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Abstract Background and aims As the incidence of heart failure (HF) increases, the need for practical tools to evaluate the long‐term prognosis in these patients remains critical. Our study aimed to develop a 48 month prediction model for all‐cause mortality in decompensated HF patients using available clinical indicators. Methods HF patients (n = 503), 60 years or older, were divided into a training cohort (n = 402) and a validation cohort (n = 101). Data on demographics, comorbidities, laboratory results and medications were gathered. Prediction models were developed using the Prognostic Nutritional Index (PNI), cholinesterase (ChE) and a multifactorial nomogram incorporating clinical variables. These models were constructed using the least absolute shrinkage and selection operator algorithm and multivariate logistic regression analysis. The performance of the model was assessed in terms of calibration, discrimination and clinical utility. Results The mean age was 77.11 ± 8.85 years, and 216 (42.9%) were female. The multifactorial nomogram included variables of ChE, lymphocyte count, albumin, serum creatinine and N‐terminal pro‐brain natriuretic peptide (all P

Establishing the corresponding forecasting models based on numerical model that fails to capture gale events is helpful to improve the ability to forecast gales in coastal areas of China. First, we screened for gale events occurred in coastal areas of Qingdao from 2016 to 2019, and established the dataset of gale events that are missed by the forecast with ECMWF (European Center for Medium-range Weather Forecast) high resolution model (hereinafter referred to as EC model). Second, based on support vector machine (SVM), artificial neural network (ANN) and long short-term memory network (LSTM) algorithms, we established the forecast models for gales along the coast of Qingdao, and used these models to revise the wind speed forecasted by the EC model. Finally, after comparative analysis, a model suitable for forecasting gale along the coast of Qingdao, i.e. the forecast model SVM_2 based on SVM algorithm, was selected and its operational forecasting results were ex⁃ amined. Results show that the SVM_2 model has the smallest forecast error for wind speed compared to other models. In order to evaluate the prediction performance of SVM_2 model in terms of the gale events, two gale events occurred in the coast of Qingdao and influenced by differ⁃ ent weather systems are selected to further examine the prediction error of SVM_2 model and EC model for the gale events. The results show that the error of the maximum wind speed forecasted by the SVM_2 model against the observations is significantly smaller than that of the EC model, and the SVM_2 model also has some improvement on the weak gale along the coast of Qingdao compared to the forecast by EC model.

Summary Background Heart failure (HF) is a prevalent clinical syndrome with diverse etiologies. It is crucial to identify novel therapeutic targets based on underlying causes. Here, we aimed to use proteome-wide Mendelian randomization (MR) analyses to identify the associations between genetically predicted elevated levels of circulating proteins and distinct HF outcomes, along with specific HF etiologies. Methods Protein quantitative trait loci (pQTL) data for circulating proteins were sourced from the Atherosclerosis Risk in Communities (ARIC) study, encompassing 7,213 individuals and profiling 4,657 circulating proteins. Genetic associations for outcomes were obtained from the HERMES Consortium and the FinnGen Consortium. Colocalization analysis was employed to assess the impact of linkage disequilibrium on discovered relationships. For replication, two-sample MR was conducted utilizing independent pQTL data from the deCODE study. Multivariable MR (MVMR) and two-step MR were further conducted to investigate potential mediators. Results Two proteins (PCSK9 and AIDA) exhibited associations with HF in patients with coronary heart disease (CHD), and four proteins (PCSK9, SWAP70, NCF1, and RELT) were related with HF in patients receiving antihypertensive medication. Among these associations, strong evidence from subsequent analyses supported the positive relationship between genetically predicted PCSK9 levels and the risk of HF in the context of CHD. Notably, MVMR analysis revealed that CHD and LDL-C did not exert a complete mediating effect in this relationship. Moreover, two-step MR results yielded valuable insights into the potential mediating proportions of CHD or LDL-C in this relationship. Conclusions Our findings provide robust evidence supporting the association between PCSK9 and concomitant HF and CHD. This association is partly elucidated by the influence of CHD or LDL-C, underscoring the imperative for additional validation of this connection and a thorough exploration of the mechanisms through which PCSK9 directly impacts ischemic HF.

