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Background: The majority of diabetic cats in remission have abnormal glucose tolerance, and approximately one third relapse within 1 year. Greater understanding of the metabolic characteristics of diabetic cats in remission, and predictors of relapse is required to effectively monitor and manage these cats. Objectives: To identify and compare differences in plasma metabolites between diabetic cats in remission and healthy control cats using a metabolomics approach. Secondly, to assess whether identified metabolites are predictors of diabetic relapse. Animals: Twenty cats in diabetic remission for a median of 101 days, and 22 healthy matched control cats. Methods: Cats were admitted to a clinic, and casual blood glucose was recorded. After a 24 h fast, blood glucose concentration was measured, then a blood sample was taken for metabolomic (GCMS and LCMS) analyses. Three hours later, a simplified intravenous glucose tolerance test (1 g glucose/kg) was performed. Cats were monitored for diabetes relapse for at least 9 months (270 days) after baseline testing. Results: Most cats in remission continued to display impaired glucose tolerance. Concentrations of 16 identified metabolites differed (P ≤ 0.05) between remission and control cats: 10 amino acids and stearic acid (all lower in remission cats), and glucose, glycine, xylitol, urea and carnitine (all higher in remission cats). Moderately close correlations were found between these 16 metabolites and variables assessing glycaemic responses (most |r| = 0.31 to 0.69). Five cats in remission relapsed during the study period. No metabolite was identified as a predictor of relapse. Conclusion and clinical importance: This study shows that cats in diabetic remission have abnormal metabolism.
Pubmed ID: 32500084 RIS Download
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A multi-institutional effort to identify and quantitate, using a systems biology approach and sophisticated mass spectrometers, all of the major - and many minor - lipid species in mammalian cells, as well as to quantitate the changes in these species in response to perturbation. The goal of their research is to better understand lipid metabolism and the active role lipids play in diabetes, stroke, cancer, arthritis, Alzheimer's and other lipid-based diseases in order to facilitate development of more effective treatments. Resources available include: LIPID MAPS publications, detailed biochemical pathways, improved protocols for lipid separation and quantification, analytical tools for determining lipid quantitation, structure drawing tools for automatically drawing lipid molecular structures in stereochemical detail, and experimental data. The LIPID MAPS organization includes six lipidomics core laboratories, each specialized in extracting, identifying, and quantifying one of the major categories of mammalian lipids: fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids, and prenol lipids. Other core laboratories and bridge projects include bioinformatics, mass spectrometric imaging, lipid synthesis, oxidized lipids, and macrophage biology and genomics.
View all literature mentionsA public repository of metabolite information as well as tandem mass spectrometry data is provided to facilitate metabolomics experiments. It contains structures and represents a data management system designed to assist in a broad array of metabolite research and metabolite identification. An annotated list of known metabolites and their mass, chemical formula, and structure are available. Each metabolite is linked to outside resources for further reference and inquiry. MS/MS data is also available on many of the metabolites.
View all literature mentionsSoftware tools for compound-centric data mining and navigation. Used to identify compounds in overlapping and co-eluting peaks with feature extraction and correlation algorithms for chromatographic separation. Used for separating true signals from noise.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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