Seasonal variation and human impacts of the river biofilm bacterial communities in the Shiting River in southeastern China.

Bacterial communities in epilithic biofilm plays an important role in biogeochemistry processes in freshwater ecosystems. Nevertheless, our understanding of the geographical and seasonal variations of the composition of bacterial communities in the biofilm of gravels on river bed is still limited. Various anthropogenic activities also influence the biofilm bacteria in gravel rivers. By taking the Shiting River in the upper Yangtze River basin in Sichuan Province as an example, we studied the geographical and seasonal variations of epilithic bacteria and the impacts of weirs and other human activities (e.g., sewage pollution). The river has experienced severe degradation since the Ms 8.0 Wenchuan Earthquake, and weirs were constructed to prevent bed erosion. We collected epilithic biofilms samples at 17 sites along ~ 30 km river reach of the Shiting River in the autumn of 2021 and the summer of 2022, respectively. We applied 16S rRNA gene high-throughput sequencing technology and Functional Annotation of Prokaryotic Taxa (FAPROTAX) to analyze the seasonal and biogeographic patterns and potential functions of the biofilm bacterial communities. The results showed that epilithic bacteria from the two surveys exhibited variation in community composition, bacterial diversity and potential functions. The bacteria samples collected in the autumn have much higher alpha diversity and richness than those collected in the summer. Bacterial richness and diversity were lower downstream of the weirs than upstream. Low diversity was observed at a sampling site influenced by sewage inflow, which contains high level of nitrogen-related chemicals.

Direct three-dimensional segmentation of prostate glands with nnU-Net.

Significance: In recent years, we and others have developed non-destructive methods to obtain three-dimensional (3D) pathology datasets of clinical biopsies and surgical specimens. For prostate cancer risk stratification (prognostication), standard-of-care Gleason grading is based on examining the morphology of prostate glands in thin 2D sections. This motivates us to perform 3D segmentation of prostate glands in our 3D pathology datasets for the purposes of computational analysis of 3D glandular features that could offer improved prognostic performance. Aim: To facilitate prostate cancer risk assessment, we developed a computationally efficient and accurate deep learning model for 3D gland segmentation based on open-top light-sheet microscopy datasets of human prostate biopsies stained with a fluorescent analog of hematoxylin and eosin (H&E). Approach: For 3D gland segmentation based on our H&E-analog 3D pathology datasets, we previously developed a hybrid deep learning and computer vision-based pipeline, called image translation-assisted segmentation in 3D (ITAS3D), which required a complex two-stage procedure and tedious manual optimization of parameters. To simplify this procedure, we use the 3D gland-segmentation masks previously generated by ITAS3D as training datasets for a direct end-to-end deep learning-based segmentation model, nnU-Net. The inputs to this model are 3D pathology datasets of prostate biopsies rapidly stained with an inexpensive fluorescent analog of H&E and the outputs are 3D semantic segmentation masks of the gland epithelium, gland lumen, and surrounding stromal compartments within the tissue. Results: nnU-Net demonstrates remarkable accuracy in 3D gland segmentations even with limited training data. Moreover, compared with the previous ITAS3D pipeline, nnU-Net operation is simpler and faster, and it can maintain good accuracy even with lower-resolution inputs. Conclusions: Our trained DL-based 3D segmentation model will facilitate future studies to demonstrate the value of computational 3D pathology for guiding critical treatment decisions for patients with prostate cancer.

An end-to-end workflow for nondestructive 3D pathology.

Recent advances in 3D pathology offer the ability to image orders of magnitude more tissue than conventional pathology methods while also providing a volumetric context that is not achievable with 2D tissue sections, and all without requiring destructive tissue sectioning. Generating high-quality 3D pathology datasets on a consistent basis, however, is not trivial and requires careful attention to a series of details during tissue preparation, imaging and initial data processing, as well as iterative optimization of the entire process. Here, we provide an end-to-end procedure covering all aspects of a 3D pathology workflow (using light-sheet microscopy as an illustrative imaging platform) with sufficient detail to perform well-controlled preclinical and clinical studies. Although 3D pathology is compatible with diverse staining protocols and computationally generated color palettes for visual analysis, this protocol focuses on the use of a fluorescent analog of hematoxylin and eosin, which remains the most common stain used for gold-standard pathological reports. We present our guidelines for a broad range of end users (e.g., biologists, clinical researchers and engineers) in a simple format. The end-to-end workflow requires 3-6 d to complete, bearing in mind that data analysis may take longer.

