High-altitude hypoxia has long been recognized as a vital etiology for high-altitude illnesses. High-altitude myocardial injury (HAMI) usually occurs in people who suffered from high-altitude exposure. To date, the molecular mechanism of HAMI remains elusive, which seriously hinders the prevention and treatment of HAMI. L-carnitine and trimetazidine are classic cardiovascular protective medicines. In this study, we used the metabolomic method, based on GC/MS, to explore the changes in metabolites in rats exposed to high-altitude hypoxia and then illustrate the metabolic pathways associated with the modulatory effect of L-carnitine combined with trimetazidine on rats with high-altitude exposure. The results showed that metabolites in the myocardium in rats under high-altitude hypoxia were markedly changed, such as branched-chain amino acids (BCAA, leucine, isoleucine, and valine), taurine, succinic acid, fumaric acid, lactic acid, pyruvic acid, 3-hydroxybutyrate, and docosahexaenoic acid (DHA), while L-carnitine combined with trimetazidine modulated and improved the abnormal changes in energy substances caused by high-altitude hypoxia. L-carnitine mainly promoted the metabolism of fatty acids, while trimetazidine enhanced the glycolysis process. The combined administration of the two components not only increased the metabolism of fatty acids but also promoted aerobic glycolysis. Meanwhile, it contributed to the decrease in the elevation in some of the intermediates of the tricarboxylic acid (TCA) cycle, decrease in the production of 3-hydroxybutyric acid, and relief of the abnormal energy metabolism process in organisms and the cardiac tissue. Our analysis delineates the landscape of the metabolites in the myocardial tissue of rats that were exposed to high altitude. Moreover, L-carnitine combined with trimetazidine can relieve the HAMI through modulated and improved abnormal changes in energy substances caused by high-altitude hypoxia.
acute myocardial infarction (aMi) is a major cause of heart failure and is associated with insufficient myocardial oxygen supply. However, the molecular mechanisms underlying hypoxia-induced cardiomyocyte apoptosis are not completely understood. in the present study, the role of human coilin interacting nuclear aTPase protein (hcinaP) in cardiomyocytes was investigated. ac16 cells were divided into the following four groups: i) Small interfering (si) rna-control (ctrl); (ii) sirna-hcinaP; (iii) empty vector; and (iv) hcinaP-Flag. Protein expression was assessed using western blotting. MTT and apoptosis assays were conducted to detect cell viability and apoptosis, respectively. ccK8 assays and apoptosis assays were used to detect cell viability and apoptosis, respectively. hcinaP promoter activity was examined by luciferase reporter assay. hcinaP expression was induced in a hypoxia-inducible factor-1α-dependent manner under hypoxic conditions. compared with the sirna-ctrl group, hcinaP knockdown inhibited apoptosis, whereas compared with the vector group, hcinaP overexpression increased apoptosis under hypoxic conditions. Mechanistically, compared with the sirna-ctrl group, hcinaP knockdown decreased hypoxia-induced lactate accumulation via regulating lactate dehydrogenase a activity. Moreover, the results indicated that hcinaP was associated with mitochondrial-mediated apoptosis via caspase signaling. collectively, the present study suggested that hcinaP was an important regulator in hypoxia-induced apoptosis and may serve as a promising therapeutic target for aMi.
Background: According to the Global Tuberculosis Report for three consecutive years, tuberculosis (TB) is the second leading infectious killer. Primary pulmonary tuberculosis( PTB) leads to the highest mortality among TB diseases. Regretfully,no previous studies targeted the PTB of a specific type or in a specific course, so models established in previous studies cannot be accurately feasible for clinical treatments.This study aimed to construct a nomogram prognostic model to quickly recognize death-related risk factors in patients initially diagnosed with PTB to intervene and treat high-risk patients as early as possible in the clinic to reduce mortality. Methods: We retrospectively analyzed the clinical data of 1,809 in-hospital patients initially diagnosed with primary PTB at Hunan Chest Hospital from January 1, 2019, to December 31, 2019. Binary logistic regression analysis was used to identify the risk factors. A nomogram prognostic model for mortality prediction was constructed using R software and was validated using a validation set. Results: Univariate and multivariate logistic regression analyses revealed that drinking, hepatitis B virus (HBV), body mass index (BMI), age, albumin (ALB), and hemoglobin (Hb) were six independent predictors of death in in-hospital patients initially diagnosed with primary PTB. Based on these predictors, a nomogram prognostic model was established with high prediction accuracy, of which the area under the curve (AUC) was 0.881 (95% confidence interval [Cl]: 0.777-0.847), the sensitivity was 84.7%, and the specificity was 77.7%internal and external validations confirmed that the constructed model fit the real situation well. Conclusion: The constructed nomogram prognostic model can recognize risk factors and accurately predict the mortality of patients initially diagnosed with primary PTB. This is expected to guide early clinical intervention and treatment for high-risk patients.
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