ObjectiveTo explore the mechanism of Yishen Qubi Tongluo Formula （益肾祛痹通络方， YQTF） in the treatment of rheumatoid arthritis（RA）. MethodsNetwork pharmacology was employed to retrieve and screen the active components and potential targets of YQTF as well as RA-related targets using databases including TCMSP， BATMAN， ETCM and GEO. The intersection of targets related to active components and RA-related targets was identified， and a protein-protein interaction （PPI） network was constructed. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed， and a drug-active component-common target network of YQTF in the treatment of RA was established. The core components of YQTF were molecularly docked with key targets. Human rheumatoid arthritis synovial fibroblast cell line MH7A was divided into blank group， model group， methotrexate group and YQTF group. The blank group was cultured with 10% fetal bovine serum， while the other three groups were stimulated with 10 μg/L of recombinant human tumor necrosis factor-α （TNF-α） for 24 h to establish the RA cell model. On this basis， the methotrexate group was treated with methotrexate suspension at a concentration of 20 μmol/L， and the YQTF group was treated with 10% YQTF-medicated serum. After 48 h of intervention， the levels of TNF-α and interleukin-17A（IL-17A）contents in cell supernatants were detected by enzyme-linked immunosorbent assay （ELISA）， and mRNA expressions of phosphatidylinositol 3-kinase（PI3K）， protein kinase B（AKT） and mammalian target of rapamycin（mTOR） were detected by real-time quantitative polymerase chain reaction （RT-qPCR）. ResultsNetwork pharmacological analysis identified 209 active components and 583 potential target genes of YQTF， as well as 818 RA-related targets. A total of 29 common targets were obtained from the intersection of drug-related targets and RA-related targets. Quercetin，β-sitosterol， kaempferol， stigmasterol and luteolin were the core active components of YQTF for the treatment of RA， while matrix metalloproteinase-9 （MMP9）， prostaglandin-endoperoxide synthase 2 （PTGS2）， Toll-like receptor 4 （TLR4）， tumor protein p53 （TP53） and transcription factor AP-1 subunit JUN were the key targets. The GO and KEGG pathway enrichment analysis showed that the involved biological processes and pathways were mainly associated with antioxidant responses， PI3K-AKT signaling pathway and Toll-like receptor （TLR） signaling pathway. Molecular docking results showed that MMP9 and PTGS2 exhibited high binding affinities with quercetin， β-sitosterol， kaempferol， stigmasterol and luteolin； TLR4 exhibited high binding activities with β-sitosterol， stigmasterol and luteolin； and TP53 showed high binding affinity with luteolin. The results of cell experiments showed that compared with the control group， the contents of TNF-α and IL-17A as well as the mRNA expressions of AKT and mTOR in the model group significantly increased （P＜0.05 or P＜0.01）. Compared with the model group， all the above indicators significantly decreased in the YQTF group， while the contents of TNF-α and the mRNA expression of AKT significantly decreased in the methotrexate group （P＜0.05 or P＜0.01）. ConclusionThe mechanism of YQTF in the treatment of RA may be associated with reducing inflammatory cytokine secretion and inhibiting the activation of the PI3K-AKT-mTOR signaling pathway.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Background/Aims: Treatment indications for patients with chronic hepatitis B (CHB) remain contentious, particularly for patients with mild alanine aminotransferase (ALT) elevation. We aimed to evaluate treatment effects in this patient population. Methods: This rollover study extended a placebo-controlled trial that enrolled non-cirrhotic patients with CHB and ALT levels below two times the upper limit of normal. Following 3 years of randomized intervention with either tenofovir disoproxil fumarate (TDF) or placebo, participants were rolled over to open-label TDF for 3 years. Liver biopsies were performed before and after the treatment to evaluate histopathological changes. Virological, biochemical, and serological outcomes were also assessed (NCT02463019). Results: Of 146 enrolled patients (median age 47 years, 80.8% male), 123 completed the study with paired biopsies. Overall, the Ishak fibrosis score decreased in 74 (60.2%), remained unchanged in 32 (26.0%), and increased in 17 (13.8%) patients (p<0.0001). The Knodell necroinflammation score decreased in 58 (47.2%), remained unchanged in 29 (23.6%), and increased in 36 (29.3%) patients (p=0.0038). The proportion of patients with an Ishak score ≥ 3 significantly decreased from 26.8% (n=33) to 9.8% (n=12) (p=0.0002). Histological improvements were more pronounced in patients switching from placebo. Virological and biochemical outcomes also improved in placebo switchers and remained stable in patients who continued TDF. However, serum HBsAg levels did not change and no patient cleared HBsAg. Conclusions In CHB patients with minimally raised ALT, favorable histopathological, biochemical, and virological outcomes were observed following 3-year TDF treatment, for both treatment-naïve patients and those already on therapy.

