Diagnostic value of parameters derived from planar MUGA for detecting HFpEF in coronary artery disease patients.

BACKGROUND: In recent years, heart failure with preserved ejection fraction (HFpEF) has received increasing clinical attention. To investigate the diagnostic value of diastolic function parameters derived from planar gated blood-pool imaging (MUGA) for detecting HFpEF in coronary atherosclerotic heart disease (coronary artery disease, CAD) patients. METHODS: Ninety-seven CAD patients with left ventricular ejection fraction ≥ 50% were included in the study. Based on the left ventricular end-diastolic pressure (LVEDP), the patients were divided into the HFpEF group (LVEDP ≥ 16 mmHg, 47 cases) and the normal LV diastolic function group (LVEDP < 16 mmHg, 50 cases). Diastolic function parameters obtained by planar MUGA include peak filling rate (PFR), filling fraction during the first third of diastole (1/3FF), filling rate during the first third of diastole (1/3FR), mean filling rate during diastole (MFR), and peak filling time (TPF). Echocardiographic parameters include left atrial volume index (LAVI), peak tricuspid regurgitation velocity (peak TR velocity), transmitral diastolic early peak inflow velocity (E), average early diastolic velocities of mitral annulars (average e'), average E/e' ratio. The diastolic function parameters obtained by planar MUGA were compared with those obtained by echocardiography to explore the clinical value of planar MUGA for detecting HFpEF. RESULTS: The Receiver-operating characteristic curve analysis of diastolic function parameters obtained from planar MUGA and echocardiography to detect HFpEF showed that: among the parameters examined by planar MUGA, the area under the curve (AUC) of PFR, 1/3FF, 1/3FR, MFR and TPF were 0.827, 0.662, 0.653, 0.663 and 0.809, respectively. Among the echocardiographic parameters, the AUCs for average e', average E/e' ratio, peak TR velocity, and LAVI values were 0.747, 0.706, 0.735, and 0.633. The combination of PFR and TPF showed an AUC of 0.856. PFR combined with TPF value demonstrated better predictive value than average e' (Z = 2.020, P = 0.043). CONCLUSION: Diastolic function parameters obtained by planar MUGA can be used to diagnose HFpEF in CAD patients. PFR combined with TPF was superior to the parameters obtained by echocardiography and showed good sensitivity and predictive power for detecting HFpEF.

Three-dimensional reduced graphene reinforced cement with enhanced safety and durability for drinking water distribution applications: Long-term experimental and theoretical study.

Cement mortar lining (CML) is commonly used for iron pipe internal corrosion inhibition in drinking water distribution system (DWDS), however, the corrosion of CML itself is still a problem, particularly under soft water conditions. In this study, both long-term experimental study and theoretical studies were conducted to evaluate the effects of graphene oxide (GO) and three-dimensional reduced graphene oxide (3D-rGO) as additives on the stability of CML and the corresponding water quality. Results showed that during a 182-day leaching experiment, the 3D-rGO modified cement had a higher ability to inhibit the cement constituent leaching than GO modified and original cements. Structural characterization indicated that the addition of 3D-rGO could slightly promote the degree of calcium hydroxide crystallization in CML. Molecular dynamics simulation demonstrated that the 3D-rGO nanosheets strengthened the tensile strain of the cement and restricted the movement of calcium ions by forming strong bonds with the calcium-silicate-hydrate gel network. In addition, compared with GO modified cement and original cement, the 3D-rGO modified cement could somewhat reduce the disinfection by-products formation and the microbial richness in drinking water. Thus, the reinforcement of cement by 3D-rGO could enhance the safety and durability of CML iron pipes in DWDS.

Prevalence of cardiovascular diseases in relation to total bone mineral density and prevalent fractures: A population-based cross-sectional study.

