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Background His-Purkinje conduction system pacing (HPCSP) has emerged as an effective alternative to overcome the limitations of right ventricular pacing (RVP) via physiological left ventricular activation, but there remains a paucity of comparative information for His bundle pacing (HBP) and left bundle branch pacing (LBBP). Methods A Bayesian random-effects network analysis was conducted to compare the relative effects of HBP, LBBP, and RVP in patients with bradycardia and conduction disorders. PubMed, Embase, Cochrane Library, and Web of Science were systematically searched from database inception until 21 September 2021. Results Twenty-eight studies involving 4,160 patients were included in this meta-analysis. LBBP significantly improved success rate, pacing threshold, pacing impedance, and R-wave amplitude compared with HBP. LBBP also demonstrated a non-significant trend towards superior outcomes of lead complications, heart failure hospitalization, atrial fibrillation, and all-cause death. However, HBP was associated with significantly shorter paced QRS duration relative to LBBP. Despite higher success rate, shorter procedure/fluoroscopy duration, and fewer lead complications, patients receiving RVP were more likely to experience reduced left ventricular ejection fraction, longer paced QRS duration, and higher rates of heart failure hospitalization than those receiving HPCSP. No statistical differences were observed in the remaining outcome measures. Conclusions This network meta-analysis demonstrates the efficacy and safety of HPCSP for the treatment of bradycardia and conduction disorders, with differences in pacing parameters, electrophysiology characteristics, and clinical outcomes between HBP and LBBP. Larger-scale, long-term comparative studies are warranted for further verification. This article is protected by copyright. All rights reserved.

Background: Age is an independent risk factor of the progress and prognosis of atrial fibrillation (AF). However, ablation outcomes between elderly and younger patients with AF remain elusive. Methods: Cochrane Library, Embase, PubMed, and Web of Science were systematically searched up to 1 April 2022. Studies comparing AF ablation outcomes between elderly and younger patients and comprising outcomes of AF ablation for elderly patients were included. Trial sequential analysis (TSA) was performed to adjust for random error and lower statistical power in our meta-analysis. Subgroup analysis identified possible determinants of outcome impact for elderly patients after ablation. Moreover, linear and quadratic prediction fit plots with confidence intervals were performed, as appropriate. Results: A total of 27 studies with 113,106 AF patients were eligible. Compared with the younger group, the elderly group was significantly associated with a lower rate of freedom from AF (risk ratio [RR], 0.95; p = 0.008), as well as a higher incidence of safety outcomes (cerebrovascular events: RR, 1.64; p = 0.000; serious hemorrhage complications: RR, 1.50; p = 0.035; all-cause death: RR, 2.61; p = 0.003). Subgroup analysis and quadratic prediction fit analysis revealed the follow-up time was the potential determinant of freedom from AF for elderly patients after AF ablation. Conclusions: Our meta-analysis suggests that elderly patients may have inferior efficacy and safety outcomes to younger patients with AF ablation. Moreover, the follow-up time may be a potential determinant of outcome impact on freedom from AF for elderly patients after AF ablation.

Background: Dilated cardiomyopathy (DCM) is characterized by the left ventricular dilatation and impaired myocardial systolic dysfunction with high mortality and morbidity. However, the underlying mechanisms remain elusive. Methods: Differentially expressed genes (DEGs) analysis was performed using two expression profiles from GSE3585 and GSE84796. Enrichment analysis to explore the potential mechanisms underlying DCM was conducted. A total of four algorithms, including key module of MCODE, degree, maximum neighborhood component (MNC), and maximal clique centrality (MCC), were used within Cytoscape to identify the hub genes. Correlation analysis between hub genes and infiltrated immune cells to identify potential immune-related genes. The expression analysis and diagnosis value analysis of potential immune-related genes were performed. Finally, the expression analysis with GSE57338 and relationship analysis with the comparative toxicogenomics database (CTD) were performed for identification of the key immune-related genes in DCM. Results: A total of 80 DEGs were screened for DCM. Enrichment analysisrevealed that DEGs were involved in immune-related pathological process. Immune infiltration analysis indicated a potential immune response abnormal in DCM. Four up-regulated genes, including COL1A2, COL3A1, CD53, and POSTN, were identified as potential immune-related genes. Finally, three genes (COL1A2, COL3A1, and POSTN) were determined as the key immune-related genes in DCM via expression analysis with a validation set (GSE57338) and relationship analysis with CTD. Conclusions: Our study suggested that the upregulated COL1A2, COL3A1, and POSTN might be the key immune-related genes for DCM. Further studies are needed to validate the underlying mechanisms.