Islet transplantation is a promising therapy for diabetes treatment. However, the molecular underpinnings governing the immune response, particularly T-cell dynamics in syngeneic and allogeneic transplant settings, remain poorly understood. Understanding these T cell dynamics is crucial for enhancing graft acceptance and managing diabetes treatment more effectively. This study aimed to elucidate the molecular mechanisms, gene expression differences, biological pathway alterations, and intercellular communication patterns among T-cell subpopulations after syngeneic and allogeneic islet transplantation. Using single-cell RNA sequencing, we analyzed cellular heterogeneity and gene expression profiles using the Seurat package for quality control and dimensionality reduction through t-SNE. Differentially expressed genes (DEGs) were analyzed among different T cell subtypes. GSEA was conducted utilizing the HALLMARK gene sets from MSigDB, while CellChat was used to infer and visualize cell-cell communication networks. Our findings revealed genetic variations within T-cell subpopulations between syngeneic and allogeneic islet transplants. We identified significant DEGs across these conditions, highlighting molecular discrepancies that may underpin rejection or other immune responses. GSEA indicated activation of the interferon-alpha response in memory T cells and suppression in CD4+ helper and γδ T cells, whereas TNFα signaling via NFκB was particularly active in regulatory T cells, γδ T cells, proliferating T cells, and activated CD8+ T cells. CellChat analysis revealed complex communication patterns within T-cell subsets, notably between proliferating T cells and activated CD8+ T cells. In conclusion, our study provides a comprehensive molecular landscape of T-cell diversity in islet transplantation. The insights into specific gene upregulation in xenotransplants suggest potential targets for improving graft tolerance. The differential pathway activation across T-cell subsets underscores their distinct roles in immune responses posttransplantation.

BackgroundSmall Bowel Adenocarcinoma (SBA) is rare, occult and life-threatening malignancy in digestive system. Given low incidence and nonspecific symptoms, SBA is frequently detected in later stages. Double contrast enhanced ultrasound (DCEUS) is an innovative imaging technique applied to visualize the gastrointestinal tract, merging intravenous contrast-enhanced ultrasound with oral contrast-enhanced ultrasound. In this case, DCEUS was utilized and successfully detected an SBA of the jejunum.Case presentationA Chinese woman, aged 64, sought consultation in the gastroenterology department at our hospital, reporting symptoms of abdominal pain. Three months before entering the hospital, she underwent gastroscopy and colonoscopy which suggested chronic gastritis, and she was treated with oral drugs. However, her symptoms were not relieved, and even worsened. To further investigate, DCEUS was performed. The oral contrast agent dilated the luminal space of the upper gastrointestinal tract, resolving the hindrance caused by gas in the gastrointestinal tract and creating an acoustic window for scanning. Through this acoustic window, oral agent contrast-enhanced ultrasound (OA-CEUS) revealed a localized thickening of jejunal intestinal wall measuring 4x3 cm. Following intravenous injection of ultrasound contrast agent, the jejunal lesion exhibited faster enhancement and heterogeneous hyper-enhancement. Finally, the patient underwent jejunal tumor resection. Pathological examination revealed a jejunal adenocarcinoma.ConclusionThe timely diagnosis of SBA can be challenging. DCEUS may have the potential to contribute to diagnosis and detailed evaluation of SBA, particularly in cases involving jejunum. Further researches are needed to fully explore the benefits of DCEUS in the standard diagnostic approach for small bowel diseases.

Automatic detection and alarm of abnormal electrocardiogram (ECG) events play an important role in an ECG monitor system; however, popular classification models based on supervised learning fail to detect abnormal ECG effectively. Thus, we propose an ECG anomaly detection framework (ECG-AAE) based on an adversarial autoencoder and temporal convolutional network (TCN) which consists of three modules (autoencoder, discriminator, and outlier detector). The ECG-AAE framework is trained only with normal ECG data. Normal ECG signals could be mapped into latent feature space and then reconstructed as the original ECG signal back in our model, while abnormal ECG signals could not. Here, the TCN is employed to extract features of normal ECG data. Then, our model is evaluated on an MIT-BIH arrhythmia dataset and CMUH dataset, with an accuracy, precision, recall, F1-score, and AUC of 0.9673, 0.9854, 0.9486, 0.9666, and 0.9672 and of 0.9358, 0.9816, 0.8882, 0.9325, and 0.9358, respectively. The result indicates that the ECG-AAE can detect abnormal ECG efficiently, with its performance better than other popular outlier detection methods.

