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.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To investigate the diagnostic value of our regression model based on quantitative parameters of dual-energy CT and clinical features for stages T2 and T3 colorectal cancer.Methods A cross-section study was performed on 91 patients with colorectal cancer confirmed by postoperative pathology in our hospital from January 2022 to November 2023.All of them underwent dual-energy CT examination.According to the pathological T staging criteria of Chinese Colorectal Cancer Diagnosis and Treatment Standard(2020 Edition),they were divided into T2 group(n=43)and T3 group(n=48).Univariate analysis was used to compare the differences in quantitative CT parameters and clinical features between the 2 groups,and the obtained significant variables were employed to construct diagnosis models by univariate or multivariate logistic regression analysis.The area under receiver operating characteristic curve(AUC)of the CT parametric model and the model combined with clinical features was compared to evaluate the efficacy of diagnosing T2 and T3 stages.Results Univariate analysis showed that carcinoembryonic antigen(CEA),N stage,tumor location,tumor longest diameter(LD),CT value of virtual noncontrast(CT-VNC),fat fraction,electron density(Rho)and dual energy index(DEI)were significantly different between the T2 and T3 groups(P＜0.05).Multivariate logistic regression analysis found that N stage,tumor location,LD,fat fraction and DEI were independent risk factors for the diagnosis of stage T3.The AUC value of the model of above CT parameters in diagnosing stage T3 colorectal cancer was 0.671(95％CI:0.558～0.783),and the AUC value of the combined model of above CT parameters and clinical features was 0.886(95％CI:0.815～0.957),and statistical difference was observed in the AUC value between the combined model and the CT parametric model(P＜0.01).Conclusion The regression model constructed with dual-energy CT quantitative parameters combined with clinical features has high value in the preoperative diagnosis of stages T2 and T3 colorectal cancer before surgery.

Objective:To evaluate the impact of roxadustat on thyroid function and to identify the associated factors in patients undergoing maintenance peritoneal dialysis (PD).Methods:This study was a single-center retrospective study. PD patients who received roxadustat or recombinant human erythropoietin (rHuEPO) treatment at Nanjing Drum Tower Hospital between January 2020 and June 2024 were included. The general and clinical information as well as laboratory indexes were collected. Serum free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH) were compared before and after treatment initiation. Hemoglobin (Hb) responses were also observed between the two groups. Logistic regression analysis was performed to explore the factors associated with thyroid function changes.Results:A total of 120 patients were enrolled, with an age of (55.17±16.42) years, including 66 males (55.0%). There were 81 patients received roxadustat (roxadustat group) and 39 patiens received rHuEPO (rHuEPO group). Compared to the rHuEPO group, the roxadustat group had a higher proportion of patients with diabetes ( χ 2= 4.172, P=0.041), a shorter PD vintage ( Z=-3.406, P=0.002), a lower serum level of total cholesterol ( Z=-2.082, P=0.037) and a lower level of fasting blood glucose ( Z=-2.589, P=0.010). Following treatment with roxadustat, the levels of FT4 ( Z=-5.349, P<0.01) and TSH ( Z=-3.720, P<0.01) decreased significantly. In contrast, no significant changes in FT4 or TSH levels were observed in the rHuEPO group (both P>0.05). For both roxadustat and rHuEPO groups, there were no significant changes in FT3 levels after treatment (both P>0.05). Multivariate analysis identified that higher baseline TSH (TSH≥2.27 μIU/ml, OR=1.581, 95% CI 1.196-2.089, P=0.001) and roxadustat exposure ( OR=3.432, 95% CI 1.410-8.355, P=0.007) as independent associated factors of subsequent TSH decline, and identified that higher baseline FT4 (FT4≥14.9 pmol/L, OR=1.390, 95% CI 1.162-1.662, P=0.001) and roxadustat exposure ( OR=5.798, 95% CI 2.225-15.113, P=0.001) as independent associated factors of subsequent FT4 decline. The degrees of hemoglobin changes after roxadustat or rHuEPO treatment did not differ significantly between roxadustat group and rHuEPO group ( t=-1.062, P=0.290). Of the 31 patients who underwent a second thyroid function test during roxadustat treatment, 24 continued with the original regimen, while 7 discontinued roxadustat. Among 24 patients who maintained roxadustat treatment, TSH ( Z=-0.400, P=0.689) and FT4 ( t=0.143, P=0.888) remained stable between the second and third tests. All 7 patients who discontinued roxadustat treatment showed TSH rebound and the changes of TSH levels were more significant than that in continuers ( Z=-2.505, P=0.012). FT4 recovery occurred in only 3 of them, with no significant difference in FT4 change between discontinuers and continuers ( Z=-0.685, P=0.493). Conclusions:Roxadustat commonly suppresses TSH and FT4, but not FT3, in PD patients. Baseline levels of TSH and FT4 are key associated factors of the inhibitory effect of roxadustat on thyroid function. This suppression does not intensify with prolonged exposure and is reversible after discontinuation, with TSH levels normalizing more quickly than FT4. Roxadustat-induced thyroid suppression does not compromise its efficacy in treating renal anemia.

Objective:To establish a rapid and precise dose measurement method with EBT4 film and ensure its measurement accuracy to be within the required range through strict operational procedures for the purpose of addressing the two essential issues of poor measurement accuracy and timeliness of EBT film under FLASH conditions.Methods:After storing under different humidity conditions for a certain period of time, the film was exposed to radiation for analyzing the influence of air humidity on the intrinsic performance of EBT film. By means of repeated scanning operations and the film angle rotation, the influences of repeated scanning and film placement angle were analuzed. Parabolic correction method was used to reduce the spatial position influence during the scanning process. By analying the relationship between net optical density (netOD) and absorbed dose through the comparison of three fitting method, the optimal fitting curve was selected. After irradiation of the same batch of films for 5 min and 24 h, the film doses were calibrated and then compared with ionization chamber-measured result. The rapid and precise film dosimetry method was used to measure both the percentage depth dose from X-rays at ultra-high dose rate and the dose distribution at a depth of 2 cm in water.Results:Air humidity had the greatest influence on the intrinsic performance of EBT film (approximately 20%). The average deviation of repeated scans is within 0.5%. The angle at which the film is placed significantly affected the readouts of the film with the maximum influence approximately 70%. The net optical density combined with polynomial fitting can control the fitting residuals of 1-16 Gy within 3%. The change rate of light channels at 5 min already mostly met the requirements of the rapid mode (< 0.5%). Compared with the measurement result obtained using the reference ionization chamber, the deviations of the 5 min or 24 h dose calibration curves were all within 2%.Conclusions:The EBT4 film can be employed as a precise dosimeter to quickly measure the FLASH radiation dose. Rapid and precise FLASH dose measurements can meet the stringent requirements of both preclinical and clinical FLASH research.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.