Glucocorticoid Effects on the Programming of AT1b Angiotensin Receptor Gene Methylation and Expression in the Rat

Adverse events in pregnancy may ‘programme’ offspring for the later development of cardiovascular disease and hypertension. Previously, using a rodent model of programmed hypertension we have demonstrated the role of the renin-angiotensin system in this process. More recently we showed that a maternal low protein diet resulted in undermethylation of the At1b angiotensin receptor promoter and the early overexpression of this gene in the adrenal of offspring. Here, we investigate the hypothesis that maternal glucocorticoid modulates this effect on fetal DNA methylation and gene expression. We investigated whether treatment of rat dams with the 11β-hydroxylase inhibitor metyrapone, could prevent the epigenetic and gene expression changes we observed. Offspring of mothers subjected to a low protein diet in pregnancy showed reduced adrenal Agtr1b methylation and increased adrenal gene expression as we observed previously. Treatment of mothers with metyrapone for the first 14 days of pregnancy reversed these changes and prevented the appearance of hypertension in the offspring at 4 weeks of age. As a control for non-specific effects of programmed hypertension we studied offspring of mothers treated with dexamethasone from day 15 of pregnancy and showed that, whilst they had raised blood pressure, they failed to show any evidence of Agtr1b methylation or increase in gene expression. We conclude that maternal glucocorticoid in early pregnancy may induce changes in methylation and expression of the Agtr1b gene as these are clearly reversed by an 11 beta-hydroxylase inhibitor. However in later pregnancy a converse effect with dexamethasone could not be demonstrated and this may reflect either an alternative mechanism of this glucocorticoid or a stage-specific influence

Modalités non invasives d'instillation du surfactant exogène

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Sensitivity of predatory bacteria of the genus Bdellovibrio sp. and their preys from Enterobacteriaceae family on antibiotics and disinfectant

Celem pracy była ocena możliwości wykorzystania bakterii drapieżnych z rodzaju Bdellovibrio do oczyszczania ścieków komunalnych z patogennych bakterii Serratia liquefaciens i Citrobacter freundii. Wykazano, że wyizolowane ze ścieków bakterie drapieżne oraz ich ofiary były wrażliwe na antybiotyki, m.in. chloramfenikol, streptomycynę i tetracyklinę oraz płyn dezynfekcyjny tzw. Wodę Ecofair. Stwierdzono, że bakterie Bdellovibrio sp. mogą pełnić funkcję regulatora liczebności bakterii G (-) z rodziny Enterobacteriaceae.The aim of this study was to evaluate the use of predatory bacteria of the genus Bdellovibrio to treatment municipal wastewater with Serratia liquefaciens and Citrobacter freundii bacteria. It was observed, that isolated predadatory bacteria and their preys were sensitive on antibiotics: chloramphenicol, streptomycine and tetracycline and Ecofair Water disinfectant. It was showed that the bacteria of Bdellovibrio genus can reduce the total number of G (-) pathogenic bacteria from Enterobacteriaceae family

Early Detection of Late Onset Sepsis in Premature Infants Using Visibility Graph Analysis of Heart Rate Variability

International audienceObjective: This study was designed to test the diagnostic value of visibility graph features derived from the heart rate time series to predict late onset sepsis (LOS) in preterm infants using machine learning. Methods: The heart rate variability (HRV) data was acquired from 49 premature newborns hospitalized in neonatal intensive care units (NICU). The LOS group consisted of patients who received more than five days of antibiotics, at least 72 hours after birth. The control group consisted of infants who did not receive antibiotics. HRV features in the days prior to the start of antibiotics (LOS group) or in a randomly selected period (control group) were compared against a baseline value calculated during a calibration period. After automatic feature selection, four machine learning algorithms were trained. All the tests were done using two variants of the feature set: one only included traditional HRV features, and the other additionally included visibility graph features. Performance was studied using area under the receiver operating characteristics curve (AUROC). Results: The best performance for detecting LOS was obtained with logistic regression, using the feature set including visibility graph features, with AUROC of 87.7% during the six hours preceding the start of antibiotics, and with predictive potential (AUROC above 70%) as early as 42 h before start of antibiotics. Conclusion: These results demonstrate the usefulness of introducing visibility graph indexes in HRV analysis for sepsis prediction in newborns. Significance: The method proposed the possibility of non-invasive, real-Time monitoring of risk of LOS in a NICU setting