Glucose fluctuations may contribute to large conductance calcium activated potassium (BK) channel dysfunction. However, the underlying mechanisms remain elusive. The aim of this study was to investigate the molecular mechanisms involved in BK channel dysfunction as a result of glucose fluctuations. A rat diabetic model was established through the injection of streptozotocin. Glucose fluctuations in diabetic rats were induced via consumption and starvation. Rat coronary arteries were isolated and coronary vascular tensions were measured after three weeks. Rat coronary artery smooth muscle cells were isolated and whole-cell BK channel currents were recorded using a patch clamp technique. Human coronary artery smooth muscle cells in vitro were used to explore the underlying mechanisms. After incubation with iberiotoxin (IBTX), the Δ tensions (% Max) of rat coronary arteries in the controlled diabetes mellitus (C-DM), the uncontrolled DM (U-DM) and the DM with glucose fluctuation (GF-DM) groups were found to be 84.46 ± 5.75, 61.89 ± 10.20 and 14.77 ± 5.90, respectively (P .05), while the current densities of the BK channels in the three groups were 43.09 ± 4.35 pA/pF, 34.23 ± 6.07 pA/pF and 17.87 ± 4.33 pA/pF, respectively (P .05). The Δ tensions (% Max) of rat coronary arteries after applying IBTX in the GF-DM rats injected with 0.9% sodium chloride (NaCl) (GF-DM + NaCl) and the GF-DM rats injected with N-acetyl-L-cysteine (NAC) (GF-DM + NAC) groups were found to be 8.86 ± 1.09 and 48.90 ± 10.85, respectively (P .05). Excessive oxidative stress and the activation of protein kinase C (PKC) α and nuclear factor (NF)-κB induced by glucose fluctuations promoted the decrease of BK-β1 expression, while the inhibition of reactive oxygen species (ROS), PKCα, NF-κB and muscle ring finger protein 1 (MuRF1) reversed this effect. Glucose fluctuations aggravate BK channel dysfunction via the ROS overproduction and the PKCα/NF-κB/MuRF1 signaling pathway.

Co-expression network may contribute to better understanding molecular interaction patterns underlying cellular processes. To explore microRNAs (miRNAs) expression patterns correlated with AF, we performed weighted gene co-expression network analysis (WGCNA) based on the dataset GSE28954. Thereafter, we predicted target genes using experimentally verified databases (ENOCRI, miRTarBase, and Tarbase), and overlapped genes with differentially expressed genes (DEGs) from GSE79768 were identified as key genes. Integrated analysis of association between hub miRNAs and key genes was conducted to screen hub genes. In general, we identified 3 differentially expressed miRNAs (DEMs) and 320 DEGs, predominantly enriched in inflammation-related functional items. Two significant modules (red and blue) and hub miRNAs (hsa-miR-146b-5p and hsa-miR-378a-5p), which highly correlated with AF-related phenotype, were detected by WGCNA. By overlapping the DEGs and predicted target genes, 38 genes were screened out. Finally, 9 genes (i.e. ATP13A3, BMP2, CXCL1, GABPA, LIF, MAP3K8, NPY1R, S100A12, SLC16A2) located at the core region in the miRNA-gene interaction network were identified as hub genes. In conclusion, our study identified 2 hub miRNAs and 9 hub genes, which may improve the understanding of molecular mechanisms and help to reveal potential therapeutic targets against AF.

Background. There are few biomarkers with an excellent predictive value for postacute myocardial infarction (MI) patients who developed heart failure (HF). This study aimed to screen candidate biomarkers to predict post-MI HF. Methods. This is a secondary analysis of a single-center cohort study including nine post-MI HF patients and eight post-MI patients who remained HF-free over a 6-month follow-up. Transcriptional profiling was analyzed using the whole blood samples collected at admission, discharge, and 1-month follow-up. We screened differentially expressed genes and identified key modules using weighted gene coexpression network analysis. We confirmed the candidate biomarkers using the developed external datasets on post-MI HF. The receiver operating characteristic curves were created to evaluate the predictive value of these candidate biomarkers. Results. A total of 6,778, 1,136, and 1,974 genes (dataset 1) were differently expressed at admission, discharge, and 1-month follow-up, respectively. The white and royal blue modules were most significantly correlated with post-MI HF (dataset 2). After overlapping dataset 1, dataset 2, and external datasets (dataset 3), we identified five candidate biomarkers, including FCGR2A, GSDMB, MIR330, MED1, and SQSTM1. When GSDMB and SQSTM1 were combined, the area under the curve achieved 1.00, 0.85, and 0.89 in admission, discharge, and 1-month follow-up, respectively. Conclusions. This study demonstrates that FCGR2A, GSDMB, MIR330, MED1, and SQSTM1 are the candidate predictive biomarker genes for post-MI HF, and the combination of GSDMB and SQSTM1 has a high predictive value.

