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  • 1
    Publication Date: 2022-05-25
    Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Conservation Physiology 1 (2013): cot006, doi:10.1093/conphys/cot006.
    Description: Large whales are subjected to a variety of conservation pressures that could be better monitored and managed if physiological information could be gathered readily from free-swimming whales. However, traditional approaches to studying physiology have been impractical for large whales, because there is no routine method for capture of the largest species and there is presently no practical method of obtaining blood samples from free-swimming whales. We review the currently available techniques for gathering physiological information on large whales using a variety of non-lethal and minimally invasive (or non-invasive) sample matrices. We focus on methods that should produce information relevant to conservation physiology, e.g. measures relevant to stress physiology, reproductive status, nutritional status, immune response, health, and disease. The following four types of samples are discussed: faecal samples, respiratory samples (‘blow’), skin/blubber samples, and photographs. Faecal samples have historically been used for diet analysis but increasingly are also used for hormonal analyses, as well as for assessment of exposure to toxins, pollutants, and parasites. Blow samples contain many hormones as well as respiratory microbes, a diverse array of metabolites, and a variety of immune-related substances. Biopsy dart samples are widely used for genetic, contaminant, and fatty-acid analyses and are now being used for endocrine studies along with proteomic and transcriptomic approaches. Photographic analyses have benefited from recently developed quantitative techniques allowing assessment of skin condition, ectoparasite load, and nutritional status, along with wounds and scars from ship strikes and fishing gear entanglement. Field application of these techniques has the potential to improve our understanding of the physiology of large whales greatly, better enabling assessment of the relative impacts of many anthropogenic and ecological pressures.
    Description: This work was supported by the United States Office of Naval Research (award #N000141110435 to K.E.H., award #N000141110540 to R.M.R., and award #N0001412WX20890 to L.C.Y. and C.E.D.); the United Kingdom Natural Environmental Research Council (supporting A.J.H.); the National Center for Research Resources, a component of the United States National Institutes of Health (NIH; supporting C.E.D.); the NIH Roadmap for Medical Research (UL1 RR024146 supporting C.E.D.); The Hartwell Foundation (supporting C.E.D.) and the 2012 Marine Mammal Breath Workshop, which was funded by the National Oceanic and Atmospheric Administration’s Marine Mammal Health and Stranding Response Program.
    Keywords: Blow ; Biopsy dart ; Cetacea ; Faecal samples ; Non-invasive ; Visual health assessment
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
    Publication Date: 2016-01-30
    Description: Disease-gene identification is a challenging process that has multiple applications within functional genomics and personalized medicine. Typically, this process involves both finding genes known to be associated with the disease (through literature search) and carrying out preliminary experiments or screens (e.g. linkage or association studies, copy number analyses, expression profiling) to determine a set of promising candidates for experimental validation. This requires extensive time and monetary resources. We describe Beegle , an online search and discovery engine that attempts to simplify this process by automating the typical approaches. It starts by mining the literature to quickly extract a set of genes known to be linked with a given query, then it integrates the learning methodology of Endeavour (a gene prioritization tool) to train a genomic model and rank a set of candidate genes to generate novel hypotheses. In a realistic evaluation setup, Beegle has an average recall of 84% in the top 100 returned genes as a search engine, which improves the discovery engine by 12.6% in the top 5% prioritized genes. Beegle is publicly available at http://beegle.esat.kuleuven.be/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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