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Biomedical subjects

Hiren Patel

Publications and source records attributed to Hiren Patel.

5 recordsLinked to original sources
PubMed2003

2HAPI: a microarray data analysis system.

SUMMARY: 2HAPI (version 2 of High density Array Pattern Interpreter) is a web-based, publicly-available analytical tool designed to aid researchers in microarray data analysis. 2HAPI includes tools for searching, manipulating, visualizing, and clustering the large sets of data generated by microarray experiments. Other features include association of genes with NCBI information and linkage to external data resources. Unique to 2HAPI is the ability to retrieve upstream sequences of co-regulated genes for promoter analysis using MEME (Multiple Expectation-maximization for Motif Elicitation) AVAILABILITY: 2HAPI is freely available at http://array.sdsc.edu. Users can try 2HAPI anonymously with pre-loaded data or they can register as a 2HAPI user and upload their data.

Algorithms↗
PubMed2003

Angiotensin-converting enzyme inhibition induces death receptor apoptotic pathways in erythroid precursors following renal transplantation.

BACKGROUND: Posttransplant erythrocytosis (PTE) is a condition that occurs in kidney transplant patients and is characterized by increase in hematocrit above 51%. While its pathogenesis remains unclear, angiotensin-converting enzyme inhibitors (ACEI) have been used successfully in the treatment of PTE. We have previously shown that ACEI induce apoptosis in the peripheral erythroid precursors from patients with PTE. In the current study we elucidate the molecular mechanisms of ACEI-induced apoptosis. METHODS: Peripheral CD34+ cells were obtained from four normal controls, five normal kidney transplants, and six kidney transplants with PTE, before and after treatment with ACEI. We evaluated the expression of a variety of apoptotic factors by quantitative reverse transcription-multiplex polymerase chain reaction, Western blot and immunocytochemistry. RESULTS: ACEI resulted in a significant induction of Fas, FADD, and TRADD mRNAs in renal transplant patients with or without PTE. No changes were noted in the expression of mRNAs encoding Bcl-2, Bcl-xL, Bax, caspase 8, caspase 3, or GAPDH. ACEI also resulted in a significant upregulation of Fas, FADD and TRADD protein expression, and their localization predominantly at the plasma membrane. CONCLUSIONS: Our results suggest that ACEI therapy induces apoptosis in erythrocyte progenitor cells of renal transplant patients at least in part via induction of death receptor apoptotic cascades.

Adaptor Proteins, Signal Transducing↗
PubMed2002

Quantitative structure-activity relationships (QSARs) for the prediction of skin permeation of exogenous chemicals.

Quantitative structure-activity relationships (QSARs) for the skin permeability coefficients of 158 compounds through excised human skin in vitro have been developed. A number of compounds, including hydrocortisone derivatives, were removed from the dataset as reported permeability data for these compounds was considered to be in error. QSARs developed for the dataset with the outliers removed included terms for hydrophobicity, molecular size, and hydrogen bonding. These descriptors provided an excellent fit to the data (r2 = 0.90), are easily calculated from molecular structure, and are mechanistically interpretable. Further analyses of the dataset indicated that good QSARs could be developed utilising hydrophobicity and molecular size alone, with molecular volume and molecular weight providing good quantification of molecular size.

Culture Techniques↗
PubMedDate not supplied

Structure-based classification of antibacterial activity.

The aim of this study was to develop a simple quantitative structure-activity relationship (QSAR) for the classification and prediction of antibacterial activity, so as to enable in silico screening. To this end a database of 661 compounds, classified according to whether they had antibacterial activity, and for which a total of 167 physicochemical and structural descriptors were calculated, was analyzed. To identify descriptors that allowed separation of the two classes (i.e. those compounds with and without antibacterial activity), analysis of variance was utilized and models were developed using linear discriminant and binary logistic regression analyses. Model predictivity was assessed and validated by the random removal of 30% of the compounds to form a test set, for which predictions were made from the model. The results of the analyses indicated that six descriptors, accounting for hydrophobicity and inter- and intramolecular hydrogen bonding, provided excellent separation of the data. Logistic regression analysis was shown to model the data slightly more accurately than discriminant analysis.

Anti-Bacterial Agents↗