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Full-Text Articles in Life Sciences
Liver Perilipin 5 Expression Worsens Hepatosteatosis But Not Insulin Resistance In High Fat-Fed Mice, Michelle B. Trevino, David Mazur-Hart, Yui Machida, Timothy King, Joseph Nadler, Elena V. Galkina, Arjun Poddar, Sucharita Dutta, Yumi Imai
Liver Perilipin 5 Expression Worsens Hepatosteatosis But Not Insulin Resistance In High Fat-Fed Mice, Michelle B. Trevino, David Mazur-Hart, Yui Machida, Timothy King, Joseph Nadler, Elena V. Galkina, Arjun Poddar, Sucharita Dutta, Yumi Imai
Mathematics & Statistics Faculty Publications
Perilipin 5 (PLIN5) is a lipid droplet (LD) protein highly expressed in oxidative tissues, including the fasted liver. However, its expression also increases in nonalcoholic fatty liver. To determine whether PLIN5 regulates metabolic phenotypes of hepatosteatosis under nutritional excess, liver targeted overexpression of PLIN5 was achieved using adenoviral vector (Ad-PLIN5) in male C57BL/6J mice fed high-fat diet. Mice treated with adenovirus expressing green fluorescent protein (GFP) (Ad-GFP) served as control. Ad-PLIN5 livers increased LD in the liver section, and liquid chromatography with tandem mass spectrometry revealed increases in lipid classes associated with LD, including triacylglycerol, cholesterol ester, and phospholipid classes, …
Computational Protein Biomarker Prediction: A Case Study For Prostate Cancer, Michael Wagner, Dayanand N. Naik, Alex Pothen, Srinivas Kasukurti, Raghu Ram Devineni, Bao-Ling Adam, O. John Semmes, George L. Wright Jr.
Computational Protein Biomarker Prediction: A Case Study For Prostate Cancer, Michael Wagner, Dayanand N. Naik, Alex Pothen, Srinivas Kasukurti, Raghu Ram Devineni, Bao-Ling Adam, O. John Semmes, George L. Wright Jr.
Mathematics & Statistics Faculty Publications
Background: Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates.
Results: Thorough cross-validation studies and randomization tests are performed on a prostate cancer dataset with over 300 patients, obtained …
Protocols For Disease Classification From Mass Spectrometry Data, Michael Wagner, Dayanand Naik, Alex Pothen
Protocols For Disease Classification From Mass Spectrometry Data, Michael Wagner, Dayanand Naik, Alex Pothen
Mathematics & Statistics Faculty Publications
We report our results in classifying protein matrix-assisted laser desorption/ionizationtime of flight mass spectra obtained from serum samples into diseased and healthy groups. We discuss in detail five of the steps in preprocessing the mass spectral data for biomarker discovery, as well as our criterion for choosing a small set of peaks for classifying the samples. Cross-validation studies with four selected proteins yielded misclassification rates in the 10-15% range for all the classification methods. Three of these proteins or protein fragments are down-regulated and one up-regulated in lung cancer, the disease under consideration in this data set. When cross-validation studies …