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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Animals, Coronary Angiography, Coronary Disease, Disease Models, Animal, Electrocardiography, Gas Chromatography-Mass Spectrometry, Hemorheology, Metabolome, Metabolomics, Principal Component Analysis, Sus scrofa, Tricarboxylic Acids.
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Does metabolomic profiling reveal distinct patterns of tricarboxylic acid disorders in blood stasis syndrome associated with coronary heart disease? Context: To investigate the underlying metabolomic profifiling of coronary heart disease (CHD) with blood stasis syndrome (BSS). CHD model was induced by a nameroid constrictor in Chinese miniature swine. Fifteen miniature swine were randomly divided into a model group (n=9) and a control group (n=6), respectively according to arandom number table. After 4 weeks, plasma hemorheology was detected by automatic hemorheological analyzer, indices including hematocrit, plasma viscosity, blood viscosity, rigidity index and erythrocyte sedimentation rate; cardiac function was assessed by echocardiograph to detect left ventricular end-systolic diameter (LVED), left ventricular end-diastolic diameter (LVEDd), ejection fraction (EF), fractional shortening (FS) and other indicators. Gas chromatography coupled with mass spectrometry (GC-MS) and bioinformatics were applied to analyze spectra of CHD plasma with BSS. The results of hemorheology analysis showed signifificant changes in viscosity, with low shear whole blood viscosity being lower and plasma viscosity higher in the model group compared with the control group. Moreover, whole blood reduction viscosity at high shear rate and whole blood reduction viscosity at low shear rate increased signifificantly (P <0.05). The echocardiograph results demonstrated that cardiac EF and FS showed signifificant difference (P <0.05), with EF values being decreased to 50% or less. The GC-MS data showed that principal component analysis can clearly separate the animals with BSS from those in the control group. The enriched Kyoto Encyclopedia of Genes and Genomes biological pathways results suggested that the patterns involved were associated with dysfunction of energy metabolism including glucose and lipid disorders, especially in glycolysis/gluconeogenesis, galactose metabolism and adenosine-triphosphate-binding cassette transporters.
assistant
Glucose metabolism and lipid metabolism disorders were the major contributors to the syndrome classifification of CHD with BSS. Final Decision: yes