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Articles 1 - 6 of 6
Full-Text Articles in Medicine and Health Sciences
Analyzing And Mapping Sweat Metabolomics By High-Resolution Nmr Spectroscopy, Viktor P. Kutyshenko, Maxim Molchanov, Peter Beskaravayny, Vladimir N. Uversky, Maria A. Timchenko
Analyzing And Mapping Sweat Metabolomics By High-Resolution Nmr Spectroscopy, Viktor P. Kutyshenko, Maxim Molchanov, Peter Beskaravayny, Vladimir N. Uversky, Maria A. Timchenko
Molecular Medicine Faculty Publications
The content of human sweat is studied by high-resolution NMR, and the majority of organic components most often found in sweat of conditionally healthy people are identified. Original and simple tools are designed for sweat sampling from different areas of human body. The minimal surface area needed for sampling is in the range of 50–100 cm2. On all the surface parts of the human body examined in this work, the main constituents forming a sweat metabolic profile are lactate, glycerol, pyruvate, and serine. The only exception is the sole of the foot (planta pedis), where trace amounts of …
Mechanism Of Resistance To Dietary Cholesterol, Lindsey R. Boone, Patricia A. Brooks, Melissa I. Niesen, Gene C. Ness
Mechanism Of Resistance To Dietary Cholesterol, Lindsey R. Boone, Patricia A. Brooks, Melissa I. Niesen, Gene C. Ness
Molecular Medicine Faculty Publications
Background. Alterations in expression of hepatic genes that could contribute to resistance to dietary cholesterol were investigated in Sprague-Dawley rats, which are known to be resistant to the serum cholesterol raising action of dietary cholesterol. Methods. Microarray analysis was used to provide a comprehensive analysis of changes in hepatic gene expression in rats in response to dietary cholesterol. Changes were confirmed by RT-PCR analysis. Western blotting was employed to measure changes in hepatic cholesterol 7α hydroxylase protein. Results. Of the 28,000 genes examined using the Affymetrix rat microarray, relatively few were significantly altered. As expected, decreases …
In-Silico Prediction Of Disorder Content Using Hybrid Sequence Representation, Marcin J. Mizianty, Tuo Zhang, Bin Xue, Yaoqi Zhou, A. Keith Dunker, Vladimir N. Uversky, Lukasz Kurgan
In-Silico Prediction Of Disorder Content Using Hybrid Sequence Representation, Marcin J. Mizianty, Tuo Zhang, Bin Xue, Yaoqi Zhou, A. Keith Dunker, Vladimir N. Uversky, Lukasz Kurgan
Molecular Medicine Faculty Publications
Background: Intrinsically disordered proteins play important roles in various cellular activities and their prevalence was implicated in a number of human diseases. The knowledge of the content of the intrinsic disorder in proteins is useful for a variety of studies including estimation of the abundance of disorder in protein families, classes, and complete proteomes, and for the analysis of disorder-related protein functions. The above investigations currently utilize the disorder content derived from the per-residue disorder predictions. We show that these predictions may over-or under-predict the overall amount of disorder, which motivates development of novel tools for direct and accurate sequence-based …
Predictive Power Estimation Algorithm (Ppea) - A New Algorithm To Reduce Overfitting For Genomic Biomarker Discovery, Jiangang Liu, Robert A. Jolly, Aaron T. Smith, George H. Searfoss, Keith M. Goldstein, Vladimir N. Uversky, Keith Dunker, Shuyu Li, Craig E. Thomas, Tao Wei
Predictive Power Estimation Algorithm (Ppea) - A New Algorithm To Reduce Overfitting For Genomic Biomarker Discovery, Jiangang Liu, Robert A. Jolly, Aaron T. Smith, George H. Searfoss, Keith M. Goldstein, Vladimir N. Uversky, Keith Dunker, Shuyu Li, Craig E. Thomas, Tao Wei
Molecular Medicine Faculty Publications
Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through …
Effects Of Hmgn Variants On The Cellular Transcription Profile, Mark Rochman, Leila Taher, Toshihiro Kurahashi, Srujana Cherukuri, Vladimir N. Uversky, David Landsman, Ivan Ovcharenko, Michael Bustin
Effects Of Hmgn Variants On The Cellular Transcription Profile, Mark Rochman, Leila Taher, Toshihiro Kurahashi, Srujana Cherukuri, Vladimir N. Uversky, David Landsman, Ivan Ovcharenko, Michael Bustin
Molecular Medicine Faculty Publications
High mobility group N (HMGN) is a family of intrinsically disordered nuclear proteins that bind to nucleosomes, alters the structure of chromatin and affects transcription. A major unresolved question is the extent of functional specificity, or redundancy, between the various members of the HMGN protein family. Here, we analyze the transcriptional profile of cells in which the expression of various HMGN proteins has been either deleted or doubled. We find that both up- and downregulation of HMGN expression altered the cellular transcription profile. Most, but not all of the changes were variant specific, suggesting limited redundancy in transcriptional regulation. Analysis …
Modulating Α-Synuclein Misfolding And Fibrillation In Vitro By Agrochemicals, Blanca A. Silva, Olöf Einarsdóttir, Anthony L. Fink, Vladimir N. Uversky
Modulating Α-Synuclein Misfolding And Fibrillation In Vitro By Agrochemicals, Blanca A. Silva, Olöf Einarsdóttir, Anthony L. Fink, Vladimir N. Uversky
Molecular Medicine Faculty Publications
A combination of spectroscopic techniques including atomic force microscopy (AFM) and transmission electron microscopy (TEM), was used to analyze the effect of chemically distinct agrochemicals (pesticides, herbicides, and fungicides) on the in vitro misfolding and aggregation of a presynaptic intrinsically disordered protein α-synuclein. Despite their differences in chemical properties, almost all the compounds screened affected the α-synuclein fibrillation in a concentration-dependent manner. The morphology of the aggregated α-synuclein was characterized by AFM and TEM techniques. In addition to typical fibrils abundantly found at the equilibrium phase, this analysis revealed the existence of a noticeable nonfibrillar fraction where α-synuclein was present …