Gastric outlet obstruction (GOO) is a condition characterized by a mechanical obstruction of the stomach or duodenum, caused by either benign or malignant disease. Traditionally, surgical gastrojejunostomy (SGJ) has been the standard treatment for malignant GOO and endoscopic stenting (ES) offers a less invasive option, but it often requires repeat interventions. Recently, endoscopic ultrasound (EUS)-guided gastroenterostomy (EUS-GE), an innovative technique, has been applied as an alternative to SGJ and ES for GOO patients. Direct EUS-GE, device-associated EUS-GE, and EUS-guided double balloon-occluded gastrojejunostomy bypass are the most commonly used techniques with reported technical success rates ranging from 80% to 100%, and clinical success rates between 68% and 100%. Adverse event (AE) rates range from 0% to 28.2% and the stent misdeployment is the most common while other AEs include abdominal pain, bleeding, infection, peritonitis, bowel perforation, gastric leakage, and stent migration. It is clear that EUS-GE may achieve a similar clinical success to SGJ with fewer AEs and a shorter hospital stay. Compared to ES, EUS-GE showed higher clinical success, fewer stent obstructions, and lower reintervention rates.

ObjectiveTo develop a systematic case management model based on the International Classification of Functioning, Disability and Health (ICF) Vocational Rehabilitation Core Set (VR-CS) and explore its application pathways and efficacy in vocational rehabilitation. The 13 core categories of VR-CS are applied in vocational rehabilitation case management practices, utilizing comprehensive functional assessments to design and implement structured and individualized case management plans. This, in turn, seeks to enhance individuals' vocational independence, social participation and overall quality of life. MethodsThis study adopted a combined approach of theoretical research and empirical case analysis. Based on the 13 core categories of VR-CS, a comprehensive vocational assessment was conducted across three dimensions: body function and structure, activities and participation, and environmental factors. The study theoretically analyzed how to develop and implement holistic and individualized vocational rehabilitation plans, along with dynamic monitoring processes. Three types of typical vocational rehabilitation cases were examined, including individuals with major depressive disorder, high-functioning autism and mild cognitive impairment, to illustrate the evidence and effectiveness of VR-CS-based case management. ResultsThe VR-CS-based case management method, grounded in the ICF bio-psycho-social model, constructed an integrated and individualized case management system. This system combined the assessment and analysis of vocational rehabilitation needs, goal setting and planning, multidisciplinary team intervention, individualized interventions, process monitoring and dynamic adjustments, return-to-work activities, and long-term follow-up services.The case management model developed through VR-CS demonstrated significant and systematic efficacy in promoting vocational independence and social participation. This study provided a detailed analysis of the primary methods and steps involved in designing and implementing case management and elaborates on the practical applications of this model from the three representative cases. At the body function and structure level, case management included the evaluation of energy and drive functions (b130), high-level cognitive training (b164), and the enhancement of exercise tolerance (b455). Case management focused on accurately setting short- and long-term goals around functional limitations and needs. Dynamic monitoring during interventions ensured timely adjustments to intervention measures. This process improved physical endurance and cognitive function, enhanced sustained work capacity in complex vocational environments. At the activities and participation level, the focus was on skill acquisition (d155), stress management and psychological adjustment (d240), and the cultivation of complex interpersonal communication abilities (d720). Individuals engaged in regular professional skills training, role-playing and simulated work scenarios to progressively enhance vocational adaptability and social interaction skills. Through this process, individuals acquired practical skills, gradually boosting self-efficacy and vocational confidence, thereby facilitating the reshaping of their social roles. At the environmental and personal factors level, case management pathways