adult patients (“other strains”) were compared based on growth kinetics and ability to form biofilm as well as tolerance to desiccation and to different disinfectants. S. capitis biofilm formation was enhanced in rich medium and decreased under conditions of nutrient stress for all strains. However, under conditions of nutrient stress, NRCS-A strains presented an enhanced ability to adhere and form a thin biofilm containing more viable and culturable bacteria (mean 5.7 log10 CFU) than the strains from alpha clone (mean, 1.1 log10 CFU) and the “other strains” (mean, 4.2 log10 CFU) (P

Epidermal growth factor receptor (EGFR) genotyping, a critical examen for the treatment decisions of patients with non-small cell lung cancer (NSCLC), is commonly assayed by next-generation sequencing (NGS), but this global approach takes time. To determine whether rapid EGFR genotyping tests by the IdyllaTM system guides earlier therapy decisions, EGFR mutations were assayed by both the IdyllaTM system and NGS in 223 patients with NSCLC in a bicentric prospective study. IdyllaTM demonstrated agreement with the NGS method in 187/194 cases (96.4%) and recovered 20 of the 26 (77%) EGFR mutations detected using NGS. Regarding the seven missed EGFR mutations, five were not detected by the IdyllaTM system, one was assayed in a sample with insufficient tumoral cells, and the last was in a sample not validated by the IdyllaTM system (a bone metastasis). IdyllaTM did not detect any false positives. The average time between EGFR genotyping results from IdyllaTM and the NGS method was 9.2 ± 2.2 working days (wd) (12.6 ± 4.0 calendar days (cd)). Subsequently, based on the IdyllaTM method, the timeframe from tumor sampling to the initiation of EGFR-TKI was 7.7 ± 1.2 wd (11.4 ± 3.1 cd), while it was 20.3 ± 6.7 wd (27.2 ± 8.3 cd) with the NGS method (p < 0.001). We thus demonstrated here that the IdyllaTM system contributes to improving the therapeutic care of patients with NSCLC by the early screening of EGFR mutations.

Accurate and timely fog forecasts are needed to support decision making for various activities which are critically affected by low visibility conditions [...]

Aim: The aim of this work was to investigate the association between early postoperative anastomotic leakage or pelvic abscess (AL/PA) and symptomatic anastomotic stenosis (SAS) in patients after surgery for left colonic diverticulitis. Method: This is a retrospective study based on a national cohort of diverticulitis surgery patients carried out by the Association Française de Chirurgie. The assessment was performed using path analyses. The database included 7053 patients operated on for colonic diverticulitis, with surgery performed electively or in an emergency, by open access or laparoscopically. Patients were excluded from the study analysis where there was (i) right‐sided diverticulitis (the initial database included all consecutive patients operated on for colonic diverticulitis), (ii) no anastomosis was performed during the first procedure or (iii) missing information about stenosis, postoperative abscess or anastomotic leakage. Results: Of the 4441 patients who were included in the final analysis, AL/PA occurred in 327 (4.6%) and SAS occurred in 82 (1.8%). AL/PA was a significant independent factor associated with a risk for occurrence of SAS (OR = 3.41, 95% CI = 1.75–6.66), as was the case for diverting stoma for ≥100 days (OR = 2.77, 95% CI = 1.32–5.82), while central vessel ligation proximal to the inferior mesenteric artery was associated with a reduced risk (OR = 0.41; 95% CI = 0.19–0.88). Diverting stoma created for <100 days or ≥100 days was also a factor associated with a risk for AL/PA (OR = 3.08, 95% CI = 2–4.75 and OR = 12.95, 95% CI = 9.11–18.50). Interestingly, no significant association between radiological drainage or surgical management of AL/PA and SAS could be highlighted. Conclusion: AL/PA was an independent factor associated with the risk for SAS. The treatment of AL/PA was not associated with the occurrence of anastomotic stenosis. Diverting stoma was associated with an increased risk of both AL/PA and SAS, especially if it was left for ≥100 days. Physicians must be aware of this information in order to decide on the best course of action when creating a stoma during elective or emergency surgery. [ABSTRACT FROM AUTHOR]

Low-visibility conditions (LVC) are a common cause of air traffic, road, and sailing fatalities. Forecasting those conditions is an arduous challenge for weather forecasters all over the world. In this work, a new decision support system is developed based on an analog ensemble (AnEn) method to predict LVC over 15 airports of Morocco for 24 forecast hours. Hourly forecasts from the AROME model of eight predictors were used to select the skillful analogs from 2016 to 2018. The verified hourly observations were used as members of the ensemble. The developed ensemble prediction system (EPS) was assessed over 1 year (2019) as a single-value forecast and as a probabilistic forecast. Results analysis shows that AnEn outperforms persistence and its best performances are perceived generally during night and early-morning lead times. From continuous verification analysis, AnEn forecasting errors are found to be location- and lead-time-dependent and become higher for low-visibility cases. AnEn draws an averaged Centered Root Mean Square Error of about 1500 m for all visibilities, 2000 m for fog and 1500 m for mist. As an EPS, AnEn is under-dispersive for all lead times and draws a positive bias for fog and mist events. For probabilistic verification analysis, AnEn visibility forecasts are converted to binary occurrences depending on a set of thresholds from 200 m to 6000 m by a step of 200 m. It is found that the averaged Heidke Skill Score for AnEn is 0.65 for all thresholds. However, AnEn performance generally becomes weaker for fog or mist events prediction.