Quality appraisal of clinical practice guidelines for the management of Dysphagia after acute stroke.

Objectives: Dysphagia is a common complication in stroke patients, widely affecting recovery and quality of life after stroke. The objective of this systematic review is to identify the gaps that between evidence and practice by critically assessing the quality of clinical practice guidelines (CPGs) for management of dysphagia in stroke. Methods: We systematically searched academic databases and guideline repositories between January 1, 2014, and August 1, 2023. The Appraisal of Guidelines for Research and Evaluation (AGREE II) instrument was used by two authors to independently assess CPG quality. Results: In a total of 14 CPGs included, we identified that three CPGs obtained a final evaluation of "high quality," nine CPGs achieved "moderate quality" and two CPGs received "low quality." The domain of "scope and purpose" achieved the highest mean score (91.1%) and the highest median (IQR) of 91.7% (86.1, 94.4%), while the domain of "applicability" received the lowest mean score (55.8%) and the lowest median (IQR) of 55.4% (43.2, 75.5%). Conclusion: The CPG development group should pay more attention to improving the methodological quality according to the AGREE II instrument, especially in the domain of "applicability" and "stakeholder involvement;" and each item should be refined as much as possible.

Miniature line-scanned dual-axis confocal microscope for versatile clinical use.

A miniature optical-sectioning fluorescence microscope with high sensitivity and resolution would enable non-invasive and real-time tissue inspection, with potential use cases including early disease detection and intraoperative guidance. Previously, we developed a miniature MEMS-based dual-axis confocal (DAC) microscope that enabled video-rate optically sectioned in vivo microscopy of human tissues. However, the device's clinical utility was limited due to a small field of view, a non-adjustable working distance, and a lack of a sterilization strategy. In our latest design, we have made improvements to achieve a 2x increase in the field of view (600 × 300 µm) and an adjustable working distance range of 150 µm over a wide range of excitation/emission wavelengths (488-750 nm), all while maintaining a high frame rate of 15 frames per second (fps). Furthermore, the device is designed to image through a disposable sterile plastic drape for convenient clinical use. We rigorously characterize the performance of the device and show example images of ex vivo tissues to demonstrate the optical performance of our new design, including fixed mouse skin and human prostate, as well as fresh mouse kidney, mouse intestine, and human head and neck surgical specimens with corresponding H&E histology. These improvements will facilitate clinical testing and translation.

MicroRNA-206-3p suppresses hepatic lipogenesis and cholesterol synthesis while driving cholesterol efflux.

BACKGROUND AND AIMS: Hepatosteatosis, hypertriglyceridemia, and hypercholesterolemia are interconnected metabolic disorders. This study is designed to characterize how microRNA-206-3p (miR-206) simultaneously prevents de novo lipogenesis (DNL), cholesterol synthesis, and VLDL production in hepatocytes while promoting cholesterol efflux in macrophages. APPROACH AND RESULTS: MiR-206 levels were reduced in hepatocytes and macrophages of mice subjected to a high-fat, high-cholesterol diet. A negative feedback between LXRα (liver X receptor alpha) and miR-206 is formed to maintain high LXRα and low miR-206 in hepatocytes. Systemic administration of miR-206 alleviated hepatosteatosis, hypertriglyceridemia, and hypercholesterolemia in mice. A significant reduction in LDL cholesterol and VLDL cholesterol but unaltered HDL cholesterol was observed in miR-206-treated mice. Mirroring these findings, miR-206 reprogrammed the transcriptome of hepatocytes towards the inhibition of DNL, cholesterol synthesis, and assembly and secretion of VLDL. In macrophages, miR-206 activated the expression of genes regulating cholesterol efflux. Hepatocyte-specific expression of miR-206 reduced hepatic and circulating triglycerides and cholesterol, as well as VLDL production, while transplantation of macrophages bearing miR-206 facilitated cholesterol efflux. Mechanistically, miR-206 directly targeted Lxrα and Hmgcr in hepatocytes but facilitated expression of Lxrα in macrophages by targeting macrophage-specific tricho-rhino-phalangeal syndrome 1 (TRPS1), a transcription repressor of Lxrα . By targeting Hmgc r and Lxrα , miR-206 inhibited DNL, VLDL production, and cholesterol synthesis in hepatocytes, whereas it drove cholesterol efflux by activating the TRPS1-LXRα axis. CONCLUSIONS: MiR-206, through differentially modulating LXRα signaling in hepatocytes and macrophages, inhibits DNL, promotes cholesterol efflux, and concurrently hinders cholesterol synthesis and VLDL production. MiR-206 simulates the functions of lipid-lowering medications, statins, and LXRα agonists.

