Short-chain fatty acids and polyamines in the pathogenesis of necrotizing enterocolitis: Kinetics aspects in gnotobiotic quails

Despite years of investigation, pathogenesis of necrotizing enterocolitis (NEC) remains elusive. Bacterial metabolites were implicated by several authors but their roles remain controversial. The aim of our study was to investigate the role of SCFAs and polyamines through a kinetic study of histological and macroscopical digestive lesions in monobiotic quails. Germ-free quails, inoculated with a Clostridium butyricum strain involved in a NEC case, were fed or not with a diet including lactose (7%). Quails were sacrificed at various times between D7 and D24 after bacterial inoculation. NEC-like lesions, i.e. thickening, pneumatosis, and hemorrhages, occurred only in lactose-fed quails and increased with time. The main histological characteristics were infiltrates of mononuclear cells, then heterophilic cells, then gas cyst and necrosis. The first event observed, before histological and macroscopical lesions, is a high production of butyric acid, which precedes an increase of iNOS gene expression. No difference in polyamines contents depending on the diet was observed. These results show the major role of butyric acid produced by commensal bacteria in the onset of the digestive lesions.     

New Insights into Handling Missing Values in Environmental Epidemiological Studies

Missing data are unavoidable in environmental epidemiologic surveys. The aim of this study was to compare methods for handling large amounts of missing values: omission of missing values, single and multiple imputations (through linear regression or partial least squares regression), and a fully Bayesian approach. These methods were applied to the PARIS birth cohort, where indoor domestic pollutant measurements were performed in a random sample of babies'' dwellings. A simulation study was conducted to assess performances of different approaches with a high proportion of missing values (from 50% to 95%). Different simulation scenarios were carried out, controlling the true value of the association (odds ratio of 1.0, 1.2, and 1.4), and varying the health outcome prevalence. When a large amount of data is missing, omitting these missing data reduced statistical power and inflated standard errors, which affected the significance of the association. Single imputation underestimated the variability, and considerably increased risk of type I error. All approaches were conservative, except the Bayesian joint model. In the case of a common health outcome, the fully Bayesian approach is the most efficient approach (low root mean square error, reasonable type I error, and high statistical power). Nevertheless for a less prevalent event, the type I error is increased and the statistical power is reduced. The estimated posterior distribution of the OR is useful to refine the conclusion. Among the methods handling missing values, no approach is absolutely the best but when usual approaches (e.g. single imputation) are not sufficient, joint modelling approach of missing process and health association is more efficient when large amounts of data are missing.     

Kinetics of Aggregate Formation in Social Insects

A model for the kinetics of aggregation in social insects which accounts for stochastic effects arising from individual variability and covers both the early and the mature stages of the process is developed. Different aggregation scenarios are studied, depending on the degree of cooperativity and the mean population density. It is shown that under certain conditions, the system evolves slowly to a single cluster incorporating all individuals, or to two coexisting clusters of similar sizes. Present address: Department of Zoology, University of Oxford, OX1 3PS Oxford, UK.