China has become the country with the highest global burden of heart failure(HF).Despite the widespread use of prognostic-improving medications today,the mortality rate of HF remains high,reaching 13.7％at one year-particularly among patients with heart failure with reduced ejection fraction(HFrEF).HF interventional device therapy(structural intervention)targets the structural factors underlying HF,including atrial pressure,ventricular remodeling,and valvular intervention.It leverages the heart's intrinsic physiological properties and pathological progression mechanisms to deliver treatments through interventions without external active forces,achieving anatomical or functional repair.This field has emerged as a rapidly growing area and plays an increasingly critical role in HF management.This article provides a comprehensive review and summary of the latest advancements in HF and cardiomyopathy interventional therapy over the past year.It covers various novel technologies and products currently in the research phase,aiming to provide an in-depth analysis of the current status and future directions of HF interventional therapy,and further advance the development of this discipline.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Icaritin(ICT)is an 8-isopentenylflavonoid,which is the main effective component of the tra-ditional Chinese medicine Epimedium.Previously,we found that Icaritin inhibits the growth of glioblasto-ma(GBM)cells.Herein we aim to study the in vivo anti-GBM effectiveness of Icaritin and explore its mechanism.The results of MTT assay,flow cytometry,comet assay and cellular immunofluorescence as-say in vitro showed that ICT inhibited the proliferation of four kinds of GBM cells,U87,U251,U118 and A172,induced early apoptosis(P＜0.001)and late apoptosis(P＜0.05)in U87 cells,induced DNA damage in U87 cells,and blocked the growth of U87 cells at the G0/G1 phase(P＜0.0001)in a concen-tration-time-dependent manner.In vivo subcutaneous tumor transplantation tumor experiments showed that feeding 200 mg/kg(P＜0.01)and 400 mg/kg(P＜0.001)ICT had a significant inhibitory effect on the growth of GBM subcutaneous tumors,and had no significant toxic effects on heart,liver,spleen,lung and kidney tissues.The results of network pharmacological analysis,molecular docking and cellular thermodynamic experiments showed that there were 26 possible target proteins between ICT and GBM,a-mong which the expression of p53 in GBM tissues was significantly(P＜0.001)higher than in normal tis-sues,and the binding energy of ICT and p53 was lower;cellular thermodynamic experiments verified that ICT significantly enriched the level of p53 in the living cells of GBM,which indicated that ICT could tar-get p53.The expression of key proteins in the DNA damage repair and apoptosis-associated FOXO signa-ling pathway was detected by ICT.The results showed that the expression of ATR(P＜0.01),P53(P＜0.001),P21(P＜0.05)and γ-H2AX(P＜0.05)was up-regulated,whereas the expression of Cyc-lin E1(P＜0.01),E2F1(P＜0.05),CDK2(P＜0.01),Rb(P＜0.001),p-Rb(P＜0.0001)and WRN(P＜0.0001)expression were down-regulated.There was no significant change in the expres-sion of FOXO 1 in the FOXO pathway or a significant down-regulation of its phosphorylation level.This study demonstrated that ICT could effectively inhibit the growth of GBM cells in vivo.It targets p53 to regulate the DNA damage repair pathway and FOXO signaling pathway to induce GBM cell cycle arrest and apoptosis.

Blood from a case of group B epidemic cerebrospinal meningitis identified in February 2024 in Ganzhou City,Jiangxi Province,and throat swabs from close contacts were collected for isolation and culture.The isolates were subjected to serogrouping,drug sensitivity testing,and whole genome sequencing and analysis,to provide a basis for epidemiological inves-tigation and clinical drug use.One strain of Neisseria meningitidis was isolated from the blood of the case and denoted group B.The MLST type was ST-7962,with no clonal group attribution.The phylogenetic tree showed that it was genetically close to the 1977 Shanghai carrier isolate(id-52231).Drug sensitivity results indicated that the strain was sensitive to 8 drugs:azithro-mycin,cefotaxime,minocycline,ceftriaxone,chloramphenicol,meropenem,rifampicin,and benzylpenicillin;resistant to cot-rimoxazole,levofloxacin,and ciprofloxacin;and showed an intermediate response to penicillin.This report describes the first case of ST-7962 group B meningoencephalitis found in Jiangxi Province.Monitoring of Neisseria meningitidis carriage,drug re-sistance,and molecular characteristics of strains in the healthy population in this region should be strengthened,to provide la-boratory support for the clinical use of medications,traceability,and control of the pathogen underlying meningoencephalitis infection.

BACKGROUND: Temozolomide (TMZ) resistance is a significant challenge in treating glioblastoma (GBM). Collagen remodeling has been shown to be a critical factor for therapy resistance in other cancers. This study aimed to investigate the mechanism of TMZ chemoresistance by GBM cells reprogramming collagens. METHODS: Key extracellular matrix components, including collagens, were examined in paired primary and recurrent GBM samples as well as in TMZ-treated spontaneous and grafted GBM murine models. Human GBM cell lines (U251, TS667) and mouse primary GBM cells were used for in vitro studies. RNA-sequencing analysis, chromatin immunoprecipitation, immunoprecipitation-mass spectrometry, and co-immunoprecipitation assays were conducted to explore the mechanisms involved in collagen accumulation. A series of in vitro and in vivo experiments were designed to assess the role of the collagen regulators prolyl 4-hydroxylase subunit alpha 1 (P4HA1) and yes-associated protein (YAP) in sensitizing GBM cells to TMZ. RESULTS: This study revealed that TMZ exposure significantly elevated collagen type I (COL I) expression in both GBM patients and murine models. Collagen accumulation sustained GBM cell survival under TMZ-induced stress, contributing to enhanced TMZ resistance. Mechanistically, P4HA1 directly binded to and hydroxylated YAP, preventing ubiquitination-mediated YAP degradation. Stabilized YAP robustly drove collagen type I alpha 1 ( COL1A1) transcription, leading to increased collagen deposition. Disruption of the P4HA1-YAP axis effectively reduced COL I deposition, sensitized GBM cells to TMZ, and significantly improved mouse survival. CONCLUSION P4HA1 maintained YAP-mediated COL1A1 transcription, leading to collagen accumulation and promoting chemoresistance in GBM.
Temozolomide ; Humans ; Glioblastoma/drug therapy* ; Animals ; Mice ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics* ; YAP-Signaling Proteins ; Hydroxylation ; Dacarbazine/pharmacology* ; Adaptor Proteins, Signal Transducing/metabolism* ; Transcription Factors/metabolism* ; Collagen/biosynthesis* ; Collagen Type I/metabolism* ; Prolyl Hydroxylases/metabolism* ; Antineoplastic Agents, Alkylating/therapeutic use*

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*