Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

Objective: To develop a RHCE genotyping assay based on kompetitive allele-specific PCR (KASP) and assess its clinical accuracy for RhCE blood group determination. Methods: KASP primers were designed to interrogate three RHCE loci: the 109 bp insertion/deletion in intron 2, c. 307T>C, and c. 676C>G. A total of 1 194 RhD-positive inpatients from Chengdu were typed by both KASP genotyping and manual tube serology. Discordant samples (n=10) were retested by both methods and further resolved by Sanger sequencing. An additional 377 cases were tested for the c. 48C>G locus to evaluate the predictive accuracy of individual loci and combined locus testing for RhC antigen. Results: Genotyping concordance with serology was 100.0% for both the c. 676C>G locus (RhE/Rhe) and the c. 307T>C locus (Rhc). For RhC prediction using the 109 bp insertion, overall accuracy was 99.7% (1 191/1 194); the 3 discordant cases were confirmed by Sanger sequencing to be false negatives attributable to 109 bp deletion in intron 2. Testing the c. 48C>G allele for RhC prediction yielded 7 false positives, with an accuracy of 98.1% (370/377). RhC antigen status was determined by combining the 109 bp insertion and the c. 48C allele. After excluding 10 samples with inconsistent results between the two loci, the accuracy reached 100% in the remaining 367 samples. When both loci were applied in combination, accuracy reached 100% in the 367 cases with concordant results. Among the 1 194 patients, CCee (45.8%) and CcEe (31.7%) were the most common RhCE phenotypes. The e antigen had the highest positivity rate (92.2%), and the Ce haplotype was the most frequent (66.9%). Conclusion: The KASP-based RHCE genotyping method achieves high accuracy for clinical RhCE typing. Combining the 109 bp insertion/deletion with the c. 48C allele significantly improves RhC antigen prediction compared with either locus alone. This method was applied to RhCE genotyping of 1 194 RhD-positive inpatients in Chengdu, providing local RhCE phenotype and haplotype distribution data to support RhCE-matched transfusion practice.

Background/Aims: The pathophysiology of refractory gastroesophageal reflux disease (RGERD), which differs from proton pump inhibitor dependent gastroesophageal reflux disease (DGERD), remains incompletely elucidated. This study aims to compare esophageal motility patterns, transdiaphragmatic pressure gradients (TPG), and reflux profiles between RGERD and DGERD patients, and to delineate dynamic pressure gradient-esophagogastric junction (EGJ) interactions in these patients. Methods: In this retrospective study, 274 patients who underwent 24-hour impedance-pH monitoring and high-resolution manometry, along with an assessment of proton pump inhibitor responsiveness, were classified as RGERD (32.5%), DGERD (54.4%), or non-GERD (13.1%). Clinical characteristics, TPG, esophageal motility, and reflux metrics were compared between RGERD and DGERD patients. Subgroup analysis excluding hiatal hernia (HH) was conducted to investigate the pathophysiology of RGERD. Results: The RGERD group exhibited a significantly higher proportion of chest pain compared to the DGERD group. Regarding reflux profiles, RGERD patients without HH (RGERDHH- group) experienced increased weakly acidic reflux (P < 0.001) and prolonged bolus exposure (P = 0.006) compared to their counterparts (DGERDHH- group). Mechanistically, the RGERDHH- group showed reduced lower esophageal sphincter basal pressure (P = 0.010) and EGJ contractile integral (P = 0.005). Notably, following a wet-swallow, the RGERDHH- group experienced the significant elevation in gastric pressure and TPG. Correlation analyses revealed weakly acidic reflux and bolus exposure were positively correlated with gastric pressure variation, and inversely correlated with lower esophageal sphincter basal pressure. Conclusions Transient gastric pressure elevation and compromised EGJ barrier function drive weakly acidic reflux and esophageal bolus exposure. This pressure gradient-barrier mismatch underpins the refractoriness of RGERD.

