Background. Diabetes mellitus (DM) can induce cardiomyocyte injury and lead to diabetic cardiomyopathy (DCM) which presently has no specific treatments and consequently increase risk of mortality. Objective. To characterize the therapeutic effect of 6‐gingerol (6‐G) on DCM and identify its potential mechanism. Methods. In vivo streptozotocin‐ (STZ‐) induced DM model was established by using a high‐fat diet and STZ, followed by low‐dose (25 mg/kg) and high‐dose (75 mg/kg) 6‐G intervention. For an in vitro DCM model, H9c2 rat cardiomyoblast cells were stimulated with high glucose (glucose = 33 mM) and palmitic acid (100 μM) and then treated with 6‐G (100 μM). Histological and echocardiographic analyses were used to assess the effect of 6‐G on cardiac structure and function in DCM. Western blotting, ELISA, and real‐time qPCR were used to assess the expression of ferroptosis, inflammation, and the Nrf2/HO‐1 pathway‐related proteins and RNAs. Protein expression of collagen I and collagen III was assessed by immunohistochemistry, and kits were used to assay SOD, MDA, and iron levels. Results. The results showed that 6‐G decreased cardiac injury in both mouse and cell models of DCM. The cardiomyocyte hypertrophy and interstitial fibrosis were attenuated by 6‐G treatment in vivo and resulted in an improved heart function. 6‐G inhibited the expression of ferroptosis‐related protein FACL4 and the content of iron and enhanced the expression of anti‐ferroptosis‐related protein GPX4. In addition, 6‐G also diminished the secretion of inflammatory cytokines, including IL‐1β, IL‐6, and TNF‐α. 6‐G treatment activated the Nrf2/HO‐1 pathway, enhanced antioxidative stress capacity proved by increased activity of SOD, and decreased MDA production. Compared with in vivo, 6‐G treatment of H9c2 cells treated with high glucose and palmitic acid could produce a similar effect. Conclusion. These findings suggest that 6‐G could protect against DCM by the mechanism of ferroptosis inhibition and inflammation reduction via enhancing the Nrf2/HO‐1 pathway.

Recent investigations have proposed a potential causal association between the occurrence of ferroptosis, nuclear factor kappa B (NF-κB) and ubiquitin-specific protease 24 (USP24). Nevertheless, the mechanism of USP24 and NF-κB regulation of ferroptosis in the context of diabetic cardiomyopathy (DCM) remain unclear. In this study, a high-fat diet and a streptozotocin-induced mouse DCM model were established, and high glucose and palmitic acid treatment of H9c2 cells and neonatal mouse primary cardiomyocytes (NMPCs) was used as an in vitro DCM models. Utilizing both the in vivo and in vitro DCM models, we assessed of USP24, NF-κB, and ferroptosis levels, and explored the relationship among them. In in vivo and in vitro DCM models, increased expression of USP24, NF-κB, phosphorylated NF-κB (p-NF-κB) and fatty acid-CoA ligase 4 (FACL4) were detected, along with accumulated iron, as well as reduced ferritin heavy chain 1 (FTH1), solute carrier family 7 member 11 (SLC7A11) and antioxidant capacity. Knockdown of USP24 resulted in a reduction of NF-κB levels, while knockdown of NF-κB did not lead to a decrease in USP24 expression. Moreover, in H9c2 cells, knockdown of USP24 and NF-κB separately resulted in reduced levels of FACL4, increased levels of SLC7A11 and FTH1, as well as improved antioxidant capacity and cell viability. In shUSP24 knockdown H9c2 cells, administration of phorbol 12-myristate 13-acetate (PMA) activated NF-κB, subsequently reversing the previously observed effect caused by USP24 knockdown. These findings show that USP24 upregulates NF-κB to promote ferroptosis in DCM.

Background: To date, no studies have investigated the correlation between the neutrophil-to-lymphocyte ratio (NLR) and the long-term risk of mortality in individuals with both coronary heart disease (CHD) and hypertension. This study aims to evaluate the association between NLR and all-cause and cardiovascular mortality among this patient population.Methods: National Death Index (NDI) and National Health and Nutrition Examination Survey (NHANES 2001–2018) were the data sources. A nonlinear association between the NLR and mortality risk was shown by restricted cubic spline (RCS) analysis. Using a weighted Cox proportional hazards model, we quantitatively evaluated the effect of NLR on mortality risk.The capacity of NLR to forecast survival was assessed by evaluating time-dependent receiver operating characteristic (ROC) curves. A mediating influence analysis was conducted to assess the influence of NLR on mortality through eGFR as a mediator.Results: The study involved a total of 2136 individuals. During the median follow-up interval of 76.0 months, 801 deaths were recorded. The RCS analysis showed NLR and mortality risk to have a nonlinear relationship. Two groups were established based on the participants’ NLR levels: a group with high NLR (NLR > 2.65) and a group with low NLR (NLR < 2.65). After adjusting for potential confounding factors, the Cox proportional hazards model revealed that participants with an increased NLR faced a significantly higher risk of cardiovascular mortality. (HR 1.58, 95% CI 1.33–1.82, p < 0.0001) and all-cause mortality (HR 1.46, 95% CI 1.30–1.62, p < 0.0001). An analysis of interactions and data stratification corroborated the validity of our findings. eGFR was identified as a partial mediator in the association between NLR and mortality rates, contributing 12.17% and 9.66% of the variance in all-cause and cardiovascular mortality, respectively. The predictive performance for cardiovascular mortality was quantified using ROC curves, with respective AUC values of 0.67, 0.65, and 0.64 for predictions over 3, 5, and 10 years. The AUC values for all-cause mortality were 0.66, 0.64, and 0.63 for the same time frames.Conclusion: For patients with CHD and hypertension, an elevated NLR serves as an independent prognostic indicator for both all-cause and cardiovascular mortality.

