EVALUATION OF PASSIVE TRANSFER IN NINE SPECIES OF CERVIDAE.

The reliability of packed cell volumes (PCV), total solids (TS), blood glucose (BG), γ-glutamyl transferase (GGT), and glutaraldehyde test in determining passive transfer of colostral immunoglobulins was investigated in nine species of cervids: axis deer (Axis axis), hog deer (Axis porcinus), sika deer (Cervus nippon), tufted deer (Elaphodus cephalophus), Père David's deer (Elaphurus davidianus), pudu (Pudu puda), sambar deer (Rusa unicolor), barasinga deer (Rucervus duvaucelli), and Eld's deer (Rucervus eldii). Individually the parameters evaluated were significant though imperfect predictors of passive transfer status in cervids. Interpreted collectively as a panel along with neonate condition, these tests were clinically helpful in diagnosing failure of passive transfer (FPT). Collectively interpreting test results as a panel along with clinical assessment of the animal is recommended. Some species-specific variations in TS, GGT, and glutaraldehyde test results were identified.

A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.

Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purposes. Here, we describe a collaboration between safety researchers at Pfizer and the research team at the Comparative Toxicogenomics Database (CTD) to text mine and manually review a collection of 88,629 articles relating over 1,200 pharmaceutical drugs to their potential involvement in cardiovascular, neurological, renal and hepatic toxicity. In 1 year, CTD biocurators curated 254,173 toxicogenomic interactions (152,173 chemical-disease, 58,572 chemical-gene, 5,345 gene-disease and 38,083 phenotype interactions). All chemical-gene-disease interactions are fully integrated with public CTD, and phenotype interactions can be downloaded. We describe Pfizer's text-mining process to collate the articles, and CTD's curation strategy, performance metrics, enhanced data content and new module to curate phenotype information. As well, we show how data integration can connect phenotypes to diseases. This curation can be leveraged for information about toxic endpoints important to drug safety and help develop testable hypotheses for drug-disease events. The availability of these detailed, contextualized, high-quality annotations curated from seven decades' worth of the scientific literature should help facilitate new mechanistic screening assays for pharmaceutical compound survival. This unique partnership demonstrates the importance of resource sharing and collaboration between public and private entities and underscores the complementary needs of the environmental health science and pharmaceutical communities. Database URL: http://ctdbase.org/

Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database.

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) is a public resource that curates interactions between environmental chemicals and gene products, and their relationships to diseases, as a means of understanding the effects of environmental chemicals on human health. CTD provides a triad of core information in the form of chemical-gene, chemical-disease, and gene-disease interactions that are manually curated from scientific articles. To increase the efficiency, productivity, and data coverage of manual curation, we have leveraged text mining to help rank and prioritize the triaged literature. Here, we describe our text-mining process that computes and assigns each article a document relevancy score (DRS), wherein a high DRS suggests that an article is more likely to be relevant for curation at CTD. We evaluated our process by first text mining a corpus of 14,904 articles triaged for seven heavy metals (cadmium, cobalt, copper, lead, manganese, mercury, and nickel). Based upon initial analysis, a representative subset corpus of 3,583 articles was then selected from the 14,094 articles and sent to five CTD biocurators for review. The resulting curation of these 3,583 articles was analyzed for a variety of parameters, including article relevancy, novel data content, interaction yield rate, mean average precision, and biological and toxicological interpretability. We show that for all measured parameters, the DRS is an effective indicator for scoring and improving the ranking of literature for the curation of chemical-gene-disease information at CTD. Here, we demonstrate how fully incorporating text mining-based DRS scoring into our curation pipeline enhances manual curation by prioritizing more relevant articles, thereby increasing data content, productivity, and efficiency.

The Comparative Toxicogenomics Database: update 2013.

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) provides information about interactions between environmental chemicals and gene products and their relationships to diseases. Chemical-gene, chemical-disease and gene-disease interactions manually curated from the literature are integrated to generate expanded networks and predict many novel associations between different data types. CTD now contains over 15 million toxicogenomic relationships. To navigate this sea of data, we added several new features, including DiseaseComps (which finds comparable diseases that share toxicogenomic profiles), statistical scoring for inferred gene-disease and pathway-chemical relationships, filtering options for several tools to refine user analysis and our new Gene Set Enricher (which provides biological annotations that are enriched for gene sets). To improve data visualization, we added a Cytoscape Web view to our ChemComps feature, included color-coded interactions and created a 'slim list' for our MEDIC disease vocabulary (allowing diseases to be grouped for meta-analysis, visualization and better data management). CTD continues to promote interoperability with external databases by providing content and cross-links to their sites. Together, this wealth of expanded chemical-gene-disease data, combined with novel ways to analyze and view content, continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases.

Enteroendocrine cell expression of a cholecystokinin gene construct in transgenic mice and cultured cells.

CCK is predominantly expressed in subsets of endocrine cells in the intestine and neurons in the brain. We evaluated the expression of a CCK gene construct in transgenic mice and cultured cells to identify a genomic region that directs correct tissue- and cell-specific expression in enteroendocrine cells. The CCKL1 transgene contained 6.4 kb of mouse Cck fused to lacZ. Expression was evaluated in three transgenic lines (J11, J12, J14) by measurement of beta-galactosidase in tissue homogenates and frozen sections. Correct tissue-specific expression was observed, with beta-galactosidase activity detected in intestine and brain. However, there were differences seen in cell-specific expression in the intestine. Line J14 exhibited expression in CCK-endocrine cells, with expressing cells arising at the normal time during fetal development. However, transgene expression in line J12 intestine was limited to neurons of the enteric nervous system, which reflect an early fetal expression pattern for CCK. Analysis of an additional 15 transgenic founder mice demonstrated intestinal expression in 40% of transgenics, with expressing mice following either an endocrine cell pattern or a neuronal pattern in approximately equal numbers. CCKL1 transfection analysis in cultured cells also demonstrated enteroendocrine cell expression, with 100-fold enhanced activity in the enteroendocrine cell line STC-1 compared with nonendocrine cell lines. The results suggest that the minimal cis-regulatory DNA elements necessary for appropriate CCK expression in enteroendocrine cells reside within the 6.4-kb mouse genomic fragment.