BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Dental treatments for children and adolescents have unique clinical characteristics that differ from dental care for adults in terms of children's physiology, psychology, and behavior. These differences impose specific requirements on the application of local anesthesia in pediatric dental procedures. This article presents expert consensus on the principles of local anesthesia techniques in pediatric dental therapies, including the use of common anesthetic drugs and dosage control, safety and efficacy evaluation, and prevention and management of complications. The aim is to improve the safety and quality of pediatric dental treatments and offer guidance for clinical application by dentists.
Humans ; Child ; Anesthesia, Local/methods* ; Consensus ; Anesthesia, Dental/methods* ; Adolescent ; Anesthetics, Local/administration & dosage* ; Dental Care for Children

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To analyze the epidemiological and clinical features of infectious diseases of the central nervous system (CNS).Methods:A cross-sectional study and analysis were conducted to summarize the epidemiological and clinical characteristics of 9 918 patients with CNS infectious diseases, who were diagnosed and treated at 29 hospitals across China from January 1, 2001 to December 31, 2020. Data collected included demographic data, clinical manifestations, health economic indicators, and prognostic outcomes.Results:Among the 9 918 collected cases of CNS infectious diseases, 5 559 were male (56.0%) and 4 359 were female (44.0%), with an onset age of 38 (25, 53) years. Education level: slightly more junior high school education (2 651 cases, 26.7%), and less elementary school education and below (2 181 cases, 22.0%) were found. Occupational distribution: farmers were found predominant (3 215 cases, 32.4%), followed by workers (1 826 cases, 18.4%) and students (1 633 cases, 16.5%). Clinical manifestations: headache (6 074 cases, 61.2%), fever (5 869 cases, 59.2%) and positive meningeal irritation signs (2 273 cases, 22.9%) were the 3 most common clinical manifestations, followed by nausea and (or) vomiting (2 095 cases, 21.1%), impaired consciousness (2 077 cases, 20.9%), psychiatric symptom (1 866 cases, 18.8%) and epilepsy (1 627 cases, 16.4%), etc., and cranial nerve involvement was found in 669 cases (6.7%). Major pathogens included viruses in 6 814 cases (68.7%), Mycobacterium tuberculosis in 1 677 cases (16.9%), common bacteria in 864 cases (8.7%), fungi in 254 cases (2.6%), spirochetes of syphilis in 183 cases (1.8%), parasites in 121 cases (1.2%), and rickettsiae in 5 cases (0.1%). Urban-rural distribution: slightly more cases were found in the countryside (5 418 cases, 54.6%) than in the towns (4 500 cases, 45.4%). Distribution of onset by season: 2 412 cases (24.3%) fell ill in spring, 2 835 cases (28.6%) in summer, 2 187 cases (22.1%) in fall, and 2 484 cases (25.0%) in winter. Health economics: the duration of hospitalization was 15 (8, 27) days, and the cost of hospitalization was 1.53 (0.91, 3.02)×10 000 yuan. Prognosis: 9 531 cases (96.1%) were cured or improved, and 92 cases (0.9%) died. Conclusions:The pathogens responsible for CNS infectious diseases are predominantly viruses. Although the incidence is slightly higher during the summer months, the overall seasonal pattern is not particularly pronounced. These infections are more commonly observed in young and middle-aged males and present with a diverse range of clinical manifestations, contributing to a significant disease burden.

AIM: To investigate the clinical efficacy of pars plana vitrectomy(PPV)combined with fovea-sparing internal limiting membrane(ILM)peeling and silicone oil(SO)tamponade for treating pathological myopic foveoschisis(PMF).METHODS:This study is a retrospective observational analysis of 10 cases(10 eyes)diagnosed with PMF that underwent PPV with fovea-sparing ILM peeling and SO tamponade between January 2023 and November 2024. The best-corrected visual acuity(BCVA), central foveal thickness(CFT), foveoschisis(FS), and the detachment and reattachment of FS and macular fovea were assessed preoperatively and at 1 wk, 1 and 3 mo postoperatively.RESULTS:Among the 10 cases of PMF patients(10 eyes), the complete reattachment rate was 30%(3 eyes), while partial reattachment was observed in 70%(7 eyes). At 3 mo postoperatively, BCVA(LogMAR)was significantly improved to 0.957±0.393 compared with 1.432±0.509 before surgery(P<0.05), and both CFT(437.9±180.4 vs. 207.5±76.1 μm)and FS(686.5±172.2 vs. 290.7±86.6 μm)showed significant decreases(P<0.05). No complications such as macular hole, retinal detachment, silicone oil emulsification, or endophthalmitis were observed during the surgery or throughout the follow-up period.CONCLUSION:PPV with SO tamponade and fovea-sparing ILM peeling has been demonstrated to facilitate both visual acuity improvement and anatomical reattachment in cases of PMF.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

