Jejunal ulceration and push enteroscopy.
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Biomedical subjects
Publications and source records attributed to A C Taylor.
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Two related experiments examined the relationship between plasma cortisol concentrations and the development of social hierarchies in fish. In the first, rainbow trout, Oncorhynchus mykiss, and brown trout, Salmo trutta, were observed for dominance interactions when confined within single-species pairs for 4, 48, or 168 h. Subordinate members of a pair exhibited significantly higher cortisol concentrations than dominant and single fish, but the pattern of cortisol elevation differed between the two species, being quicker to rise and increasing to a higher level in rainbow trout. Cortisol concentrations were correlated with behavioural measurements; the more subordinate the behaviour exhibited by a fish, the higher its cortisol concentration. Social stress was a chronic stressor, and no acclimation to social status occurred during the week. In the second experiment, measurements of plasma cortisol were made before pairing of rainbow trout and then after 48 h of confinement in pairs. Subordinate fish demonstrated significantly higher concentrations of plasma cortisol both before and after social stress. It therefore appears that in addition to cortisol being elevated during periods of social stress, an association may exist between initial cortisol levels and the likelihood of a fish becoming subordinate.
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The propagation of variance through complex exposure models has been simplified by simulation software running on desktop computers; however, the appropriate representation of variability in, and uncertainty about, model inputs remains a challenge. The U.S. Environmental Protection Agency (EPA) has indicated that the Monte Carlo simulation approach to exposure assessment is acceptable as long as input distributions are credible, i.e., rooted in fact (EPA, 1992). The use of distributions based on empirical evidence is certainly desirable; however, it is not always possible to obtain measurements for all exposure model inputs under the conditions of interest. Where objective evidence is scarce or unavailable, subjective judgments are necessary. In this work, the application of both statistical and subjective approaches to the development of distributions for exposure model inputs is explored. The consequences of one's approach to distribution development, on the interpretation and applicability of the output, are also considered.