ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

Objective: To investigate the mechanism of shed syndecan-4 (sSDC4) in temporomandibular joint osteoarthritis (TMJOA) in rats, aiming to provide experimental evidence for its prevention and treatment. Methods: This study was approved by the Institutional Animal Ethics Committee. Twelve 6-week-old female Sprague Dawley (SD) rats were randomly divided into two groups. They received a single intra-articular injection into the bilateral superior cavity of temporomandibular joint, which consisted of either 50 μL of 4 mg/mL monosodium iodoacetate (TMJOA model group) or 50 μL of phosphate-buffered saline (PBS, control group). After 4 weeks, the mandibular condylar cartilage was harvested for hematoxylin & eosin (H&E) staining, Safranin O-fast green (SO) staining, and type II collagen (Col-Ⅱ) immunohistochemical staining to assess the degree of cartilage degeneration. The synovium of the temporomandibular joint was collected for immunohistochemical staining to detect the expression levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) to evaluate the degree of synovial inflammation. Synovial fluid from the temporomandibular joint cavity was collected to measure sSDC4 levels by enzyme-linked immunosorbent assay (ELISA). In addition, 12 6-week-old female SD rats were randomly divided into a His-SDC4 group and a control group, receiving injections into the bilateral superior cavity of temporomandibular joint of either 100 ng/mL (50 μL) of His-SDC4 protein or 50 μL of PBS once every 3 days for a total of 28 days. The same experimental procedures were performed for H&E staining, SO staining, and immunohistochemical staining (Col-Ⅱ IL-6, TNF-α) to observe condylar cartilage degeneration and detect synovial inflammation. Rat synovial fibroblasts and condylar chondrocytes were cultured in vitro and randomly divided into a His-SDC4-stimulated (10 ng/mL) group and control group. Perform CCK-8 cytotoxicity assays and observe cellular morphology under optical microscopy, the mRNA expression levels of IL-6 and TNF-α were detected by real-time quantitative polymerase chain reaction (RT-qPCR), and the levels of IL-6 and TNF-α in cell culture supernatants were measured by ELISA. Results: Compared with the control group, the TMJOA group showed decreased condylar cartilage thickness, percentage of SO-positive area, and percentage of Col-Ⅱ-positive area (all P<0.001); an increased synovitis score (P<0.001) and increased percentages of IL-6- and TNF-α-positive cells in the synovium (all P<0.001); and a significant increase in sSDC4 levels in the synovial fluid (P=0.011). Following intra-articular injection of His-SDC4, condylar cartilage thickness, percentage of SO-positive area, and percentage of Col-Ⅱ-positive area all decreased (all P<0.001); the synovitis score increased (P=0.006), and the percentages of IL-6- and TNF-α-positive cells in the synovium increased (all P<0.001). In vitro experiments showed that His-SDC4 stimulation significantly upregulated the expression levels of IL-6 and TNF-α in both synovial fibroblasts and condylar chondrocytes (all P<0.01), and the levels of these two cytokines in the culture supernatants also significantly increased (all P<0.01). Conclusion During TMJOA progression, the level of sSDC4 in the synovial fluid is significantly elevated, which can directly stimulate synovial fibroblasts and condylar chondrocytes to secrete more pro-inflammatory cytokines, forming a vicious cycle that accelerates TMJOA progression.

Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

A method that integrates the features of image patches from corneal lesions and conjunctival congestion-like complications is proposed to address the limitations of manual keratitis diagnosis(i.e.,time-consuming,laborious,high subjectivity)and the generally low accuracy of automatic keratitis diagnosis based on original slit-lamp images.Specifically,samples are acquired from the corneal and conjunctival regions.A cost-sensitive convolutional neural network is then used to extract and concatenate the high-level features of these image patches.After dimensionality reduction through principal component analysis,the processed features are input into the fully connected layer for classification.Trained and evaluated on 6414 slit-lamp images collected from Ningbo Eye Hospital,the proposed method achieves accuracies of 97.8%,98.6%,and 97.0%for keratitis,normal cornea,and other abnormal corneas,respectively.This method effectively integrates relevant features and provides a feasible solution for high-accuracy keratitis diagnosis.

