Parameterizing Potential Exposure to Sulfur Mustard (HD) Using Mixed Model Regression

The possible threat posed by terrorists using chemical warfare agents (CWAs) against civilian targets is a major concern, reflecting the fact that CWAs are highly toxic to unprotected populations, with releases as vapors or aerosols likely to produce mass casualties on a highly localized basis within minutes or hours after an incident. A conceptual site model is developed and mixed model regression is used to estimate concentration values for the vesicant sulfur mustard (HD) based on the output from computational fluid dynamics (CFD) simulation following wind tunnel experimentation. The analysis provides a first-approximation of the spatial and temporal distribution of potential exposures within a set of 50 m × 50 m × 2 m grids across a 1000 m width by 300 m height by 2250 m length domain in a geographic information system (GIS) environment. The HD concentration values are calculated as log-averaged mean and the 95% confidence intervals for each grid at 1.9 d and 6.0 d after initial release. The technique offers a statistically valid means for rapidly generating unbiased first-approximations of concentration values subsequent to an initial release as an alternative to extensive monitoring or multiple runs of CFD models to parameterize potential exposure to HD spatially and temporally.     

Serum microRNA-33 levels in pre-diabetic and diabetic patients

Molecular Biology Reports - Diabetes mellitus (DM) is a metabolic disease characterized by hyperglycemia and abnormal insulin secretion. MicroRNAs are small, non-coding RNAs that are able to affect...