Objective To develop and validate a machine learning model based on preoperative clinical characteristics, laboratory indices, and radiological features for the non-invasive prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma. Methods Preoperative data from patients with early-stage lung adenocarcinoma who underwent surgical resection at Northern Jiangsu People's Hospital between January 2020 and August 2025 were retrospectively collected. The data included clinical characteristics, laboratory indices, and radiological features. Patients were divided into a STAS-positive and a STAS-negative group based on postoperative pathological findings. The dataset was randomly split into a training set and a testing set at a 7 : 3 ratio. Feature variables were selected using the maximum relevance and minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression. Five machine learning models were constructed: logistic regression (LR), random forest (RF), support vector machine (SVM), light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The shapley additive explanations (SHAP) method was employed to interpret the optimal prediction model. Results A total of 377 patients were included, comprising 177 (46.9%) males and 200 (53.1%) females, with a mean age of (63.31±9.73) years. There were 261 patients in the training set and 116 patients in the testing set. In the training set, statistically significant differences were observed between the STAS-positive group (n=130) and STAS-negative group (n=131) across multiple features, including age, sex, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), clinical T stage, and maximum solid component diameter (P<0.05). A final set of 10 feature variables was selected by combining mRMR and LASSO regression, and five machine learning models (LR, RF, SVM, LightGBM, XGBoost) were developed. The XGBoost model demonstrated optimal performance in both the training and testing sets, achieving AUCs of 0.947 [95%CI (0.920, 0.975)] and 0.943 [95%CI (0.894, 0.993)], respectively. DCA indicated that the XGBoost model provided a high net clinical benefit across a wide range of threshold probabilities. SHAP analysis revealed that the vessel convergence sign, clinical T stage, age, consolidation-to-tumor ratio (CTR), and MLR were the features with the highest contributions to STAS prediction. Conclusion The XGBoost model effectively predicts preoperative STAS status in early-stage lung adenocarcinoma, exhibiting excellent discriminative performance and good clinical interpretability. Key predictors such as the vessel convergence sign, clinical T stage, age and CTR provide a crucial reference for preoperative risk assessment and the individualized selection of surgical strategies, ultimately benefiting patients.

ObjectiveTo investigate the patterns of chronic disease comorbidity among permanent elderly residents in Xuhui District of Shanghai, and to analyze the impact of different comorbidity patterns on the elderly’s ability to perform activities of daily living. MethodsBased on data from the 2015 and 2021 Surveys on Health Status and Health Service Utilization among Permanent Residents in Xuhui District of Shanghai, the study included permanent residents who fully participated in both surveys, were aged 60 years or older at the 2015 survey, self-reported having a chronic disease, and reported no significant changes in their chronic disease status between the two surveys. A prospective cohort study design was adopted, using the 2015 data as the baseline and the 2021 survey data as follow-up data. Physical examinations and questionnaire surveys were conducted by the Shanghai Xuhui District Center for Disease Control and Prevention in the subdistricts and towns within the jurisdiction from April to July in both 2015 and 2021. Latent class analysis (LCA) was used to classify comorbidity patterns across 11 types of chronic diseases. The smaller the values of the Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the sample-corrected Bayesian information criterion (aBIC), the better the model fits. The Barthel index (BI) and the Lawton and Brody Instrumental Activities of Daily Living Scale (LB-IADL) were used to assess the participants’ activities of daily living (ADL) and instrumental activities of daily living (IADL). Multiple linear regression and multivariate logistic regression models were used to analyze the association between different comorbidity patterns and ADL and IADL. ResultsA total of 1 608 study participants were enrolled. Among them, 671 (41.73%) self-reported having no chronic diseases. The prevalence of 11 types of chronic diseases was as follows: hypertension in 743 participants (46.21%), heart disease in 148 participants (9.20%), cerebrovascular disease in 37 participants (2.30%), diabetes or abnormal blood glucose in 310 participants (19.28%), other endocrine system diseases (non-diabetic) in 39 participants (2.43%), malignant tumors in 37 participants (2.30%), chronic lung disease in 16 participants (1.00%), gout in 8 participants (0.50%), musculoskeletal disorders in 34 participants (2.11%), gastric or digestive system diseases in 27 participants (1.68%), and dyslipidemia in 15 participants (0.93%). LCA was used to classify comorbidity patterns of chronic diseases among older adults into 1 to 9 latent category combinations. Model 5 (i.e., 5 latent categories) had the lowest BIC (7 112.69) and aBIC (6 909.38), with a relatively low AIC (6 768.20), indicating the best model fit; thus, five latent categories represented the optimal combination in this study. The five latent categories (and their respective proportions of study participants) were the healthy control group (41.73%), the hypertension group (31.28%), the diabetes-hypertension group (19.28%), the severe illness group (5.29%), and the other metabolic diseases group (2.43%). According to multiple linear regression analyses, compared with the healthy control group, the diabetes-hypertension group had significantly lower BI-20 scores (b=-0.952, 95%CI: -1.317‒ -0.587, P<0.001) and lower IADL scores (b=-0.744, 95%CI: -0.999‒ -0.489, P<0.001); the severe illness group (b=-0.644, 95%CI: -1.072‒ -0.217, P=0.003) and the hypertension group (b=-0.344, 95%CI: -0.562‒ -0.125, P=0.002) had lower IADL scores. According to multivariate logistic regression analyses, compared with the healthy control group, older adults in the diabetes-hypertension group had a higher risk of disability (OR=2.835, 95%CI: 1.392‒5.774), impaired ADL function (OR=2.470, 95%CI: 1.637‒3.726), and impaired IADL function (OR=1.739, 95%CI: 1.264‒2.392); older adults in the severe illness group had a higher risk of impaired ADL function (OR=2.206, 95%CI: 1.171‒4.155). ConclusionAmong the elderly participating in the Survey on Health Status and Health Service Utilization of Permanent Residents in Xuhui District of Shanghai, diabetes-hypertension is one of the key chronic disease comorbidity combinations and has adverse effects on both ADL and IADL. Community health management should prioritize the elderly with diabetes-hypertension comorbidity, and strengthen early screening and comprehensive interventions to slow the decline in ADL and IADL.

