Search

Cardiac arrest can lead to severe neurological impairment as a result of inflammation, mitochondrial dysfunction, and post-cardiopulmonary resuscitation neurological damage. Hypoxic preconditioning has been shown to improve migration and survival of bone marrow–derived mesenchymal stem cells and reduce pyroptosis after cardiac arrest, but the specific mechanisms by which hypoxia-preconditioned bone marrow–derived mesenchymal stem cells protect against brain injury after cardiac arrest are unknown. To this end, we established an in vitro co-culture model of bone marrow–derived mesenchymal stem cells and oxygen–glucose deprived primary neurons and found that hypoxic preconditioning enhanced the protective effect of bone marrow stromal stem cells against neuronal pyroptosis, possibly through inhibition of the MAPK and nuclear factor κB pathways. Subsequently, we transplanted hypoxia-preconditioned bone marrow–derived mesenchymal stem cells into the lateral ventricle after the return of spontaneous circulation in an 8-minute cardiac arrest rat model induced by asphyxia. The results showed that hypoxia-preconditioned bone marrow–derived mesenchymal stem cells significantly reduced cardiac arrest–induced neuronal pyroptosis, oxidative stress, and mitochondrial damage, whereas knockdown of the liver isoform of phosphofructokinase in bone marrow–derived mesenchymal stem cells inhibited these effects. To conclude, hypoxia-preconditioned bone marrow–derived mesenchymal stem cells offer a promising therapeutic approach for neuronal injury following cardiac arrest, and their beneficial effects are potentially associated with increased expression of the liver isoform of phosphofructokinase following hypoxic preconditioning.

Abstract Background The Triglyceride glucose (TyG) index-related indicators improve risk stratification by identifying individuals prone to atherosclerosis early in life. This study aimed to examine the relation between TyG-waist circumference-to-height ratio (TyG-WHtR) and coronary heart disease. Methods Data from four National Health and Nutrition Examination Surveys (NHANES) cycles between 2011 and 2018 were used for a cross-sectional study. The association between TyG-WHtR and coronary heart disease risk was examined using a multifactorial logistic regression model, and corresponding subgroup analyses were performed. Nonlinear correlations were analyzed using smooth curve fitting and threshold effects analysis. When nonlinear connections were discovered, appropriate inflection points were investigated using recursive methods. Results TyG-WHtR and coronary heart disease were significantly positively correlated in the multifactorial logistic regression analysis. Subgroup analyses and interaction tests revealed that gender, age, smoking status, and cancer were not significantly associated with this correlation (P for interaction > 0.05). Furthermore, utilizing threshold effect analysis and smooth curve fitting, a nonlinear connection with an inflection point of 0.36 was observed between TyG-WHtR and coronary heart disease. Conclusions According to this study, the American population is far more likely to have coronary heart disease if they have higher TyG-WHtR levels.

Abstract Background The incidence of rebleeding in patients with upper gastrointestinal bleeding (UGIB) remains despite advances in intervention approaches. Therefore, early prediction of the risk of rebleeding could help to greatly reduce the mortality rate in these patients. We aim to develop and validate a new prediction model to predict the probability of rebleeding in patients with AUGIB. Methods A total of 1170 AUGIB patients who completed the procedure of emergency gastroscopy within 48 h of admission were included. Logistic regression analyses were performed to construct a new prediction model. A receiver operating characteristic curve, a line graph, and a calibration and decision curve were used to assess the predictive performance of our new prediction model and compare its performance with that of the AIMS65 scoring system to determine the predictive value of our prediction model. Results A new prediction model was constructed based on Lactic acid (LAC), neutrophil percentage (NEUTP), platelet (PLT), albumin (ALB), and D-DIMER. The AUC values and their 95% confidence interval (CI) for the new prediction model and the AIMS65 score were 0.746 and 0.619, respectively, and 0.697–0.795 and 0.567–0.670, respectively. In the training group, the C index values based on the prediction model and the AIMS65 scoring system were 0.720 and 0.610, respectively. In the validation group, the C index values based on the prediction model and the AIMS65 scoring system were 0.828 and 0.667, respectively. The decision and calibration curve analysis also showed that the prediction model was superior to the AIMS65 scoring system in terms of accuracy of prediction, consistency, and net clinical benefit. Conclusion The prediction model can predict the probability of rebleeding in AUGIB patients after endoscopic hemostasis therapy.

BackgroundThere are limited epidemiological investigations of blood metal levels related to hyperlipidemia, and results indicating the association between blood lead (Pb), cadmium (Cd) and selenium (Se), and lipid biomarkers have been conflicting.MethodsWe included populations for which NHANES collected complete data. Multivariate logistic regression and subgroup analyses were conducted to ascertain the relationship between blood Pb, Cd, and Se levels and hyperlipidemia. Nonlinear relationships were characterized by smoothed curve fitting and threshold effect analysis.Results5429 participants in all, with a mean age of 53.70 ± 16.63 years, were included; 47.1% of the subjects were male, and 3683 (67.8%) of them had hyperlipidemia. After modifying for variables with confounders in a multivariate logistic regression model, we discovered a positive correlation between blood Pb and Se levels and hyperlipidemia (Pb: OR:2.12, 95% CI:1.56-2.88; Se: OR:1.84, 95% CI:1.38-2.45). Gender, age, smoking status, alcohol use status, hypertension, diabetes, and body mass index were not significantly linked with this positive correlation, according to subgroup analysis and interaction test (P for interaction>0.05). Positive correlations between blood Pb, Cd, and Se levels and the risk of hyperlipidemia have been found using smooth curve fitting.ConclusionsThis study demonstrates that higher blood levels of Pb, Cd, and selenium are linked to an increased risk of hyperlipidemia.