Hederagenin protects against myocardial ischemia-reperfusion injury via attenuating ALOX5-mediated ferroptosis.

Hederagenin (HDG), a medical herb, is known for its beneficial activities against diverse diseases. The cardioprotective effect of HDG has been preliminarily disclosed, but the efficacy and underlying mechanism by which HDG protects against myocardial ischemia-reperfusion (MI/R) injury have not been elucidated yet. To simulate MI/R injury, the left anterior descending artery was occluded for 30 min and then reperfusion for 120 min in a rat model, and the cellular model of hypoxia-reoxygenation (H/R) injury was constructed in H9c2 cardiomyocytes. Hematoxylin-eosin, Prussian blue, and 2,3,5-triphenyl-2H-tetrazolium chloride (TTC) staining were conducted to assess the histological injury, iron deposition, and myocardial infarction. Myocardial enzymes and oxidative stress-related factors were detected using their commercial kits. Lipid peroxidation was measured using BODIPY581/591 probe, and iron content was detected. Cell counting kit (CCK)-8, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL), and flow cytometry assays were performed to assess cell viability and apoptosis. Protein levels were investigated by western blot. The interaction between HDG and 5-lipoxygenase (ALOX5) was verified using molecular docking. Our findings indicated that HDG significantly attenuated myocardial dysfunction by reducing infarction and myocardial injury. HDG significantly attenuated myocardial apoptosis in vitro and in vivo, as well as alleviating oxidative stress via reducing reactive oxygen species (ROS) and maintaining the balance between antioxidant and oxidant enzymes. Meanwhile, HDG inhibited I/R-induced ferroptosis in myocardium and cardiomyocytes, including reducing lipid peroxidation and iron level. Moreover, the binding relationship between HDG and ALOX5 was verified, and HDG could concentration dependently downregulate ALOX5. Furthermore, ALOX5 overexpression eliminated the inhibition of HDG on H/R-induced apoptosis, oxidative stress, and ferroptosis in H9c2 cardiomyocytes. HDG ameliorated myocardial dysfunction and cardiomyocyte injury by reducing apoptosis, oxidative stress, and ferroptosis through inhibiting ALOX5, providing a new perspective on the prevention and treatment of MI/R injury.

Constructing high-order functional networks based on hypergraph for diagnosis of autism spectrum disorders.

Introduction: High-order functional connectivity networks (FCNs) that reflect the connection relationships among multiple brain regions have become important tools for exploring the deep workings of the brain and revealing the mechanisms of brain diseases. The traditional high-order FCN constructed based on the "correlation of correlations" strategy, is a representative method for conducting whole-brain connectivity analysis and revealing global network characteristics. However, whole-brain connectivity analysis may be affected by noise carried by less important brain regions, resulting in redundant information and affecting the accuracy and reliability of the analysis. Moreover, this type of analysis has a high computational complexity. Methods: To address these issues, a new method for constructing high-order FCN based on hypergraphs is proposed in this article, which is used to accurately capture the real interaction relationships among brain regions. Specifically, first, a low-order FCN reflecting the connection relationships between pairs of brain regions based on resting-state functional Magnetic Resonance Imaging (rs-fMRI) time series is constructed, the method first constructs the low-order FCN that reflects the connection relationships between pairs of brain regions based on rs-fMRI time series, and then selects the "good friends" of each brain region from hypergraph perspective, which refers to the local friend circles with closer relationships. Then, the rs-fMRI time series corresponding to the "good friends" in each brain region's friend circle are averaged to obtain a sequence that reflects the intimacy between brain regions in each friend circle. Finally, hypergraph high-order FCN, which reflects the interaction relationships among multiple brain regions, is obtained by calculating the correlations based on the sequence of friend circles. Results: The experimental results demonstrate that the proposed method outperforms traditional high-order FCN construction methods. Furthermore, integrating the high-order FCN constructed based on hypergraphs and the low-order FCN through feature fusion to achieve complementary information improves the accuracy of assisting in the diagnosis of brain diseases. Discussion: In addition, the effectiveness of our method has only been validated in the diagnosis of ASD. For future work, we plan to extend this method to other brain connectivity patterns.

