Toxicologic Pathology Forum: A Roadmap for Building State-of-the-Art Digital Image Data Resources for Toxicologic Pathology in the Pharmaceutical Industry.

Digitization of histologic slides brings with it the promise of enhanced toxicologic pathology practice through the increased application of computational methods. However, the development of these advanced methods requires access to substrate image data, that is, whole slide images (WSIs). Deep learning methods, in particular, rely on extensive training data to develop robust algorithms.

Zoonotic tuberculosis. A comprehensive ONE HEALTH approach.

The objective of this report is to provide information on Mycobacterium tuberculosis complex infections in animals and in humans. Included is information on the susceptibility of different species as well as information on etiology, epidemiology, pathogenesis, diagnosis, prevention and control of this disease. The term One Health has been adopted to describe the unified human medical and veterinary interdisciplinary/multidisciplinary collaborative approach to zoonoses and will be critical for future endeavors in the control of the global TB epidemic.

Improved HIV-1 RNA quantitation by COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 using a novel dual-target approach.

Background: HIV-1 RNA viral load is a key parameter for reliable treatment monitoring of HIV-1 infection. Accurate HIV-1 RNA quantitation can be impaired by primer and probe sequence polymorphisms as a result of tremendous genetic diversity and ongoing evolution of HIV-1. A novel dual HIV-1 target amplification approach was realized in the quantitative COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.

web cellHTS2: a web-application for the analysis of high-throughput screening data.

Background: The analysis of high-throughput screening data sets is an expanding field in bioinformatics. High-throughput screens by RNAi generate large primary data sets which need to be analyzed and annotated to identify relevant phenotypic hits. Large-scale RNAi screens are frequently used to identify novel factors that influence a broad range of cellular processes, including signaling pathway activity, cell proliferation, and host cell infection.

GenomeRNAi: a database for cell-based RNAi phenotypes. 2009 update.

The GenomeRNAi database (http://www.genomernai.org/) contains phenotypes from published cell-based RNA interference (RNAi) screens in Drosophila and Homo sapiens.