BackgroundStressful life events are associated with subclinical depressive and anxious symptoms， which may increase the risk of subsequent depressive and anxiety disorders. However， the mechanisms linking stressful life events to subclinical emotional symptoms remain unclear. ObjectiveTo explore the clinical characteristics of individuals with subclinical depression and anxiety following stressful events， and to analyze the mechanisms by which stressful events affect subclinical depressive and anxious symptoms， so as to provide a reference for the early identification and intervention of emotional symptoms in individuals under stress. MethodsFrom December 2024 to April 2025， 80 individuals with subclinical depression and/or anxiety （study group） and 80 healthy controls were recruited via the online official accounts of Beijing Anding Hospital， Capital Medical University and Beijing Huilongguan Hospital， Capital Medical University. Participants completed the Patients' Health Questionnaire Depression Scale-9 item （PHQ-9）， the Generalized Anxiety Disorder Scale-7 item （GAD-7）， the Life Event Scale （LES）， the Self-rating Idea of Suicide Scale （SIOSS）， and the Dysfunctional Attitude Scale （DAS）. Spearman rank correlation analysis was used to examine the associations in the study group. Serial mediation analyses were conducted using model 6 of Process version 4.1， to test whether cognitive distortion and hopelessness mediated the associations of stressful life events with subclinical depressive and anxious symptoms. ResultsCompared with healthy controls， participants with subclinical depressive and anxious symptoms had higher scores on PHQ-9， GAD-7， LES， SIOSS hopelessness subscale， and DAS scores （Z/t=10.294， 9.197， 4.659， 6.918， 3.517， P<0.01）. In the study group， GAD-7 score was positively correlated with LES， DAS， and SIOSS hopelessness subscale scores （r_s=0.233， 0.465， 0.588， P<0.05）； SIOSS hopelessness subscale score was positively correlated with DAS and LES scores （r_s=0.393， 0.309， P<0.01） and cognitive distortion was positively correlated with stressful life events（r_s=0.432， P<0.01）. Stressful life events were directly associated with subclinical anxiety symptoms （β=0.040， 95% CI： 0.015–0.065， P<0.05）， and showed a significant serial indirect association with subclinical anxiety symptoms （indirect effect=0.006， 95% CI： 0.001–0.017， P<0.01）， accounting for 7.15% of the total effect. Stressful life associated with subclinical depressive symptoms （β=0.087， 95% CI： 0.060–0.115， P<0.01）， however， the indirect effect through cognitive distortion and hopelessness were not statistically significant. ConclusionAfter experiencing stressful events， individuals with subclinical depression and anxiety exhibit more pronounced cognitive distortions and hopelessness. Stressful events can both directly affect subclinical anxiety symptoms and indirectly affect them through the serial mediating effects of cognitive distortion and hopelessness. Stressful events have a direct effect on subclinical depressive symptoms， whereas the mediating effects of cognitive distortion and hopelessness are no statistically significant. ［Funded by the Training Program for the Development of High-level Public Health Technical Talents （number， Academic Leader-01-22）； www.chictr.org.cn number， ChiCTR2400093516］