involved active participation from immediate family (e310), positive shifts in societal attitudes (e460), and the effective utilization of health and employment policy resources (e580, e590). By integrating social and community resources comprehensively, the program created a more inclusive and supportive rehabilitation environment. By designing and implementing systematic case management programs, individuals showed significant improvements in psychological well-being, vocational adaptability and social interaction skills. The majority of cases achieved stable employment or continued participation in social activities following the intervention. ConclusionVR-CS provides a systematic, multidimensional and person-centered case management framework. This framework applies the bio-psycho-social model, analyzing individuals' primary functional impairments and vocational rehabilitation needs from the perspectives of body functions, psychological states and environmental factors. On this basis, a comprehensive, targeted and holistic case management plan is developed and implemented. The VR-CS-based case management approach not only enhances vocational capabilities but also improves overall quality of life and social adaptability.

This study selected 6 529 plant-based Chinese materia medica(PCMM) from Chinese Materia Medica as research subjects and applied a random permutation test to explore the overall correlation characteristics between nature and flavor, as well as the correlation characteristics after distinguishing different medicinal parts and harvest seasons. The results showed that the overall correlation characteristics between nature and flavor in PCMM were significantly associated in the following pairs: cold and bitter, cool and bitter, cool and astringent, cool and light, neutral and sweet, neutral and astringent, neutral and light, neutral and sour, hot and pungent, and warm and pungent. When analyzing the data by distinguishing medicinal parts and/or harvest seasons, new correlation patterns emerged, characterized by the disappearance of some significant correlations and the emergence of new ones. When analyzing by medicinal parts alone, significant correlations were found in the following cases: cold and light in leaves, cold and salty in barks, cool and sweet in fruits and seeds, neutral and pungent in whole herbs, neutral and salty in stems, and warm and salty in flowers. However, no significant correlations were found between cool and bitter in stems and other types of herbs, cool and astringent in fruits, seeds, flowers, and other types of herbs, cool and light in leaves, fruits, seeds, barks, flowers and other types of herbs, neutral and sweet in barks, neutral and astringent in whole herbs and stems, neutral and light in leaves, fruits, seeds, and flowers, neutral and sour in whole herbs, stems, barks, flowers, and other types of herbs, and hot and pungent in whole herbs, stems, flowers, and other types of herbs. When analyzing by harvest season alone, significant correlations were found in the following cases: cold and salty, and cool and sour in herbs harvested in winter, and neutral and salty in herbs harvested year-round. However, no significant correlation was found between cool and light in herbs harvested in winter. When considering both medicinal parts and harvest seasons, compared to the independent influence of medicinal parts, 14 new significant correlations emerged(e.g., the correlation between cool and bitter in stems harvested in spring), while 53 previously significant correlations disappeared(e.g., the correlation between cool and bitter in barks harvested in summer). Compared to the independent influence of harvest seasons, 11 new significant correlations appeared(e.g., the correlation between cold and light in barks harvested in autumn), while 50 previously significant correlations disappeared(e.g., the correlation between hot and pungent in leaves harvested in winter). This study is the first to reveal the influence of medicinal parts and harvest seasons on the correlation between nature and flavor in PCMM, which highlights that these two factors can interact and jointly affect nature-flavor correlations. Further research is needed to explore the underlying mechanisms. This study provides a deeper understanding of the inherent scientific connotations of herbal properties and offers a theoretical foundation for the cultivation and harvesting of PCMM.
Seasons ; Plants, Medicinal/growth & development* ; Drugs, Chinese Herbal/chemistry* ; Taste

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.