Microbiological evaluation of different strategies for management of snakes in captivity

Keeping snakes in captivity to produce venom for scientific research and production of inputs is now a worldwide practice. Maintaining snakes in captivity involves capture, infrastructure investments, management techniques, and appropriate qualified personnel. Further, the success of the project requires knowledge of habitat, nutrition, and reproduction, and control of opportunistic infections. This study evaluated the management of snakes in three types of captivity (quarantine, intensive, and semiextensive) and diagnosed bacterial and fungal contaminants. A bacteriological profile was obtained by swabbing the oral and cloacal cavities, scales, and venoms of healthy adult snakes from Bothrops jararaca (Bj) and Crotalus durissus terrificus (Cdt). There was predominance of Enterobacteriaceae, especially non-fermenting Gram-negative bacilli excluding Pseudomonas spp and Gram- positive bacteria. Statistically, intensive captivity resulted in the highest number of bacterial isolates, followed by recent capture (quarantine) and by semiextensive captivity. No statistical difference was found between Bj and Cdt bacterial frequency. In vitro bacterial susceptibility testing found the highest resistance against the semisynthetic penicillins (amoxicillin and ampicillin) and highest sensitivity to amicacin and tobramycin aminoglycosides. To evaluate mycological profile of snakes from intensive captivity, samples were obtained from two healthy Bj and one B. moojeni, one B. pauloensis, and one Cdt showing whitish lesions on the scales suggestive of ringworm. Using conventional methods and DNA-based molecular procedures, five samples of Trichosporon asahii were identified. Despite the traditional role of intense captivity in ophidian venom production, semiextensive captivity was more effective in the present study by virtue of presenting superior control of bacterial and fungal transmission, easier management, lowest cost, and decreased rate of mortality; therefore, it should be considered as a good alternative for tropical countries.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

The elephant in the machine : proposing a new metric of data reliability and its application to a medical case to assess classification reliability

In this paper, we present and discuss a novel reliability metric to quantify the extent a ground truth, generated in multi-rater settings, as a reliable basis for the training and validation of machine learning predictive models. To define this metric, three dimensions are taken into account: agreement (that is, how much a group of raters mutually agree on a single case); confidence (that is, how much a rater is certain of each rating expressed); and competence (that is, how accurate a rater is). Therefore, this metric produces a reliability score weighted for the raters' confidence and competence, but it only requires the former information to be actually collected, as the latter can be obtained by the ratings themselves, if no further information is available. We found that our proposal was both more conservative and robust to known paradoxes than other existing agreement measures, by virtue of a more articulated notion of the agreement due to chance, which was based on an empirical estimation of the reliability of the single raters involved. We discuss the above metric within a realistic annotation task that involved 13 expert radiologists in labeling the MRNet dataset. We also provide a nomogram by which to assess the actual accuracy of a classification model, given the reliability of its ground truth. In this respect, we also make the point that theoretical estimates of model performance are consistently overestimated if ground truth reliability is not properly taken into account