Artificial neural network prediction of viruses in shellfish

Article Abstract:

A database was probed with artificial neural network (ANN) and multivariate logistic regression (MLR) models to investigate the efficacy of predicting PCR-identified human adenovirus (ADV) and presence or absence of other viruses in shellfish. A validation study on ADV demonstrated that the MLR and ANN models differed in sensitivity and selectivity, with the ANN model correctly identifying ADV presence with greater precision.

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Quantification and stability of human adenoviruses and polyomavirus JCPyV in wastewater matrices

Article Abstract:

Real-time quantitative PCR procedures are applied to analyze different wastewater metrices to locate the presence, quantity, and stability of a wide diversity of excreted human adenoviruses (HAdV) and human polyomavirus JCPyV. HAdV and JCPyV are detected in high quantities in the sewage, effluent wastewater, sludge, and biosolid samples confirming the suitability of both viruses as indicators of human fecal viral pollution.

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Detection of Bovine and porcine adenoviruses for tracing the source of fecal contamination

Article Abstract:

A molecular procedure for the detection of adenoviruses of animal origin is developed to evaluate the level of excretion of these viruses by swine and cattle and to design a test to facilitate the tracing of specific sources of environmental viral contamination. Two sets of oligonucleotides are designed to detect porcine and bovine adenoviruses.

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