Potential role of cyanidin 3-glucoside (C3G) in diabetic cardiomyopathy in diabetic rats: An in vivo approach

AbstractThe present study aimed to evaluate the importance of cyanidin 3-glucoside (C3G) of diabetic cardiomyopathy in diabetic rats. The rats were induced with diabetic using streptozotocin and total triglyceride (TG) and total cholesterol (TC) were determined. The range of myocardial enzymes such as aspartate aminotransferase (AST), creatine kinase (CK) and lactate dehydrogenase (LD) were also estimated, further, the Immuno histochemical analysis and western blot investigation were determined for the actual activity of C3G. Results indicated that the marker enzymes such as CK, LD and AST were significantly (P<0.05) increased in STZ administered rats (DM group), while the levels of these elevated marker enzymes of cardiac injury significantly (P<0.05) declined in the DM+C3G group, as compared to the diabetic group of rats. Additionally, a decrease in the level of TNF-alpha and interleukin-6, was noticed in the C3G treated group as compared to diabetic group. Finally, blotting analysis clearly confirmed that theC3G treatment resulted to higher level response of Bcl-2 and lower level response of caspase-3 and BAX. In conclusion, C3G a natural antioxidant may prevent cardiovascular complications by ameliorating oxidative damage, inflammation, metabolic dysfunctions and apoptosis pathways in type 2 diabetes

Contemporary survival and anticoagulation of patients with atrial fibrillation: A community based cohort study in China

BackgroundsThe understanding of death in patients with atrial fibrillation (AF) in China is limited. This study aimed to assess the contemporary survival of AF patients in China and to explore risk factors for deaths.MethodsThis was a prospective community-based cohort study including 559 AF patients, who were followed-up from July 2015 to December 2020.ResultsDuring 66-month follow-up, there were 200 deaths (56.5% cardiovascular, 40.0% non-cardiovascular, and 3.5% unknown causes) among 559 AF patients with the median age of 76 years. The top three causes of death were heart failure (33.0%), ischemic stroke (17.0%) and cancer (16.5%). Multivariate Cox regression analysis indicated baseline variables positively associated with all-cause death were age (HR: 1.10, 95% CI: 1.08–1.13), AF subtype (HR: 1.37, 95% CI: 1.08–1.73), prior myocardial infarction (HR: 3.40, 95% CI: 1.48–7.78), previous tumor (HR: 2.61, 95% CI: 1.37–4.98), hypoglycemic therapy at baseline (HR: 1.81, 95% CI: 1.13–2.91), but body weight (HR: 0.98, 95% CI: 0.97–1.00) and use of calcium channel blocker (CCB) (HR: 0.62, 95% CI: 0.41–0.95) played a protective role to all-cause death. Of patients who were alive at the end of follow-up, 24.0% were on oral anticoagulants (OAC) alone, 4.5% on dual antithrombotic therapy, 33.1% on antiplatelet agents alone and 38.4% weren't on any antithrombotic medication.ConclusionIschemic stroke still remains one of the leading causes of death and OAC is seriously underused in AF patients in China. Independent risk factors for death are age, AF subtype, previous tumor, prior myocardial infarction, hypoglycemic therapy, low body weight and no CCB use.Clinical Trial Registrationhttp://www.chictr.org.cn/ (ChiCTR-ICR-15007036)

A hybrid deep learning approach by integrating extreme gradient boosting‐long short‐term memory with generalized autoregressive conditional heteroscedasticity family models for natural gas load volatility prediction

Abstract Natural gas load forecasting provides decision‐making support for natural gas dispatch and management, pipeline network construction, pricing, and sustainable energy development. To explain the uncertainty and volatility in natural gas load forecasting, this study predicts the natural gas load volatility. As the natural gas load volatility has the time‐series features, along with long‐term memory, volatility aggregation, asymmetry, and nonnormality, this study proposes a natural gas load volatility prediction model by combining generalized autoregressive conditional heteroscedasticity (GARCH) family models, XGBoost algorithm, and long short‐term memory (LSTM) network. The model first takes the GARCH family models parameters of sliding estimation and meteorological factors as the influencing factors of volatility, and then it screens these influencing factors through the extreme gradient boosting (XGBoost) algorithm. Finally, the selected important features are input into the LSTM network to predict the volatility, and the 90% confidence interval of the volatility is calculated. Compared with a variety of single and combined models, the model proposed in this study has an average reduction of 45.404% in the evaluation index of mean squared error. The experimental results show that the model proposed in this study has a good performance and accuracy in predicting the volatility of natural gas load

Analysis of Influencing Factors and Trend Forecast of CO₂ Emission in Chengdu-Chongqing Urban Agglomeration