Abstract Background This study sought to compare the predictive value of NT-proBNP, sST2 and MMPs in HF with different ejection fractions from a population in southern China. Methods A cross-sectional study was conducted on 113 HF patients admitted to Fujian Provincial Hospital from December 2016 to March 2018.The patients were divided into three subgroups: 60 cases in HFpEF group (LVEF≥50%), 28 cases in HFmrEF group (41% ≤ LVEF≤49%) and 25 cases in HFrEF group (LVEF≤40%). ELISA method was applied to detect the concentrations of sST2, MMP-2 and MMP-9. Electrochemical luminescence immunoassay was applied to detect the concentration of plasma NT-proBNP. Univariate and multivariate Cox and logistic regression models were used to analyze the diagnostic significance of these plasma biomarkers in HF patients. Kaplan–Meier survival curves were used to assess the prognostic value of sST2 in the incidence of long-term adverse events during study. Results This study showed that plasma sST2 levels in HFrEF or HFmrEF patients were significantly higher than in HFpEF patients. Plasma levels of MMP-2 and MMP-9 in HFrEF patients were apparently higher than in HFpEF or HFmrEF patients. For the diagnosis of HFpEF, the AUC of NT-proBNP was higher than that of sST2, MMP-2 and MMP-9, which were 0.881, 0.717, 0.705 and 0.597, respectively. For the diagnosis of HFmrEF, the AUC of plasma sST2 was higher than that of MMP-2, MMP-9 and NT-proBNP, which were 0.799, 0.678, 0.676 and 0.793, respectively. For the diagnosis of HFrEF, the AUC of plasma NT-proBNP, sST2, MMP-2, and MMP-9 were 0.945, 0.820, 0.814, and 0.774 respectively. Spearman correlation analysis showed that plasma sST2 levels were significantly correlated with plasma MMP-2, MMP-9 and NT-proBNP levels. Further logistic regression analysis showed that except MMP-9, the biomarkers sST2 (OR = 1.960), MMP-2 (OR = 0.805) and NT-proBNP (OR = 0.002) were all independent risk factors for patients with heart failure. Survival analysis results suggested that for patients with HFmrEF, a higher level of plasma sST2 (≥ 0.332 ng/ml at admission) may predict a higher risk of endpoint events and a lower survival rate (P

This study aims to investigate mental health among Chinese people living in areas with differing levels of infection severity during the COVID-19 outbreak. It also assesses the association between reciprocal and authoritarian filial piety and mental health in times of crises. A sample of 1,201 Chinese participants was surveyed between April and June 2020. Wuhan city (where 23.4% of participants resided), Hubei province outside Wuhan (13.4% of participants), and elsewhere in China (63.1% of participants) were categorized into high, moderate, and low infection severity areas, respectively. The Depression, Anxiety, and Stress Scale’s severity cut-points were used to categorize participants. In the overall sample, 20.9, 34.2, and 29.0% of the participants showed elevated (mild to extremely severe) levels of stress, anxiety, and depression. Those in the highest infection severity group were significantly more likely to be categorized as having elevated levels of stress, anxiety, and depression. General linear modeling was performed on a composite mental distress variable (taking into account stress, anxiety, and depression scores). This model indicated that, even after adjusting for group differences in age, gender, education, and filial piety, the high infection severity group displayed more mental distress than the low infection severity groups. The model also found reciprocal filial piety to have a negative association with mental distress. Conversely, authoritarian filial piety was found to be unrelated to mental distress when controlling for the other variables in the model. No evidence was found for an interaction between either authoritarian or reciprocal filial piety and infection severity, which suggests that the negative association observed between reciprocal filial piety and mental distress was relatively consistent across the three infection severity groups. The findings suggest that future public health programs may integrate the promotion of filial piety as a strategy to help Chinese people maintain good mental health in the face of pandemic crises.

COVID-19 has created significant concern surrounding the impact of pandemic lockdown on mental health. While the pandemic lockdown can be distressing, times of crisis can also provide people with the opportunity to think divergently and explore different activities. Novelty seeking, where individuals explore novel and unfamiliarly stimuli and environments, may enhance the creativity of individuals to solve problems in a way that allows them to adjust their emotional responses to stressful situations. This study employs a longitudinal design to investigate changes in novelty seeking and mental health outcomes (namely, stress, anxiety, and depression) before, during, and after COVID-19 pandemic lockdown, among a group of students (final N = 173; Mage = 19.81; SDage = 0.98; 135 females and 38 males) from a university in southeast China. Participants were surveyed at three points: November, 2019 (prior to the COVID-19 pandemic); between February and March, 2020 (during the peak of the pandemic and intense lockdown in China); and between May and June, 2020 (after lockdown had been lifted in China). Cross-sectionally, correlation analysis indicated that greater novelty seeking was associated with lower levels of stress, anxiety, and depression at all three time points. Univariate latent curve modeling (LCM) indicated a growth trajectory in which novelty seeking increased over time and then remained high during the post-lockdown period. Stress, anxiety, and depression all showed V-shaped growth trajectories in which these variables decreased during lockdown, before increasing in the post-lockdown period. Multivariate LCM indicated the growth trajectory for novelty seeking was associated with the growth trajectories for stress, anxiety, and depression. This suggests that the observed decreases in stress, anxiety, and depression during the lockdown period may be attributable to the sample’s observed increase in novelty seeking. These findings are valuable in that they challenge the notion that lockdown measures are inherently detrimental to mental health. The findings indicate the important role of novelty seeking in responding to crises. It may be possible for future public health measures to incorporate the promotion of novelty seeking to help individuals’ respond to stressful situations and maintain good mental health in the face of crises.