Glucose fluctuations may be associated with myocardial fibrosis. This study aimed to investigate the underlying mechanisms of glucose fluctuation-related myocardial fibrosis.Streptozotocin (STZ)-injected type 1 diabetic rats were randomized to five groups: the controlled blood glucose (CBG) group, uncontrolled blood glucose (UBG) group, fluctuated blood glucose (FBG) group, FBG rats injected with 0.9% sodium chloride (NaCl) (FBG + NaCl) group, and FBG rats injected with MCC950 (FBG + MCC950) group. Eight weeks later, left ventricular function was evaluated by echocardiography and myocardial fibrosis was observed by Masson trichrome staining. The primary neonatal rat cardiac fibroblasts were cultured with different concentrations of glucoseThe left ventricular function was impaired and myocardial fibrosis was aggravated most significantly in the FBG group compared with the CBG and UBG groups. The levels of interleukin (IL)-1β, IL-18, transforming growth factor-β1 (TGF-β1), collagen type 1 (collagen I), nuclear factor (NF)-κB, and nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome were significantly increased in the FBG group.Glucose fluctuations promote diabetic myocardial fibrosis by the NF-κB-mediated inflammasome activation.

Aim: Glucose fluctuations may be responsible for, or further the onset of arterial hypertension, but the exact mechanisms remain unclear. The purpose of this study was to investigate the mechanisms behind and related to aortic fibrosis and aortic stiffening induced by glucose fluctuations. Methods: Sprague-Dawley rats were injected with streptozotocin (STZ) and randomly divided into three treatment groups: controlled STZ-induced diabetes (C-STZ); uncontrolled STZ-induced diabetes (U-STZ); and STZ-induced diabetes with glucose fluctuations (STZ-GF). After 3 weeks, rat blood pressure (BP) was tested, and aortic fibrosis was detected by using the Masson trichrome staining technique. Levels of p38 mitogen-activated protein kinase (p38 MAPK), runt-related transcription factor 2 (Runx2), collagen type 1 (collagen I), and NADPH oxidases were determined by Western blot.Rat vascular smooth muscle cells in vitro were used to explore underlying mechanisms. Results: The systolic BP of diabetic rats in the C-STZ, U-STZ, and STZ-GF groups was 127.67 ± 6.53, 150.03 ± 5.24, and 171.63 ± 3.53 mm Hg, respectively (p< 0.05). The mean BP of diabetic rats in the three groups was 91.20 ± 10.07, 117.29 ± 4.28, and 140.58 ± 2.14 mm Hg, respectively (p< 0.05). The diastolic BP of diabetic rats in the three groups was 73.20 ± 12.63, 101.93 ± 5.79, and 125.37 ± 4.62 mm Hg, respectively (p< 0.05). The ratios of fibrosis areas in the aortas of the three groups were 11.85 ± 1.23, 29.00 ± 0.87, and 48.36 ± 0.55, respectively (p< 0.05). The expressions of p38 MAPK, Runx2, and collagen I were significantly increased in the STZ-GF group. In vitro, applications of inhibitors of reactive oxygen species (ROS) and p38 MAPK successfully reversed glucose fluctuations that would have possibly induced aortic fibrosis. Conclusions: Blood glucose fluctuations aggravate aortic fibrosis via affecting the ROS/p38 MAPK /Runx2 signaling pathway.

Objective This study aims to develop an artificial intelligence-based method to screen patients with left ventricular ejection fraction (LVEF) of 50% or lesser using electrocardiogram (ECG) data alone. Methods Convolutional neural network (CNN) is a class of deep neural networks, which has been widely used in medical image recognition. We collected standard 12-lead ECG and transthoracic echocardiogram (TTE) data including the LVEF value. Then, we paired the ECG and TTE data from the same individual. For multiple ECG-TTE pairs from a single individual, only the earliest data pair was included. All the ECG-TTE pairs were randomly divided into the training, validation, or testing data set in a ratio of 9:1:1 to create or evaluate the CNN model. Finally, we assessed the screening performance by overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Results We retrospectively enrolled a total of 26 786 ECG-TTE pairs and randomly divided them into training (n = 21 732), validation (n = 2 530), and testing data set (n = 2 530). In the testing set, the CNN algorithm showed an overall accuracy of 73.9%, sensitivity of 69.2%, specificity of 70.5%, positive predictive value of 70.1%, and negative predictive value of 69.9%. Conclusion Our results demonstrate that a well-trained CNN algorithm may be used as a low-cost and noninvasive method to identify patients with left ventricular dysfunction.

