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metabolomic analysis in MRM mode.&lt;/p></metabolite_identification_protocol><repository>MetaboLights</repository><study_status>Public</study_status><ptm_modification></ptm_modification><instrument_platform>Liquid Chromatography MS - positive - reverse phase</instrument_platform><chromatography_protocol>&lt;p>Agilent 1200 liquid chromatograph; Discovery PFP HS F5 2.1 x 150, 3 µm column (Supelco Inc, St. Louis, Missouri, USA); Waters WAT084560 guard column (Waters Inc. USA); column temperature and the flow rate were set at 40 °C and 0.4 mL/min; The mobile phases consisted of 0.1% formic acid aqueous solution (phase A) and acetonitrile (phase B). The gradient program was as follows: 0.0 min: 1% B; 4.0 min: 10% B; 9.0 min: 90% B; 10.0 min: 90% B; 10.1 min: 1% B; 12.0 min: 1% B.&lt;/p></chromatography_protocol><publication>Targeted metabolomic profiling offor acute ST-segment elevation myocardial infarction pathogenesis.</publication><submitter_affiliation>Sechenov University</submitter_affiliation><submitter_name>Ksenia Shestakova</submitter_name><organism_part>blood plasma</organism_part><technology_type>mass spectrometry</technology_type><disease></disease><extraction_protocol>&lt;p>Sample preparation consisted of liquid-liquid extraction&amp;nbsp;with acetonitrile.&lt;/p></extraction_protocol><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/metabolights/MTBLS10634</full_dataset_link><author>Shestakova Ksenia. kshsochi2014@gmail.com.</author><author>Kseniia Shestakova. Sechenov University. Moscow, Nahimovskiy pr. 45. kshsochi2014@gmail.com. 79175357999.</author><data_transformation_protocol>&lt;p>All data transformations were performed in Chemstation software. All the statistical analyses for the characterization of biochemical and metabolic profiles were performed using the Python Stats package. Variable distribution was assessed using the Shapiro-Wilk test. According to the variable distribution, analysis of variance was performed using parametric Student’s t test and ANOVA or the nonparametric Kruskal-Wallis test and Mann-Whitney U test. After Bonferroni adjustment for multiple comparisons, a p value less than 0.05 was considered to indicate statistical significance. PCA and OPLS-DA analysis was performed using SIMCA-P software. Random forest analysis was performed using Scikit-learn python package.&lt;/p></data_transformation_protocol><study_factor>Disease</study_factor><study_factor>Time</study_factor><submitter_email>kshsochi2014@gmail.com</submitter_email><sample_collection_protocol>&lt;p>The study was conducted at the Belgorod Regional Clinical Hospital of St. Joseph (Russia) among patients with STEMI and myocardial remodeling. The morning after an 12 h-overnight fasting, whole blood samples were collected in ethylenediaminetetraacetic acid (EDTA) tubes. Venous blood samples were collected in the morning following a 12-hour overnight fast,&lt;/p>&lt;p>using tubes containing ethylenediaminetetraacetic acid (EDTA) as an anticoagulant on admission, day 10, day 30 and day 90 after admission. Immediately after collection, the samples were centrifuged at 2000 rpm for 20 minutes at 4 °C to separate the plasma, which was then aliquoted and&lt;/p>&lt;p>stored at -80 °C until analysis. The biochemical evaluation included determination of total cholesterol, triglycerides, HDL- and LDL-cholesterol, glucose, creatinine, urea, alanine aminotransferase (ALT), aspartate aminotransferase (AST), potassium, sodium, calcium, and international normalized ratio (INR).&lt;/p></sample_collection_protocol><omics_type>Metabolomics</omics_type><study_design>ultra-performance liquid chromatography-mass spectrometry</study_design><study_design>targeted metabolites</study_design><study_design>acute myocardial infarction</study_design><curator_keywords>ultra-performance liquid chromatography-mass spectrometry</curator_keywords><curator_keywords>targeted metabolites</curator_keywords><curator_keywords>acute myocardial infarction</curator_keywords><mass_spectrometry_protocol>&lt;p>Positive mode; scan m/z range: 75-444 m/z; Agilent 6450C tandem mass spectrometer; Electrospray ionization; gas temperature: 300 °C; gas flow: 8 L/min; nebulizer gas: 20 psi; sheath gas heater: 300; sheath gas flow rate: 10 L/min; capillary voltage: 3500 kV; MRM transition mode,&lt;/p></mass_spectrometry_protocol></additional><is_claimable>false</is_claimable><name>Targeted metabolomic profiling of myocardial remodeling after STEMI</name><description>&lt;p> Early detection of myocardial remodeling is essential for optimizing outcomes in patients with ST-segment elevation myocardial infarction (STEMI). However, reliable biomarkers for predicting STEMI myocardial remodeling remain scarce.&lt;/p>&lt;p> Targeted metabolomic profiling was performed on plasma samples from 61 STEMI patients: six patients with anterior STEMI with remodeling, 26 patients with anterior STEMI without remodeling and 29 patients with inferior STEMI. Quantitative analysis included 87 endogenous metabolites.&lt;/p>&lt;p> Several metabolite classes were identified as informative markers of STEMI myocardial remodeling. It was found, that nine metabolites had significant differences in STEMI patients with remodeling and without remodeling. Collagenogenic amino acids (proline, lysine) showed a marked elevation on baseline and may reflect early fibrotic activity. Gamma-aminobutyric acid and cystationine had demonstrated a strong correlation with left ventricle wall thickness and fibrous ring of the mitral valve. Branched-chain amino acids (valine) showed a significant decrease that may suggest a shift in energy metabolism in STEMI. ADMA was increased significantly in patients with remodeling which may be linked to cellular damage and impaired nitric oxide signaling. Decreased acylcarnitine (C0) indicates mismatch between fatty acid mobilization and mitochondrial oxidation in STEMI patients with remodeling. Thus, increased proline, decreased GABA and C0 levels, as well as increased ADMA : Gly, ADMA : Ser, Ala : Glu ratios may be a potential biochemical predictors of myocardial remodeling, which may be considered as a target for a future therapeutic approach.&lt;/p>&lt;p> This study highlights key metabolic alterations associated with STEMI myocardial remodeling. Taken together, these insights offer a promising foundation for the development of robust, minimally invasive, and potentially automatable blood-based tools for early prediction of myocardial remodeling.&lt;/p></description><dates><publication>2025-09-02</publication><submission>2025-09-02</submission></dates><accession>MTBLS10634</accession><cross_references/></HashMap>