This work examined quantitatively the key synoptic features influencing the high-impact heavy rainfall event in Beijing, China, on 21 July 2012 using both correlation analysis based on global ensemble forecasts (from TIGGE) and a method previously used for observation targeting. The global models were able to capture the domain-averaged rainfall of >100 mm but underestimated rainfall beyond 200 mm with an apparent time lag. In this particular case, the ensemble forecasts of the National Centres for Environmental Prediction (NCEP) had apparently better performance than those of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the China Meteorological Administration (CMA), likely because of their high accuracies in capturing the key synoptic features influencing the rainfall event. Linear correlation coefficients between the 24-h domain-averaged precipitation in Beijing and various variables during the rainfall were calculated based on the grand ensemble forecasts from ECMWF, NCEP and CMA. The results showed that the distribution of the precipitation was associated with the strength and the location of a mid-level trough in the westerly flow and the associated low-level low. The dominant system was the low-level low, and a stronger low with a location closer to the Beijing area was associated with heavier rainfall, likely caused by stronger low-level lifting. These relationships can be clearly seen by comparing a good member with a bad member of the grand ensemble. The importance of the trough in the westerly flow and the low-level low was further confirmed by the sensitive area identified through sensitivity analyses with conditional nonlinear optimal perturbation method.

Inflammation and reactive oxygen species (ROS) play important roles in the pathogenesis of atherosclerosis. Resveratrol has been shown to possess anti-inflammatory and antioxidative stress activities, but the underlying mechanisms are not fully understood. In the present study, we investigated the molecular basis associated with the protective effects of resveratrol on tumor necrosis factor-alpha (TNF-α)-induced injury in human umbilical endothelial cells (HUVECs) using a variety of approaches including a cell viability assay, reverse transcription and quantitative polymerase chain reaction, western blot, and immunofluorescence staining. We showed that TNF-α induced CD40 expression and ROS production in cultured HUVECs, which were attenuated by resveratrol treatment. Also, resveratrol increased the expression of sirtuin 1 (SIRT1); and repression of SIRT1 by small-interfering RNA (siRNA) and the SIRT1 inhibitor Ex527 reduced the inhibitory effects of resveratrol on CD40 expression and ROS generation. In addition, resveratrol downregulated the levels of p65 and phospho-p38 MAPK, but this inhibitory effect was attenuated by the suppression of SIRT1 activity. Moreover, the p38 MAPK inhibitor SD203580 and the nuclear factor (NF)-κB inhibitor pyrrolidine dithiocarbamate (PDTC) achieved similar repressive effects as resveratrol on TNF-α-induced ROS generation and CD40 expression. Thus, our study provides a mechanistic link between resveratrol and the activation of SIRT1, the latter of which is involved in resveratrol-mediated repression of the p38 MAPK/NF-κB pathway and ROS production in TNF-α-treated HUVECs.

Abstract Background and objectives Congenital heart defect (CHD) is one of the most common birth defects. The aim of this cohort study was to evaluate the prevalence of chromosomal abnormalities and the clinical utility of chromosomal microarray analysis (CMA) in fetuses with different types of CHD, aiming to assist genetic counseling and clinical decision-making. Methods In this study, 642 fetuses with CHD were enrolled from a single center over a six-year period (2017–2022). Both conventional karyotyping and CMA were performed simultaneously on these fetuses. Results The diagnostic yield of CMA in fetuses with CHD in our study was 15.3% (98/642). Our findings revealed a significant increase in the diagnostic yield of CMA compared to karyotyping in fetuses with CHD. Among CHD subgroups, the diagnostic yields were high in complex CHD (34.9%), conotruncal defects (28.6%), right ventricular outflow tract obstructive defects (RVOTO) (25.9%), atrioventricular septal defects (AVSD) (25.0%) and left ventricular outflow tract obstructive defects (LVOTO) (24.1%), while those in other CHD (10.6%) and septal defects (10.9%) were relatively low. The overall detection rate of clinically significant chromosomal abnormalities was significantly higher in the non-isolated CHD group compared to the isolated CHD group (33.1% vs. 9.9%, P