Urban agglomeration is a primary source of global energy consumption and CO2 emissions. It is employed as a major means of modern economic and social activities. Analysis of the temporal and spatial characteristics of CO2 emissions in urban agglomerations and prediction of the future trends of CO2 emissions in urban agglomerations will help in the implementation of CO2 reduction policies within region-wide areas. So, based on that, this study contains four aspects. Firstly, it calculates the energy CO2 emissions of China’s Chengdu-Chongqing urban agglomeration. Secondly, it analyzes the time and space changes in the area by using ArcGIS. Then, the STIRPAT model is used to investigate the factors influencing CO2 emissions, and the elasticity coefficient of the influencing factors is estimated using the ridge regression method, and the important influencing factors are screened on the basis of the estimated results, which are then used as input features for prediction. Finally, a combined prediction model based on the improved GM (1, N) and SVR models is constructed, and then the optimal solution is found through the particle swarm optimization algorithm. It sets up different CO2 emission scenarios to predict the energy CO2 emission of the region and its cities. The results show that, first, the CO2 emissions of the Chengdu-Chongqing urban agglomeration have accumulated year by year, but by 2030, as predicted, it will not reach its peak. The spatial layout of CO2 emissions in this region is not expected to undergo major changes by 2030. Second, population, GDP, gas and electricity consumption, and industrial structure have served as important factors affecting energy CO2 emissions in the region. Third, on the basis of the prediction results for different scenarios, the CO2 emissions in the baseline scenario are low in the short term, but the CO2 emissions in the low-carbon scenario are low in the long run. This study also puts forward some policy recommendations on how to reduce CO2 emissions

Potential role of cyanidin 3-glucoside (C3G) in diabetic cardiomyopathy in diabetic rats: An in vivo approach

The present study aimed to evaluate the importance of cyanidin 3-glucoside (C3G) of diabetic cardiomyopathy in diabetic rats. The rats were induced with diabetic using streptozotocin and total triglyceride (TG) and total cholesterol (TC) were determined. The range of myocardial enzymes such as aspartate aminotransferase (AST), creatine kinase (CK) and lactate dehydrogenase (LD) were also estimated, further, the Immuno histochemical analysis and western blot investigation were determined for the actual activity of C3G. Results indicated that the marker enzymes such as CK, LD and AST were significantly (P < 0.05) increased in STZ administered rats (DM group), while the levels of these elevated marker enzymes of cardiac injury significantly (P < 0.05) declined in the DM + C3G group, as compared to the diabetic group of rats. Additionally, a decrease in the level of TNF-alpha and interleukin-6, was noticed in the C3G treated group as compared to diabetic group. Finally, blotting analysis clearly confirmed that theC3G treatment resulted to higher level response of Bcl-2 and lower level response of caspase-3 and BAX. In conclusion, C3G a natural antioxidant may prevent cardiovascular complications by ameliorating oxidative damage, inflammation, metabolic dysfunctions and apoptosis pathways in type 2 diabetes. Keywords: Cyanidin 3-glucoside, Cardiomyopathy, Immuno histochemistry, Western blo

Complete Atrioventricular Block Caused by Retrograde Transaortic Approach

A 61-year-old female was referred for catheter ablation of symptomatic and frequent premature ventricular complexes presented with right bundle branch block and a prominent inferior frontal plane QRS axis. A retrograde transaortic approach was routinely performed. A sustained complete atrioventricular block was repeatedly encountered while the ablation catheter was attempting to cross the aortic valve with different curves and manipulations. The procedure was abandoned. The mechanical atrioventricular block could only have been caused by the retrograde transaortic approach. We should be cautious when performing a retrograde transaortic catheter manipulation in some patients

Effect of renal denervation on collagen fibers in the right atria detected by Masson staining.

<p>AAC, abdominal aortic constriction; AAC-RD, abdominal aortic constriction with renal denervation.</p

Renal Denervation Suppresses the Inducibility of Atrial Fibrillation in a Rabbit Model for Atrial Fibrosis

<div><p>Renal denervation (RD) was reported to reduce the susceptibility of atrial fibrillation (AF), but the underlying mechanism has not been well understood. This study was performed to investigate the effect of RD on the inducibility of AF in a rabbit model for atrial fibrosis and to explore the potential mechanisms. Thirty-five rabbits were randomly assigned into sham-operated group (n = 12), abdominal aortic constriction (AAC) group (n = 12) and AAC with RD (AAC-RD) group (n = 11). The incidence of AF induced by burst pacing in atriums was determined. Blood was collected to measure the levels of rennin, angiotensin II and aldosterone. Atrial samples were preserved to evaluate protein and gene expression of collagen, connective tissue growth factor (CTGF) and transforming growth factor-β1 (TGF-β1). Our data suggested cardiac structure remodeling and atrial fibrosis were successfully induced by AAC. Compared with the AAC group, the AAC-RD rabbits had smaller ascending aortic diameter and left ventricular end-systolic diameter. For burst pacing at the left atrium (LA), AF was induced in two of the 12 rabbits in the sham-operated group, 10 of the 12 rabbits in the AAC group, and 2 of the 11 rabbits in the AAC-RD group, with great difference among the three groups (P = 0.001). The percentage of LA burst stimulations with induced AF achieved 47.2% in the AAC group, which was higher than those in both the AAC-RD (12.1%) and the Sham-operated (5.6%) groups. Significantly increasing intercellular space in the AAC group (P<0.001) compared with the sham-operated rabbits. RD clearly decreased the volume fraction of collagen in LA and right atrium compared with that of the AAC group (P< 0.01). AAC-induced elevation of collagen I, CTGF and TGF-β1 was suppressed by RD. In conclusion, RD suppressed the inducibility of AF in a rabbit model for pressure associated atrial fibrosis, potentially by modulating renin-angiotensin-aldosterone system and decreasing pro-fibrotic factors.</p></div