ObjectiveTo explore the effect of serum containing Zhenwutang on myocardial mast cell apoptosis induced by angiotensin Ⅱ （AngⅡ） and the mechanism of the correlation between apoptosis and mitochondrial autophagy. MethodsIn this experiment， AngⅡ and serum containing Zhenwutang with different concentrations were used to interfere with H9C2 cardiomyocytes for 24 h， and the survival rate of H9C2 cardiomyocytes was detected by cell counting kit-8 （CCK-8） to screen the optimal concentration for the experiment. Enzyme-linked immunosorbent assay （ELISA） was used to detect the content of B-type natriuretic peptide （BNP） in cell culture supernatant， and immunofluorescence was used to detect the cell surface area to verify the construction of the myocardial mast cell model. Subsequently， the experiment was divided into a blank group （20% blank serum）， a model group （20% blank serum + 5×10^-5 mol·L^-1 AngⅡ）， low-， medium-， and high-dose （5%， 10% and 20%） serum containing Zhenwutang groups， an autophagy inhibitor group （1×10^-4 mol·L^-1 3-MA）， and autophagy inducer group （1×10^-7 mol·L^-1 rapamycin）. The apoptosis level of H9C2 cells and the changes of mitochondrial membrane potential were detected by flow cytometry. The lysosomal probe （Lyso Tracker） and mitochondrial probe （Mito Tracker） co-localization was employed to detect autophagy. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect Caspase-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， Bcl-2-related X protein （Bax）， and cytochrome C （Cyt C） in apoptosis-related pathways and the relative mRNA expression of ubiquitin ligase （Parkin）， phosphatase and tensin homolog （PTEN）-induced kinase 1 （PINK1）， and p62 protein in mitochondrial autophagy-related pathways. Western blot was used to detect cleaved Caspase-3， cleaved Caspase-9， Bax， Bcl-2， and Cyt C in apoptosis-related pathways， phosphorylated ubiquitin ligase （p-Parkin）， phosphorylated PTEN-induced kinase 1 （p-PINK1）， p62， and Bcl-2 homology domain protein Beclin1 in mitochondrial autophagy-related pathways， and the change of microtubule-associated protein 1 light chain 3 （LC3） Ⅱ/Ⅰ ratio. ResultsCCK-8 showed that when the concentration of AngⅡ was 5×10^-5 mol·L^-1， the cell activity was the lowest， and there was no cytotoxicity. At this concentration， the surface area of cardiomyocytes was significantly increased （P<0.01）， and the content of BNP in the supernatant of culture medium was significantly increased （P<0.05）. Therefore， AngⅡ with a concentration of 5×10^-5 mol·L^-1 was selected for the subsequent modeling of myocardial mast cells. Compared with the blank group， the model group and the autophagy inhibitor 3-MA group had a significantly increased apoptosis rate （P<0.01） and significantly decreased mitochondrial membrane potential （P<0.01）. The results of immunofluorescence co-localization showed that compared with the blank group， the model group had a significantly decreased number of red and green fluorescence spots. The results of Real-time PCR showed that compared with that in the blank group， the relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 in the model group was significantly up-regulated （P<0.01）， while the relative mRNA expression of Bcl-2， Parkin， and PINK1 was significantly down-regulated （P<0.01）. In addition， the relative protein expression of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 was significantly up-regulated （P<0.01）. The LC3Ⅱ/Ⅰ was significantly decreased， and the relative protein expression of Bcl-2， p-Parkin， p-PINK1， and Beclin1 was significantly down-regulated （P<0.01）. Compared with the model group， the serum containing Zhenwutang groups and the autophagy inducer group had significantly decreased apoptosis rate （P<0.01）， and the decrease ratio of mitochondrial membrane potential is significantly lowered （P<0.01） in a dose-dependent manner. Additionally， both red and green fluorescence spots became more in these groups. In the 3-MA group， the number of red and green fluorescence spots decreased significantly. The relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 was significantly down-regulated （P<0.05， P<0.01）， while that of Bcl-2， Parkin， and PINK1 was significantly up-regulated （P<0.01）. In the serum containing Zhenwutang groups， the relative protein expression levels of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 were significantly down-regulated （P<0.05，P<0.01）. The LC3Ⅱ/Ⅰ was significantly increased， and the relative protein expression levels of Bcl-2， p-Parkin， p-PINK1， and Beclin1 were significantly up-regulated （P<0.01）. ConclusionThe serum containing Zhenwutang can reduce the apoptosis of myocardial mast cells and increase mitochondrial autophagy. This is related to the inhibition of intracellular Bax/Bcl-2/Caspase-3 apoptosis pathway and regulation of Parkin/PINK1 mitochondrial autophagy pathway.