BACKGROUND AND AIM: We aimed to explore the relationship between total BMD and prevalent fractures and the risk of CVD in a female population in the United States (US). METHODS AND RESULTS: We undertook cross-sectional analyses of a female population participating in the US National Health and Nutrition Examination Survey (NHANES). Generalized linear models and restricted cubic spline curves were used to examine the association between total BMD and CVD. Subgroup analyses were also undertaken. A total of 13,707 women were enrolled. The restricted cubic spline curve revealed a linear and negative association between total BMD and CVD. The inflection point for the curve was identified at total BMD = 1.085 g/cm2. A negative relationship between total BMD and the prevalence of individual CVDs (angina and stroke) was noted (P < 0.05). In subgroup analyses stratified by race/ethnicity, hypertension, diabetes mellitus, and physical activity, a negative association existed in women who were non-Hispanic White, without hypertension, without diabetes mellitus, and who never participated in physical activity, respectively. In subgroup analyses stratified by age, this association also differed based on age. In addition, participants without history of fracture had significant lower probability of experiencing individual CVDs (angina pectoris, heart attack, and stroke) compared with those with history of fracture. CONCLUSIONS: We revealed a reduced prevalence of CVD associated with increased total BMD in a female population in the US. CVD risk decreased significantly if total BMD >1.085 g/cm2. Additionally, fracture-free individuals had much reduced odds of developing CVD.

MicroRNA-146a Serves as a Biomarker for Adverse Prognosis of ST-Segment Elevation Myocardial Infarction.

OBJECTIVE: This study is aimed at exploring the underlying molecular mechanisms of ST-segment elevation myocardial infarction (STEMI) and provides potential clinical prognostic biomarkers for STEMI. METHODS: The GSE60993 dataset was downloaded from the GEO database, and the differentially expressed genes (DEGs) between STEMI and control groups were screened. Enrichment analysis of the DEGs was subsequently performed using the DAVID database. A protein-protein interaction network was constructed, and hub genes were identified. The hub genes in patients were then validated by quantitative reverse transcription-PCR. Furthermore, hub gene-miRNA interactions were evaluated using the miRTarBase database. Finally, patient data on classical cardiovascular risk factors were collected, and plasma microRNA-146a (miR-146a) levels were detected. An individualized nomogram was constructed based on multivariate Cox regression analysis. RESULTS: A total of 239 DEGs were identified between the STEMI and control groups. Expression of S100A12 and miR-146a was significantly upregulated in STEMI samples compared with controls. STEMI patients with high levels of miR-146a had a higher risk of major adverse cardiovascular events (MACEs) than those with low levels of miR-146a (log-rank P = 0.034). Multivariate Cox regression analysis identified five statistically significant variables, including age, hypertension, diabetes mellitus, white blood cells, and miR-146a. A nomogram was constructed to estimate the likelihood of a MACE at one, two, and three years after STEMI. CONCLUSION: The incidence of MACEs in STEMI patients expressing high levels of miR-146a was significantly greater than in those expressing low levels. MicroRNA-146a can serve as a biomarker for adverse prognosis of STEMI and might function in its pathogenesis by targeting S100A12, which may exert its role via an inflammatory response. In addition, our study presents a valid and practical model to assess the probability of MACEs within three years of STEMI.

Development and Validation of a Risk Nomogram Model for Predicting Revascularization After Percutaneous Coronary Intervention in Patients with Acute Coronary Syndrome.