Background This study aimed to investigate the trend of cardiovascular disease (CVD)-specific mortality in patients with non-small cell lung cancer (NSCLC) and identify prognostic factors for CVD-specific death in stage NSCLC patients. Methods In this study, 270,618 NSCLC patients were collected from the Surveillance, Epidemiology, and End Results database. CVD- and NSCLC-specific cumulative mortality and proportion of death were calculated and graphically displayed to describe the probability of specific endpoints. Prognostic factors for CVD-specific mortality were evaluated by cause-specific hazard ratios (HR) with 95% confidence intervals (CI) using the competing risk model with non-cardiovascular death as competing risks. Results Among all competing causes of death, lung cancer resulted in the highest cumulative mortality, followed by CVDs and other causes. In the proportion of cause-specific death, heart diseases accounted for approximately 5.3% of the total death, only secondary to primary cancer. In all three stages, higher age, squamous cell carcinoma, and no-or-unknown chemotherapy and/or radiotherapy were associated with a higher risk of CVD-specific death, while surgery treatment seemed to be a protective factor. Female gender was statistically related to CVD-specific death in stage I and III patients with HRs of 0.84 (0.78–0.91) and 0.84 (0.77–0.93), respectively. Interestingly, right-sided laterality was correlated with lower CVD-specific mortality with HR of 0.82 (0.74–0.90) in stage III. Conclusions This study illustrated the historical trend of CVD-specific death in NSCLC patients and assesses potential prognostic risk factors, highlighting the involvement of cardio-oncology teams in cancer treatment to provide optimal comprehensive care and long-term surveillance for cancer patients.

Quercetin has attracted more attention in recent years due to its protective role against ischemia/reperfusion injury. Quercetin can alleviate oxidative stress injury through the inhibition of NADPH oxidase and xanthine oxidase, blockage of the Fenton reaction, and scavenging of reactive oxygen species. Quercetin can also exert anti-inflammatory and anti-apoptotic effects by reducing the response to inflammatory factors and inhibiting cell apoptosis. Moreover, it can induce vasodilation effects through the inhibition of endothelin-1 receptors, the enhancement of NO stimulation and the activation of the large-conductance calcium-activated potassium channels. Finally, Quercetin can also antagonize the calcium overload. These multifaceted activities of Quercetin make it a potential therapeutic alternative for the treatment of ischemia/reperfusion injury.

Background Heart failure (HF) is an end-stage syndrome of all structural heart diseases which accompanies the loss of myocardium and cardiac fibrosis. Although the role of inflammasome in cardiac fibrosis has recently been a point of focus, the mechanism of inflammasome activation in HF has not yet been elucidated. Methods In this study, we investigated the expression of inflammasome proteins in a rat thoracic aorta constriction (TAC) model and cultured cardiac fibroblasts with stimulation of norepinephrine (NE). Results Our results showed that levels of inflammasome proteins in the myocardial of TAC rats were elevated. By blocking β-adrenergic signaling in the rats, inflammasome activation was suppressed and heart function was improved. The stimulation of cultured cardiac fibroblasts with NE activated inflammasome in vitro, which was abrogated by the inhibition of the calcium channels and reactive oxygen species (ROS). The activation of inflammasome by NE promoted cardiac fibrosis, whereas the inhibition of the calcium channels, ROS, and inflammasome reduced this effect. Conclusions The present study indicated that activation of inflammasome by β-adrenergic signaling promotes cardiac fibrosis. Therefore, modulation of inflammasome during HF might provide a novel strategy to treat this disease.

Accumulating evidence indicates the occurrence and development of diabetic complications relates to not only constant high plasma glucose, but also glucose fluctuations which affect various kinds of molecular mechanisms in various target cells and tissues. In this review, we detail reactive oxygen species and their potentially damaging effects upon glucose fluctuations and resultant downstream regulation of protein signaling pathways, including protein kinase C, protein kinase B, nuclear factor-κB, and the mitogen-activated protein kinase signaling pathway. A deeper understanding of glucose-fluctuation-related molecular mechanisms in the development of diabetic complications may enable more potential target therapies in future.

Large-conductance calcium-activated potassium channels (BK channels) belong to a family of Ca2+-sensitive voltage-dependent potassium channels and play a vital role in various physiological activities in the human body. The renin-angiotensin-aldosterone system is acknowledged as being vital in the body's hormone system and plays a fundamental role in the maintenance of water and electrolyte balance and blood pressure regulation. There is growing evidence that the renin-angiotensin-aldosterone system has profound influences on the expression and bioactivity of BK channels. In this review, we focus on the molecular mechanisms underlying the regulation of BK channels mediated by the renin-angiotensin-aldosterone system and its potential as a target for clinical drugs.