An end-to-end workflow for non-destructive 3D pathology.

Recent advances in 3D pathology offer the ability to image orders-of-magnitude more tissue than conventional pathology while providing a volumetric context that is lacking with 2D tissue sections, all without requiring destructive tissue sectioning. Generating high-quality 3D pathology datasets on a consistent basis is non-trivial, requiring careful attention to many details regarding tissue preparation, imaging, and data/image processing in an iterative process. Here we provide an end-to-end protocol covering all aspects of a 3D pathology workflow (using light-sheet microscopy as an illustrative imaging platform) with sufficient detail to perform well-controlled preclinical and clinical studies. While 3D pathology is compatible with diverse staining protocols and computationally generated color palettes for visual analysis, this protocol will focus on a fluorescent analog of hematoxylin and eosin (H&E), which remains the most common stain for gold-standard diagnostic determinations. We present our guidelines for a broad range of end-users (e.g., biologists, clinical researchers, and engineers) in a simple tutorial format.

Spatiotemporal transcriptomic atlas reveals the dynamic characteristics and key regulators of planarian regeneration.

Whole-body regeneration of planarians is a natural wonder but how it occurs remains elusive. It requires coordinated responses from each cell in the remaining tissue with spatial awareness to regenerate new cells and missing body parts. While previous studies identified new genes essential to regeneration, a more efficient screening approach that can identify regeneration-associated genes in the spatial context is needed. Here, we present a comprehensive three-dimensional spatiotemporal transcriptomic landscape of planarian regeneration. We describe a pluripotent neoblast subtype, and show that depletion of its marker gene makes planarians more susceptible to sub-lethal radiation. Furthermore, we identified spatial gene expression modules essential for tissue development. Functional analysis of hub genes in spatial modules, such as plk1, shows their important roles in regeneration. Our three-dimensional transcriptomic atlas provides a powerful tool for deciphering regeneration and identifying homeostasis-related genes, and provides a publicly available online spatiotemporal analysis resource for planarian regeneration research.

Experimental and Numerical Investigation of the Mechanical Properties of a CFRP Tendon-Wedge Assembly Loaded under Transverse Compressive Loading.

Carbon-fiber-reinforced polymer (CFRP) tendons have become a viable alternative to steel cables in cable roof structures owing to their high tensile strength, low weight, and resistance to corrosion. However, the effective anchoring of CFRP tendons is a challenge because of their poor transverse mechanical properties. Therefore, the mechanical properties of CFRP tendons and a tendon-wedge assembly under transverse compression were investigated by simulating the force environment of the CFRP tendon inside an integrated-wedge anchorage. The deformation of and local damage to CFRP tendons under transverse compression were explored using load-strain curves and full-field strain measured using digital image correlation. The experimental and numerical results show that large-diameter CFRP tendons with a length in the range of 90-110 mm had better cross-sectional deformation resistance and more stable transverse mechanical properties. Longer CFRP tendons with larger diameters have lower contact compressive stress and local maximal shear stress under the same transverse compressive load. Based on the analysis of the experimental and numerical results, we propose design suggestions for tendon size selection and integrated-wedge design details, such as the manufacturing materials of the wedge, the radius through the gap of the wedge, and the radial difference of the groove, to improve the anchoring properties and efficiency of the integrated-wedge anchorage.

Up-regulated lncRNA SNHG9 mediates the pathogenesis of dilated cardiomyopathy via miR-326/EPHB3 axis.

