Inclusion of bone marrow fibrosis in patient assessment may further aid in risk-adapted therapeutic decisions.”
“The exposure and toxicological data used in human health risk assessment are obtained from diverse and heterogeneous sources. Complex mixtures found on contaminated sites
can pose a significant challenge to effectively assess the toxicity potential Copanlisib mouse of the combined chemical exposure and to manage the associated risks. A data fusion framework has been proposed to integrate data from disparate sources to estimate potential risk for various public health issues. To demonstrate the effectiveness of the proposed data fusion framework, an illustrative example for a hydrocarbon mixture is presented. The Joint Directors of Laboratories Data Fusion selleckchem architecture was selected as the data fusion architecture and Dempster-Shafer Theory (DST) was chosen as the technique for data fusion. For neurotoxicity response analysis, neurotoxic metabolites toxicological data were fused with predictive toxicological data and then probability-boxes (p-boxes) were developed to represent the toxicity of each compound. The neurotoxic response was
given a rating of “low”, “medium” or “high”. These responses were then weighted by the percent composition in the illustrative F1 hydrocarbon mixture. The resulting p-boxes were fused according to DST’s mixture rule of combination. The fused p-boxes were fused again with toxicity data for n-hexane. The case study for F1 hydrocarbons illustrates how data fusion can help in the assessment of the health effects for complex mixtures with limited available data. (C) 2012 Elsevier Ireland Ltd. All rights reserved.”
“The occurrence of Giardia and Cryptosporidium was investigated in cetacean specimens stranded on the northwestern coast of Spain (European Atlantic coast) by analysis of 65 samples of large intestine from eight species.
The parasites were identified by direct immunofluorescence antibody test (IFAT) and by β-Nicotinamide PCR amplification of the beta-giardin gene, the ITS1-5.8S-ITS2 region and the SSU-rDNA gene of Giardia and the SSU-rDNA gene of Cryptosporidium. Giardia and Cryptosporidium were detected in 7 (10.8 %) and 9 samples (13.8 %), respectively. In two samples, co-infection with both parasites was observed. Giardia duodenalis assemblages A, C, D and F, and Cryptosporidium parvum were identified. This is the first report of G. duodenalis in Balaenoptera acutorostrata, Kogia breviceps and Stenella coeruleoalba and also the first report of Cryptosporidium sp. in B. acutorostrata and of C. parvum in S. coeruleoalba and Tursiops truncatus. These results extend the known host range of these waterborne enteroparasites.