AIM To study the chemical constituents from the roots of Siraitia grosvenorii(Swingle)C.Jeffrey and their α-glucosidase inhibitory activities.METHODS The 95％ethanol extract was isolated and purified by silica gel,MCI,ODS and HSCCC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The α-glucosidase inhibitory activities were evaluated by PNPG method,after which molecular docking was performed.RESULTS Twenty-one compounds were isolated and identified as vanillin(1),siraitic acid B(2),cucurbitacin B(3),salicylic acid(4),ferulic acid(5),p-hydroxybenzaldehyde(6),(+)-lariciresinol(7),(+)-isolariciresinol(8),liballinol(9),3-(hydroxyacetyl)indole(10),2E-4-hydroxy-nonenoic acid(11),vomifolilol(12),vanillic acid(13),indole-3-carboxylic acid(14),ω-hydroxypropioguaiacone(15),p-hydroxybenzoic acid(16),p-coumaric acid(17),dehydrodipinocarpine(18),secoisolariciresinol(19),sesquimarocanol A(20),threo-guaiacylglycerol-β-O-4-lariciresinol ether(21).IC50 values of compounds 4,10,18 and 21 were(0.42±0.060)-(0.89±0.037)mg/mL.CONCLUSION Compounds 4,10-12,15,16,18,and 21 are isolated from the roots of this plant for the first time.Compounds 4,10,18,21 have α-glucosidase inhibitory activities,and 18 has the strongest activity.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective To identify the key determinants that enhance the scientific innovation capabilities of leading dis-ciplines in tertiary hospitals and to construct a predictive model for scientific research outputs,providing a scientific basis for the integrated development of hospital disciplines.Methods This study focused on the orthopedics,endocrinology and metabolism,otolaryngology head and neck surgery,and nephrology departments at the Shanghai Sixth People's Hospital affiliated with Shang-hai Jiao Tong University School of Medicine.Research data from 2013 to 2022 were analyzed.Significant independent variables were identified through univariate analysis,and the LASSO regression model was applied to address multicollinearity issues,in-corporating the time lag effect of research output to construct a predictive model.Results The number of senior professional title holders and the number of enrolled master's and doctoral students emerged as key factors for scientific research outputs.Factors affecting the quality and quantity of article output included the number of senior professionals,the enrollment of master's,doctor-al,and postdoctoral students,and funding for provincial,ministerial,school,bureau,and hospital-level projects.Key factors in-fluencing project-based outputs included the number of senior professionals,doctoral supervisors,the number of enrolled master' s and doctoral students,and funding for school and bureau-level projects.The prediction model based on LASSO regression dem-onstrated a good fit for various research output indicators.Conclusion This study used LASSO regression to identify key factors in scientific research outputs for top disciplines.The predictive model built in the study offers a scientific basis for discipline de-velopment.It helps optimize resource allocation,strengthen interdisciplinary collaboration,and drive high-quality hospital devel-opment.

Brucellosis,a zoonotic infectious disease caused by Brucella,leads to persistent infections in both animals and humans.This disease not only substantially affects the health and development of the livestock industry,but also poses a major threat to human health and public safety.Currently,vaccination remains the most effective method for preventing animal bru-cellosis.Compared with smooth strains,rough Brucella strains lack the O-chain antigens,thus offering advantages such as lower virulence,higher safety,and no interference with clinical diagnostics.Consequently,rough Brucella vaccines have prom-ising potential for brucellosis prevention and control.Researchers are now focusing on the development of Brucella abortus vac-cines as an important direction in brucellosis vaccine research and development.An urgent need exists for the development of Brucella abortus vaccines.This article provides a brief review of current research on vaccines for rough Brucella and candidate strains,and summarizes developed vaccine applications and their effectiveness,to provide insights for brucellosis prevention and control,and further development of vaccines for rough Brucella.