Dilated cardiomyopathy (DCM) is a common cause of heart failure and also a major indication for heart transplantation. It has been reported that long non-coding RNAs (lncRNAs) are involved in the development of various cardiac diseases. However, the roles of lncRNAs in DCM are not fully understood. In this study, we uncovered that serum SNHG9 (small nucleolar RNA host gene 9, a lncRNA) serves as a biomarker for dilated cardiomyopathy. GEO datasets (GSE124405) were re-analyzed to identify the aberrant lncRNAs in the plasma sample of patients with heart failure. The receiver operating characteristic (ROC) curve was used to assess the expression alterations of the aberrant lncRNAs including SNHG9, XIST, PLCK2-AS1, KIF9-AS1, ARHGAP31-AS1, LINC00482, etc. Using the area under curve (AUC) of ROC, we found that serum SNHG9 exhibits considerable performance in distinguishing DCM from normal control and DCM stage-III from stage-I/II (New York Heart Association Class). Furthermore, we determined the serum SNHG9 expression level of the doxorubicin (Dox)-induced DCM mice model, and found that the upregulated SNHG9 is negatively associated with heart function. Besides, the deletion of SNHG9 by AAV-9 alleviated heart injury in the Dox-induced mice model. Taken together, the current results suggest that SNHG9 is a novel regulatory factor in dilated cardiomyopathy development.

Machine learning prognosis model based on patient-reported outcomes for chronic heart failure patients after discharge.

BACKGROUND: Patient-reported outcomes (PROs) can be obtained outside hospitals and are of great significance for evaluation of patients with chronic heart failure (CHF). The aim of this study was to establish a prediction model using PROs for out-of-hospital patients. METHODS: CHF-PRO were collected in 941 patients with CHF from a prospective cohort. Primary endpoints were all-cause mortality, HF hospitalization, and major adverse cardiovascular events (MACEs). To establish prognosis models during the two years follow-up, six machine learning methods were used, including logistic regression, random forest classifier, extreme gradient boosting (XGBoost), light gradient boosting machine, naive bayes, and multilayer perceptron. Models were established in four steps, namely, using general information as predictors, using four domains of CHF-PRO, using both of them and adjusting the parameters. The discrimination and calibration were then estimated. Further analyze were performed for the best model. The top prediction variables were further assessed. The Shapley additive explanations (SHAP) method was used to explain black boxes of the models. Moreover, a self-made web-based risk calculator was established to facilitate the clinical application. RESULTS: CHF-PRO showed strong prediction value and improved the performance of the models. Among the approaches, XGBoost of the parameter adjustment model had the highest prediction performance with an area under the curve of 0.754 (95% CI: 0.737 to 0.761) for death, 0.718 (95% CI: 0.717 to 0.721) for HF rehospitalization and 0.670 (95% CI: 0.595 to 0.710) for MACEs. The four domains of CHF-PRO, especially the physical domain, showed the most significant impact on the prediction of outcomes. CONCLUSION: CHF-PRO showed strong prediction value in the models. The XGBoost models using variables based on CHF-PRO and the patient's general information provide prognostic assessment for patients with CHF. The self-made web-based risk calculator can be conveniently used to predict the prognosis for patients after discharge. CLINICAL TRIAL REGISTRATION: URL: http://www.chictr.org.cn/index.aspx ; Unique identifier: ChiCTR2100043337.

Multiple Component Pharmacokinetics after Oral Administration of Gnaphalium affine Extract in Rats.

Gnaphalium affine is traditionally used to treat hyperuricemia and gout in China. Recently, the hypouricemic and renal protective effects of G. affine extract (GAD) have been deeply evaluated. However, little is known about the pharmacokinetics (PKs) of bioactive constituents in GAD. This study is aimed at investigating the individual and holistic pharmacokinetics of 10 bioactive components (including caffeic acid, caffeoylquinic acids, and flavonoids) in rats after single and multiple administrations of GAD. GAD is orally dosed to normal male rats at doses of 225, 450, or 900 mg/kg/day for 10 consecutive days and also orally administrated to uric acid nephropathy (UAN) rats at a dose of 900 mg/kg/day for 28 consecutive days. Integrated PKs of multiple components are calculated by area under the curve (AUC)-based weighting approach. All the components show a double-peak phenomenon in terms of their plasma concentration-time curves, suggesting that the components undergo enterohepatic circulation. The integrated AUC increases in a good dose-proportional manner with GAD dose. Compared with that in normal rats, the plasma exposure of caffeic acid and caffeoylquinic acids increases by 2.3- to 4.3-fold after 10-day chronic treatment of 900 mg/kg GAD in UAN rats. Modest drug accumulation is observed after 28-day chronic treatment.

A clinical decision support system for predicting coronary artery stenosis in patients with suspected coronary heart disease.

