Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UNIPROT:P17931 (galectin-3)
 2,860 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Pretreatment of mice with a low hepatotoxic dose of acetaminophen (APAP) results in resistance to a subsequent, higher dose of APAP. This mouse model, termed APAP autoprotection was used here to identify differentially expressed genes and cellular pathways that could contribute to this development of resistance to hepatotoxicity. Male C57BL/6J mice were pretreated with APAP (400mg/kg) and then challenged 48h later with 600mg APAP/kg. Livers were obtained 4 or 24h later and total hepatic RNA was isolated and hybridized to Affymetrix Mouse Genome MU430_2 GeneChip. Statistically significant genes were determined and gene expression changes were also interrogated using the Causal Reasoning Engine (CRE). Extensive literature review narrowed our focus to methionine adenosyl transferase-1 alpha (MAT1A), nuclear factor (erythroid-derived 2)-like 2 (Nrf2), flavin-containing monooxygenase 3 (Fmo3) and galectin-3 (Lgals3). Down-regulation of MAT1A could lead to decreases in S-adenosylmethionine (SAMe), which is known to protect against APAP toxicity. Nrf2 activation is expected to play a role in protective adaptation. Up-regulation of Lgals3, one of the genes supporting the Nrf2 hypothesis, can lead to suppression of apoptosis and reduced mitochondrial dysfunction. Fmo3 induction suggests the involvement of an enzyme not known to metabolize APAP in the development of tolerance to APAP toxicity. Subsequent quantitative RT-PCR and immunochemical analysis confirmed the differential expression of some of these genes in the APAP autoprotection model. In conclusion, our genomics strategy identified cellular pathways that might further explain the molecular basis for APAP autoprotection.
...
PMID:Analysis of changes in hepatic gene expression in a murine model of tolerance to acetaminophen hepatotoxicity (autoprotection). 2412 18

The metabolic changes that accompany changes in Cardiopulmonary testing (CPET) and heart failure biomarkers (HFbio) are not well known. We undertook metabolomic and lipidomic phenotyping of a cohort of heart failure (HF) patients and utilized Multiple Regression Analysis (MRA) to identify associations to CPET and HFBio test performance (peak oxygen consumption (Peak VO2), oxygen uptake efficiency slope (OUES), exercise duration, and minute ventilation-carbon dioxide production slope (VE/VCO2 slope), as well as the established HF biomarkers of inflammation C-reactive protein (CRP), beta-galactoside-binding protein (galectin-3), and N-terminal prohormone of brain natriuretic peptide (NT-proBNP)). A cohort of 49 patients with a left ventricular ejection fraction < 50%, predominantly males African American, presenting a high frequency of diabetes, hyperlipidemia, and hypertension were used in the study. MRA revealed that metabolic models for VE/VCO2 and Peak VO2 were the most fitted models, and the highest predictors' coefficients were from Acylcarnitine C18:2, palmitic acid, citric acid, asparagine, and 3-hydroxybutiric acid. Metabolic Pathway Analysis (MetPA) used predictors to identify the most relevant metabolic pathways associated to the study, aminoacyl-tRNA and amino acid biosynthesis, amino acid metabolism, nitrogen metabolism, pantothenate and CoA biosynthesis, sphingolipid and glycerolipid metabolism, fatty acid biosynthesis, glutathione metabolism, and pentose phosphate pathway (PPP). Metabolite Set Enrichment Analysis (MSEA) found associations of our findings with pre-existing biological knowledge from studies of human plasma metabolism as brain dysfunction and enzyme deficiencies associated with lactic acidosis. Our results indicate a profile of oxidative stress, lactic acidosis, and metabolic syndrome coupled with mitochondria dysfunction in patients with HF tests poor performance. The insights resulting from this study coincides with what has previously been discussed in existing literature thereby supporting the validity of our findings while at the same time characterizing the metabolic underpinning of CPET and HFBio.
 ...
PMID:Metabolic modulation predicts heart failure tests performance. 3122 Jan 3