OBJECTIVE: Percutaneous coronary intervention (PCI) is one of the most effective treatments for acute coronary syndrome (ACS). However, the need for postoperative revascularization remains a major problem in PCI. This study was to develop and validate a nomogram for prediction of revascularization after PCI in patients with ACS. METHODS: A retrospective observational study was conducted using data from 1083 patients who underwent PCI (≥6 months) at a single center from June 2013 to December 2019. They were divided into training (70%; n = 758) and validation (30%; n = 325) sets. Multivariate logistic regression analysis was used to establish a predictive model represented by a nomogram. The nomogram was developed and evaluated based on discrimination, calibration, and clinical efficacy using the concordance statistic (C-statistic), calibration plot and decision curve analysis (DCA), respectively. RESULTS: The nomogram was comprised of ten variables: follow-up time (odds ratio (OR): 1.01; 95% confidence interval (CI): 1.00-1.03), history of diabetes mellitus (OR: 1.83; 95% CI: 1.25-2.69), serum creatinine level on admission (OR: 0.99; 95% CI: 0.98-1.00), serum uric acid level on admission (OR: 1.005; 95% CI: 1.002-1.007), lipoprotein-a level on admission (OR: 1.0021; 95% CI: 1.0013-1.0029), low density lipoprotein cholesterol level on re-admission (OR: 1.33; 95% CI: 0.10-0.47), the presence of chronic total occlusion (OR: 3.30; 95% CI: 1.93-5.80), the presence of multivessel disease (OR: 4.48; 95% CI: 2.85-7.28), the presence of calcified lesions (OR: 1.63; 95% CI: 1.11-2.39), and the presence of bifurcation lesions (OR: 1.82; 95% CI: 1.20-2.77). The area under the receiver operating characteristic curve values for the training and validation sets were 0.765 (95% CI: 0.732-0.799) and 0.791 (95% CI: 0.742-0.830), respectively. The calibration plots showed good agreement between prediction and observation in both the training and validation sets. DCA also demonstrated that the nomogram was clinically useful. CONCLUSION: We developed an easy-to-use nomogram model to predict the risk of revascularization after PCI in patients with ACS. The nomogram may provide useful assessment of risk for subsequent treatment of ACS patients undergoing PCI.

FCER1G and PTGS2 Serve as Potential Diagnostic Biomarkers of Acute Myocardial Infarction Based on Integrated Bioinformatics Analyses.

This study aimed to explore the potential diagnostic biomarkers and mechanisms underlying acute myocardial infarction (AMI). We downloaded four datasets (GSE19339, GSE48060, GSE66360, and GSE97320) from the Gene Expression Omnibus database and combined them as an integrated dataset. A total of 153 differentially expressed genes (DEGs) were analyzed by the linear models for microarray analysis (LIMMA) package. Weighted gene co-expression network analysis was used to screen for the significant gene modules. The intersection of DEGs and genes in the most significant module was termed "common genes" (CGs). CGs were mainly enriched in "inflammatory response," "neutrophil chemotaxis," and "IL-17 signaling pathway" through functional enrichment analyses. Subsequently, 15 genes were identified as the hub genes in the protein-protein interaction network. The Fc fragment of IgE receptor Ig (FCER1G) and prostaglandin-endoperoxide synthase 2 (PTGS2) showed significantly increased expression in AMI patients and mice at the 12-h time point in our experiments. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of FCER1G and PTGS2. The area under ROC curve of FCER1G and PTGS2 was 77.6% and 80.7%, respectively. Moreover, the micro (mi)RNA-messenger (m)RNA network was also visualized; the results showed that miRNA-143, miRNA-144, and miRNA-26 could target PTGS2 in AMI progression.

Identification of Pivotal MicroRNAs and Target Genes Associated with Persistent Atrial Fibrillation Based on Bioinformatics Analysis.