Invasive coronary angiography imposes risks and high medical costs. Therefore, accurate, reliable, non-invasive, and cost-effective methods for diagnosing coronary stenosis are required. We designed a machine learning-based risk-prediction system as an accurate, noninvasive, and cost-effective alternative method for evaluating suspected coronary heart disease (CHD) patients. Electronic medical record data were collected from suspected CHD patients undergoing coronary angiography between May 1, 2017, and December 31, 2019. Multi-Class XGBoost, LightGBM, Random Forest, NGBoost, logistic models and MLP were constructed to identify patients with normal coronary arteries (class 0: no coronary artery stenosis), minimum coronary artery stenosis (class 1: 0 < stenosis <50%), and CHD (class 2: stenosis ≥50%). Model stability was verified externally. A risk-assessment and management system was established for patient-specific intervention guidance. Of 1577 suspected CHD patients, 81 (5.14%) had normal coronary arteries. The XGBoost model demonstrated the best overall classification performance (micro-average receiver operating characteristic [ROC] curve: 0.92, macro-average ROC curve: 0.89, class 0 ROC curve: 0.88, class 1 ROC curve: 0.90, class 2 ROC curve: 0.89), with good external verification. In class-specific classification, the XGBoost model yielded F1 values of 0.636, 0.850, and 0.858, for Classes 0, 1, and 2, respectively. The visualization system allowed disease diagnosis and probability estimation, and identified the intervention focus for individual patients. Thus, the system distinguished coronary artery stenosis well in suspected CHD patients. Personalized probability curves provide individualized intervention guidance. This may reduce the number of invasive inspections in negative patients, while facilitating decision-making regarding appropriate medical intervention, improving patient prognosis.

Dynamic Trajectory of a Patient-Reported Outcome and Its Associated Factors for Patients with Chronic Heart Failure: A Growth Mixture Model Approach.

Purpose: This study aimed to identify subgroups of chronic heart failure (CHF) patients with distinct trajectories of quality of life (QOL) and to identify baseline characteristics associated with the trajectories. Patients and methods: Two-year, prospective, cohort study including 315 patients with CHF was conducted from July 2017. Information on QOL assessed by CHF-patient-reported outcomes measure (CHF-PROM) was collected at baseline, 6, 12, 18, and 24 months. Demographic and clinical variables were recorded at baseline. Growth mixture model was used to identify distinct trajectories of CHF-PROM and its physical, psychological, social, and therapeutic domains. Single factor analysis was employed to assess the factors associated with development of CHF-PROM over time. Results: Two classes of overall score of CHF-PROM were identified: poorer (14.0%) and better (86.0%). Poorer class tended to be aged, have low diastolic blood pressure, have concomitant atrial fibrillation, diabetes, chronic obstructive pulmonary disease, cancers, and central nervous system diseases, and used nitrates. Three classes of physical scores were identified: unstable-poorer (5.2%), stable-poorer (29.4%) and better (65.4%). Age, NYHA grade, chronic obstructive pulmonary disease, combined with cancers and central nervous system diseases were related to the grouping. Poorer (8.6%) and better (91.4%) classes of psychological scores were identified. Poorer class tended to be female and had concomitant atrial fibrillation. Degenerate class (34.6%) and meliorate class (65.4%) of therapeutic scores were identified. Degenerate class tended to have concomitant chronic obstructive pulmonary disease and use less angiotensin converting enzyme inhibitors. Conclusion: We identified different classes with distinct trajectories of QOL that may help proper evaluate QOL and further improve its status for patients CHF.

The Causal Effects of Anxiety-Mediated Social Support on Death in Patients with Chronic Heart Failure: A Multicenter Cohort Study.

Background: Chronic heart failure (CHF) affects more than 3.8 million people worldwide. There is a paucity of studies focusing on psychosocial issues in CHF patients. This study aimed to investigate the association of social support, mental adjustment and death to exploring whether mental adjustment could mediate the relationship. Methods: From May 2017 to June 2021, we conducted a multicenter clinical study to collect 1552 patients data. The Patient Report Outcome (PRO) scale were disseminated to collect information in the physical, psychological, social and therapeutic domains of patients. Marginal structural model was used to investigate the association of social support and CHF death, and the role of mental adjustment in their mediation. Results: The direct effect of social support accounted for 44.76% of the total effect. High social support (≥14 points) reduced mortality by 46.3% (RR=0.537, P=0.027), medium social support (11-14 points) reduced mortality by 45.3% (RR=0.547, P=0.042). Anxiety (effect percentage: 24.63%) and appetite-sleep quality (effect percentage: 30.61%) played a mediating role between social support and death in CHF patients. In women, aged >75 years, divorced or widowed patients were most prone to anxiety due to inadequate support (RR=0.519, P=0.019; RR=0.403, P=0.002; RR=0.413, P=0.041). Family care and socioeconomic assistance significantly reduced the risk of death (RR=0.689, P=0.040; RR=0.584, P=0.012). Conclusion: Social support can reduce patient mortality, especially family care and social economic assistance. The elderly, female, divorced or widowed patients are more likely to cause mental illness due to inadequate social support.