A scoping review was performed to systematically search and summarize the clinical research in the treatment of dysmenorrhea with oral Chinese patent medicines. The oral Chinese patent medicines for treating dysmenorrhea in three major drug lists, guidelines, and textbooks were screened, and the relevant clinical trials were retrieved from eight Chinese and English databases. The key information of the included trials was extracted and visually analyzed. A total of 50 Chinese patent medicines were included, among which oral Chinese patent medicines for the dysmenorrhea patients with the syndrome of Qi stagnation and blood stasis accounted for the highest proportion, and the average daily cost varied greatly among Chinese patent medicines. A total of 150 articles were included, involving 22 Chinese patent medicines, among which Guizhi Fuling Capsules/Pills, Sanjie Zhentong Capsules, and Dan'e Fukang Soft Extract were the most frequently studied. These articles mainly reported randomized controlled trial(RCT), which mainly focused on the comparison of the intervention effect between Chinese patent medicines combined with western medicine and western medicine alone, and the sample size was generally 51-100 cases. The high-frequency outcome indicators belonged to nine domains such as effective rate, adverse reactions, and laboratory examinations. This study showed that oral Chinese patent medicines had advantages in the treatment of dysmenorrhea, and the annual number of related clinical trials showed an overall growing trend. However, there were still problems such as insufficient safety information and vague description of traditional Chinese medicine(TCM) syndromes types in the instructions of Chinese patent medicines. The available clinical research had shortcomings such as uneven distribution of Chinese patent medicines, limited research scale, poor methodological rigor, and insufficient standardization of outcome indicators. In the future, it is necessary to deepen the development of high-quality clinical research and improve the contents of the instructions to ensure the effectiveness and safety of the clinical application of oral Chinese patent medicines in the treatment of dysmenorrhea.
Dysmenorrhea/drug therapy* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Administration, Oral ; Nonprescription Drugs/administration & dosage*

Aim To identify the chemical components of Angelica sinensis(AS)and explore the mechanism of AS in activating blood circulation.Methods UP-LC-Q-TOF-MS was used to identify the chemical com-ponents of AS.The changes of syndrome and patholog-ical section of heart in rats were observed.Hemody-namics and proteomics were measured.Results A to-tal of 270 compounds were identified from AS.It showed that rats of Angelica sinensis group were greatly improved such as arched back,shrugged fur,huddled up and less mobile,purplish paws and tails,whitish ear margins and nasolabial lips,reduced drinking and feed-ing,and slow response to external stimuli;mildly disor-dered myocardial fibre arrangement,myofibre arrange-ment was tighter than that of model group,myocardial fibres were narrower and close to normal,and mild oe-dema,exudation,and inflammatory cell infiltration could be seen in the surrounding area;SAP was signif-icantly lower and LVSP was significantly higher in An-gelica sinensis group(P＜0.05).Proteomics showed that 62 differential proteins were screened in Angelica sinensis group compared to model,GO function were concentrated in the extracellular matrix,cytoskeletal proteins binding and protein hydrolysis negatively regu-lated.KEGG pathway were enriched in signalling path-ways such as complement and coagulation cascades,cellular focal adhesion,leukocyte transendothelial mi-gration and chemokine signalling pathways.Conclu-sions AS probably through the expression of proteins,which modulate the signalling pathways of the comple-ment and coagulation cascade reactions and the con-traction of vascular smooth muscle.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.