Osteoporosis is a common senile bone metabolism disease， clinically characterized by decreased bone mass， destruction of bone microstructure， increased bone fragility， and easy fracture. It tends to occur in the elderly and postmenopausal women， seriously threatening the quality of life and physical and mental health of the elderly. At present， the treatment of osteoporosis is mainly based on oral western medicines， such as calcium， Vitamin D， and bisphosphonates. Still， there are drawbacks such as a long medication cycle and many adverse reactions. In recent years， due to the advantages of multi-component， multi-pathway， and multi-target， some traditional Chinese medicines and effective ingredients can regulate the osteogenic and osteoclastic differentiation process in both directions and are widely used in the prevention and treatment of osteoporosis. Hippophae rhamnoides is a commonly used herbal medicine， and its fruits are rich in flavonoids， polyphenols， fatty acids， vitamins， and trace elements， which have been proven to have a good anti-osteoporosis effect. Isorhamnetin is the main effective ingredient of Hippophae rhamnoides fruits， which has many pharmacological effects such as anti-inflammation， anti-oxidative stress， anti-aging， and anti-tumor. Studies have shown that isorhamnetin can participate in the regulation of bone metabolism and has a good anti-osteoporosis effect. However， the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis have not been systematically summarized. Therefore， this paper reviewed the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis by referring to relevant literature to provide more basis for the development and application of isorhamnetin.

Generative Artificial Intelligence ishows a broad application prospect in the field of healthcare and has become an important technical means to promote the development of medical informatization.It addresses the multi-faceted challenges of medical record documentation,including efficiency,quality,and doctor-patient communica-tion.It analyzes the adaptability and feasibility of Generative Artificial Intelligence in different clinical scenarios of intelli-gent medical record generation.Additionally,it explores the issues present in current applications and proposes corre-sponding solutions,providing references for the effective application and continuous optimization of Generative Artifi-cial Intelligence in medical record documentation.This provides a theoretical foundation for further expanding the appli-cation scenarios of automatic medical record documentation in China's healthcare industry.

With the accelerated progress of population aging and the shift in the disease spectrum, the prevention and management of chronic diseases and multimorbidity are facing great challenges. Multimorbidity measurement is a process that assesses and quantifies the complexity and severity of multiple disease states in a population, which is of great significance for understanding the epidemiology and disease burden of multimorbidity, as well as for optimizing medical services and policy. This article reviews existing multimorbidity measurement indicators, tools, and applications from two dimensions, static and dynamic attributes, aiming to improve the accuracy and comprehensiveness of multimorbidity epidemiology, diagnosis, and treatment.