Social and therapeutic decline earlier than physical and psychological domains after discharge in heart failure patients: A patient-reported outcome measurements of latent transition analysis.

Background: Among patients with chronic heart failure (CHF), response shifts are common in assessing treatment effects. However, few studies focused on potential response shifts in these patients. Materials and methods: Data of CHF patient-reported outcome measures (PROMs) were obtained from three hospitals in Shanxi, China, from 2017 to 2019. A total of 497 patients were enrolled and followed up at 1 month and 6 months after discharge. Latent transition analysis (LTA) was employed to determine the longitudinal transition trajectories of latent subtypes in CHF patients in the physiological, psychological, social, and therapeutic domains. Results: The patients were divided into high- and low-level groups in the four domains according to the LTA. One month after discharge, the physiological and psychological domains improved, while the social and therapeutic domains remained unchanged. Six months after discharge, the former remained stable, but the latter deteriorated. The factors affecting the state transition in four domains were as follows. The influencing factor of the physiological domains are gender, age, tea consumption, smoking, alcohol consumption, physical activity, and light diet; those of the psychological domain are gender, occupation, smoking, alcohol consumption, and physical activity; those of the social domains are age; those of the therapeutic domains are education and income. Conclusion: The disease status of CHF patients has shifted over time. Risk factors accelerate the deterioration of patients' condition. Furthermore, the risk factors of social and therapeutic domains deteriorate patients' condition faster than those of physiological and psychological domains. Therefore, individualized intervention programs should be given for CHF patients who may be transferred to the low-level groups to maintain the treatment effect and improve the prognosis.

A review of cardiovascular benefits of SGLT2 inhibitors.

Sodium-glucose cotransporter 2 inhibitor (SGLT2I) is a new type of hypoglycemic drug that targets the kidney. As research continues to advance on this topic, it has been found that SGLT2I has multiple protective effects, such as hypoglycemic, cardio-renal protective, antihypertensive, and lipid-lowering effects. This review discusses the current concepts and possible mechanisms of SGLT2I in the treatment of heart failure, myocardial infarction, hypertension, cardiomyopathy and arrhythmia to provide a reference for clinicians to use drugs more reasonably and scientifically.

RIP3 Contributes to Cardiac Hypertrophy by Influencing MLKL-Mediated Calcium Influx.

Receptor-interacting protein 3(RIP3), a RIP family member, has been reported as a critical regulator of necroptosis and involves in the pathogenesis of various heart diseases. However, its role in the development of myocardial hypertrophy after pressure overload is unclear. We aimed to investigate the roles of RIP3 in pathological cardiac hypertrophy. A rat model of myocardial hypertrophy induced by the aortic banding method was used in this study. Neonatal rat cardiomyocytes (NRCMs) were stimulated with angiotensin II (Ang-II) or phenylephrine (PE) to induce neurohumoral stress. Our results showed that RIP3 level was significantly elevated in the hypertrophic myocardium tissues from patients, rats subjected to AB surgery, and NRCMs treated with Ang-II or PE. After downregulation of RIP3 expression in NRCMs, the phenotypes of myocardial hypertrophy were obviously alleviated. In mechanism, we demonstrated that RIP3 interacts with mixed lineage kinase domain-like protein (MLKL) and promotes its cell membrane localization to increase the influx of calcium within cells, thereby mediating the development of myocardial hypertrophy. More interestingly, we found the blockage of calcium influx by 2-aminoethoxydiphenyl borate, and lanthanum chloride efficiently reverses RIP3-induced cardiac remodeling in NRCMs. Taken together, our findings indicate a key role of the RIP3-MLKL signaling pathway in myocardial hypertrophy, which may be a novel promising treatment strategy for myocardial hypertrophy.