Atrial fibrillation (AF) is one of the most common supraventricular arrhythmias worldwide. However, the specific molecular mechanism underlying AF remains unclear. Our study is aimed at identifying pivotal microRNAs (miRNAs) and targeting genes associated with persistent AF (pAF) using bioinformatics analysis. Three gene expression array datasets (GSE31821, GSE41177, and GSE79768) and an miRNA expression array dataset (GSE68475) associated with pAF were downloaded. Differentially expressed genes (DEGs) were identified using the LIMMA package, and differentially expressed miRNAs (DEMs) were screened from GSE68475. Target genes for DEMs were predicted using the miRTarBase database, and intersections between these target genes and DEGs were selected for further analysis, including the generation of protein-protein interaction (PPI) network, miRNA-transcription factor-target regulatory network, and drug-gene network. A total of 264 DEGs and 40 DEMs were identified between the pAF and control groups. Functional and pathway enrichment analyses of up- and downregulated DEGs were performed. The common genes (CGs) were primarily enriched in the phosphoinositide 3-kinase- (PI3K-) protein kinase B (Akt) signaling pathway, negative regulation of cell division, and response to hypoxia. The PPI network, miRNA-transcription factor-target regulatory network, and drug-gene network were constructed using Cytoscape. The present study revealed several novel miRNAs and genes involved in pAF. We speculated that miR-4298, miR-3125, miR-4306, and miR-671-5p could represent significant miRNAs that act on the target gene superoxide dismutase 2 (SOD2) during the development of pAF and may serve as essential biomarkers for pAF diagnosis and treatment. Moreover, MYC might function in pAF pathogenesis through the PI3K-Akt signaling pathway.

Clinical Nomogram to Predict Major Adverse Cardiac Events in Acute Myocardial Infarction Patients within 1 Year of Percutaneous Coronary Intervention.

The purpose of this study was to summarize the clinical characteristics and risk factors of major adverse cardiovascular events (MACEs) in patients who had had acute myocardial infarction (AMI) within 1 year of percutaneous coronary intervention (PCI). A total of 421 AMI patients who were treated with PCI and experienced MACEs within 1 year of their admission were included in this retrospective study. In addition, patients were matched for age, sex, and presentation with 561 patients after AMI who had not had MACEs. The clinical characteristics and risk factors for MACEs within 1 year in AMI patients were investigated, to develop a nomogram for MACEs based on univariate and multivariate analyses. The C statistic was used to assess the discriminative performance of the nomogram. In addition, calibration curve and decision curve analyses were conducted to validate the calibration performance and utility, respectively, of the nomogram. After univariate and multivariate analyses, a nomogram was constructed based on age (odds ratio (OR): 1.030; 95% confidence interval (CI): 1.014-1.047), diabetes mellitus (OR: 1.667; 95% CI: 1.151-2.415), low-density lipoprotein cholesterol (OR: 1.332; 95% CI: 1.134-1.565), uric acid (OR: 1.003; 95% CI: 1.001-1.005), lipoprotein (a) (OR: 1.003; 95% CI: 1.002-1.003), left ventricular ejection fraction (OR: 0.929; 95% CI: 0.905-0.954), Syntax score (OR: 1.075; 95% CI: 1.053-1.097), and hypersensitive troponin T (OR: 1.002; 95% CI: 1.002-1.003). The C statistic was 0.814. The calibration curve showed good concordance of the nomogram, while decision curve analysis demonstrated satisfactory positive net benefits. We developed a convenient, practical, and effective prediction model for predicting MACEs in AMI patients within 1 year of PCI. To ensure generalizability, this model requires external validation.

Predominance of sperm motion in corners.

Sperm migration through the female tract is crucial to fertilization, but the role of the complex and confined structure of the fallopian tube in sperm guidance remains unknown. Here, by confocal imaging microchannels head-on, we distinguish corner- vs. wall- vs. bulk-swimming bull sperm in confined geometries. Corner-swimming dominates with local areal concentrations as high as 200-fold that of the bulk. The relative degree of corner-swimming is strongest in small channels, decreases with increasing channel size, and plateaus for channels above 200 µm. Corner-swimming remains predominant across the physiologically-relevant range of viscosity and pH. Together, boundary-following sperm account for over 95% of the sperm distribution in small rectangular channels, which is similar to the percentage of wall swimmers in circular channels of similar size. We also demonstrate that wall-swimming sperm travel closer to walls in smaller channels (~100 µm), where the opposite wall is within the hydrodynamic interaction length-scale. The corner accumulation effect is more than the superposition of the influence of two walls, and over 5-fold stronger than that of a single wall. These findings suggest that folds and corners are dominant in sperm migration in the narrow (sub-mm) lumen of the fallopian tube and microchannel-based sperm selection devices.