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Full-Text Articles in Medicine and Health Sciences
Comparison Of Protein Phosphatase Inhibition Assay With Lc-Ms/Ms For Diagnosis Of Microcystin Toxicosis In Veterinary Cases, Caroline E. Moore, Jeanette Juan, Yanping Lin, Cynthia L. Gaskill, Birgit Puschner
Comparison Of Protein Phosphatase Inhibition Assay With Lc-Ms/Ms For Diagnosis Of Microcystin Toxicosis In Veterinary Cases, Caroline E. Moore, Jeanette Juan, Yanping Lin, Cynthia L. Gaskill, Birgit Puschner
Veterinary Diagnostic Laboratory Faculty Publications
Microcystins are acute hepatotoxins of increasing global concern in drinking and recreational waters and are a major health risk to humans and animals. Produced by cyanobacteria, microcystins inhibit serine/threonine protein phosphatase 1 (PP1). A cost-effective PP1 assay using p-nitrophenyl phosphate was developed to quickly assess water and rumen content samples. Significant inhibition was determined via a linear model, which compared increasing volumes of sample to the log-transformed ratio of the exposed rate over the control rate of PP1 activity. To test the usefulness of this model in diagnostic case investigations, samples from two veterinary cases were tested. In August …
Multiple Subject Barycentric Discriminant Analysis (Musubada): How To Assign Scans To Categories Without Using Spatial Normalization, Hervé Abdi, Lynne J. Williams, Andrew C. Connolly, M. Ida Gobbini
Multiple Subject Barycentric Discriminant Analysis (Musubada): How To Assign Scans To Categories Without Using Spatial Normalization, Hervé Abdi, Lynne J. Williams, Andrew C. Connolly, M. Ida Gobbini
Dartmouth Scholarship
We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant Analysis (MUSUBADA) suited for analyzing fMRI data because it handles datasets with multiple participants that each provides different number of variables (i.e., voxels) that are themselves grouped into regions of interest (ROIs). Like DA, MUSUBADA (1) assigns observations to predefined categories, (2) gives factorial maps displaying observations and categories, and (3) optimally assigns observations to categories. MUSUBADA handles cases with more variables than observations and can project portions of the data table (e.g., subtables, which can represent participants or ROIs) on the factorial maps. Therefore MUSUBADA can …