As modern medicine began to emerge at the turn of the 20th century, glycan-based therapies advanced. DNA- and protein-centered therapies became widely available. The research and development of structurally defined carbohydrates have led to new tools and methods that have sparked interest in the therapeutic applications of glycans. One of the latest omics disciplines to emerge in the contemporary post-genomics age is glycomics. In addition, to providing hope for patients and people with different health conditions through a deeper understanding of the mechanisms of common complex diseases, this new specialty in system sciences has much to offer to communities involved in the development of diagnostics and therapeutics in medicine and life sciences.This review focuses on recent developments that have pushed glycan-based therapies into the spotlight in medicine and the technologies powering these initiatives, which we can take as the most significant success of the 21st century.

Background: The relationship of the first-trimester triglyceride-glucose (TyG) index with GDM (gestational diabetes mellitus) and other adverse pregnancy outcomes has yet to be fully understood. This study aims to investigate the relationship between the first-trimester TyG index and the risk of adverse pregnancy outcomes in pregnant women. Methods: The data for the retrospective cohort study were derived from the Maternal and Child Health Hospital of Longgang District, Shenzhen, China. To calculate the TyG index, health indicators were measured in the early pregnancy period (<14 gestational weeks), including triglycerides and fasting blood glucose levels in pregnant women. Multivariable regression analysis and subgroup analysis were used to ascertain the independent association between the TyG index and the possibility of adverse pregnancy outcomes. Interaction analysis was performed to assess the potential heterogeneity of associations among subgroups. Nonlinear associations and the predictive value of the TyG index were explored using restricted cubic splines and receiver operating characteristic (ROC) curves. The discrimination and accuracy of the fully adjusted model were evaluated using calibration curves, Brier scores, and decision curve analysis (DCA). Mediation analysis was conducted to assess the impact of GDM (gestational diabetes mellitus) and PE (preeclampsia) as intermediaries on the risk of Preterm delivery. Results: The study included a cohort of 11,942 pregnant women, with an average TyG index of 8.36 ± 0.41. Logistic regression analysis showed that after adjusting for covariates, for each 1-unit increase in the TyG index, the risk of GDM increased by 2.21-fold, and this result was significantly different across all quartiles. Compared to the lowest quartile group, the highest TyG index group had the highest risk of PE (OR: 2.89; 95% CI 1.39 ~ 6.50), GH (gestational hypertension) (OR: 1.47; 95% CI 1.07 ~ 2.02), and Preterm delivery (OR: 1.75; 95% CI 1.21 ~ 2.56).The analysis of data stratification and interaction confirmed the validity of our study results. However, the analysis found no statistically significant association between the TyG index and low birth weight and macrosomia. GDM and PE were identified as partial mediating factors between TyG and the risk of preterm delivery, with variance contributions of 7.23% and 20.33%. The TyG index demonstrated the highest area under the curve (AUC) values in the ROC curves for GDM, PE, GH, and preterm delivery, with values of 0.61, 0.67, 0.58, and 0.56, respectively. The combination of the TyG index, maternal age, and pre-pregnancy body mass index predicted outcomes better than the TyG index alone (p < 0.01).After adjustment for confounders, the model showed good accuracy and net benefit in predicting adverse pregnancy outcomes, as supported by calibration curves, Brier scores, and decision curve analysis. Conclusion: An elevated first-trimester TyG index correlates with a heightened risk of GDM, PE, GH and Preterm delivery.The TyG index presents a promising tool for more effectively identifying populations at early risk for adverse pregnancy outcomes.

Electrocardiogram (ECG) is commonly used clinically due to convenience, but its accuracy is insufficient for left ventricular hypertrophy (LVH) diagnosis. In this study, we attempted to improve diagnostic accuracy of LVH by establishing models with ECG parameters. Eighty hundred and twenty eight patients were recruited in the present study which were divided into groups according to gender, age and body mass index (BMI). The sensitivity, specificity, Youden index, positive predictive value, negative predictive value and accuracy were calculated using ultrasonic cardiogram criteria of LVH as the gold standard. Area under the curve was also calculated to assess the diagnostic accuracy of 22 conventional ECG criteria in different groups. Stepwise discriminant analyses were performed to establish models of ECG for LVH. The diagnostic accuracy of ECG11 (S V2 + R V5,6) and ECG12 (S V1,2 + R V5,6) was significantly higher than the other 20 criteria, while ECG15 (R V5/R V6) was lowest. The ECG12 sensitivity for males was 52.5%, for <60 years old was 44.2%, and for BMI <25 kg/m2 was 46.2%,higher than for females (27.5%), for ≧60 years old (35.7%), and for BMI ≧25 kg/m2(27.6%), respectively. The difference between genders was the most obvious. Based on these observations, the following models for males and females were established: $$ {\displaystyle \begin{array}{c}\hfill {X}_n=0.838\times {SV}_{2,3}+0.742\times {RV}_{5,6}+0.744\times R\kern0.5em aVL\hfill \\ {}\hfill -0.587\times \left( RS\kern0.5em aVF+{RV}_2+{SV}_6\right)\hfill \end{array}} $$ and $$ Y=0.363\times \mathrm{age}\kern0.5em +\kern0.5em 0.439\times R\ aVL\kern0.5em +\kern0.5em 0.707\times \left(S\kern0.5em {V}_2+R\kern0.5em {V}_{5,6}\right) $$ respectively. The sensitivities of the two new models were 71.4% and 75.8%, significantly higher than the22 conventional ECG criteria. Two models developed based on gender can be considered for use to investigate the preliminary assessment of the probability of LVH.