Investigation of Urinary miRNA Profile Changes in Amphotericin B-Induced Nephrotoxicity in C57BL/6 Mouse, Sprague-Dawley Rats and Beagle Dogs.

MicroRNA (miRNAs) have been associated with drug-induced kidney injury (DIKI). However, there are few reports on the utility of miRNAs, when monitoring for nephrotoxicity across multiple species. The purpose of this study was to assess the value of urinary miRNA profile changes as renal safety biomarkers, when monitoring for kidney injury in investigative toxicology studies.

Gut microbiome and serum metabolome analyses identify molecular biomarkers and altered glutamate metabolism in fibromyalgia.

Background: Fibromyalgia is a complex, relatively unknown disease characterised by chronic, widespread musculoskeletal pain. The gut-brain axis connects the gut microbiome with the brain through the enteric nervous system (ENS); its disruption has been associated with psychiatric and gastrointestinal disorders. To gain an insight into the pathogenesis of fibromyalgia and identify diagnostic biomarkers, we combined different omics techniques to analyse microbiome and serum composition.

Functional genomic analysis identifies miRNA repertoire regulating C. elegans oocyte development.

Oocyte-specific miRNA function remains unclear in mice and worms because loss of Dgcr8 and Dicer from mouse and worm oocytes, respectively, does not yield oogenic defects. These data lead to several models: (a) miRNAs are not generated in oocytes; (b) miRNAs are generated but do not perform an oogenic function; (c) functional oocyte miRNAs are generated in a manner independent of these enzymes. Here, we test these models using a combination of genomic, expression and functional analyses on the C.

Inferring the Number of Contributors to Complex DNA Mixtures Using Three Methods: Exploring the Limits of Low-Template DNA Interpretation.

In forensic DNA casework, the interpretation of an evidentiary profile may be dependent upon the assumption on the number of individuals from whom the evidence arose. Three methods of inferring the number of contributors-NOCIt, maximum likelihood estimator, and maximum allele count, were evaluated using 100 test samples consisting of one to five contributors and 0.5-0.