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.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

Objective This study investigated the diversity of rodent populations and the infection status of Bartonella at three ports along the China-Mongolia border in 2022. Methods Rodents at three Belt and Road ports along the China-Mongolia border, namely Ganqimaodu, Erenhot, and Zhuengadabuqi, were morphologically identified. The Bartonella citrate synthase(gltA)gene was amplified by nested polymerase chain reaction(PCR), and PCR-positive products were sequenced. The resulting sequences were then analyzed for genetic characteristics. Phylogenetic analysis was performed using MEGA 11.0 software using Neighbor-Joining and Maximum-Likelihood method. Results A total of 94 rodents were captured, representing seven species from five families and six genera: Mus musculus, Meriones unguiculatus, Meriones meridianus, Spermophilus dauricus, Allactaga sibirica, Dipus sagitta, and Phodopus roborovskii. Among them, M. unguiculatus was the most abundant species, with 58 rodents, accounting for 61.70% of the total. Overall,11 positive Bartonella pathogen sequences were obtained from the three ports, with a positive detection rate of 11.70%(11/94). The infected rodent species included M. unguiculatus, M. meridianus, and A. sibirica, and two species of Bartonella were detected. Conclusions Rodents at Ganqimaodu, Erenhot, and Zhuengadabuqi ports along the China-Mongolia border were naturally infected with Bartonella. Rodent monitoring and pathogen prevention and control in this area should be strengthened.

ObjectiveTo investigate the potential therapeutic effects of Dengzhan Shengmai capsules （DZSM） on myocardial fibrosis after myocardial infarction and decipher the underlying molecular mechanisms by virtue of network robustness algorithm. MethodsA rat model of myocardial infarction was established by ligating the left anterior descending coronary artery. Successfully modeled Sprague-Dawley rats were randomly allocated into a model group， an enalapril group（3.15 mg·kg^-1）， and high- and low-dose DZSM groups（226.8，113.4 mg·kg^-1）. In addition， a sham group was set up. After four consecutive weeks of intervention， the cardiac function was assessed via echocardiography， and myocardial collagen deposition was observed through Sirius red staining. The key regulatory pathways of DZSM were analyzed by the network robustness algorithm. Enzyme-linked immunosorbent assay （ELISA） and immunofluorescence assay were employed to validate the mechanisms. ResultsCompared with the sham group， the model group exhibited decreased left ventricular ejection fraction （LVEF%） and fractional shortening （FS%） （P<0.01） and increased myocardial collagen volume fraction （CVF%） （P<0.01）. Compared with the model group， high-dose DZSM and enalapril improved LVEF% and FS% （P<0.01）. Both high- and low-dose DZSM reduced the CVF% （P<0.05， P<0.05，）. Network analysis indicated that DZSM exerted its effects by regulating neutrophil infiltration and related inflammatory pathways. Experimental validation showed that DZSM significantly reduced the protein levels of nuclear factor （NF）-κB， Janus kinase 2 （JAK2）， and signal transduction activator and transducer 3 （STAT3） in the cardiac tissue， as well as the levels of chemokine （C-X-C motif） ligand 1 （CXCL1）， interleukin （IL）-1β， neutrophil elastase-DNA complex （NE-DNA）， and myeloperoxidase-DNA complex （MPO-DNA） in the plasma. ConclusionDZSM may ameliorate myocardial fibrosis by inhibiting neutrophil infiltration and extracellular trap formation and regulating the NF-κB/JAK2/STAT3 signaling pathway.

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

Objective:To analyze the associated factors and cumulative effects of cardiometabolic multimorbidity (CMM) among residents in southern Xinjiang.Methods:A stratified random cluster sampling method was used to conduct questionnaire surveys, physical examinations and laboratory tests among the personnel of the 51st Brigade, 3rd Division, Xinjiang, in 2016. The multivariate logistic regression, multivariate linear regression, restricted cubic spline, and network analysis methods were used to study the association of lifestyle (smoking, alcohol consumption and physical activity), socioeconomic (occupation, education and marital status) and clinical factors (waist circumference, body mass index and family history) with CMM.Results:A total of 12 773 study subjects were included. The prevalence of cardiovascular metabolic diseases among residents in southern Xinjiang was 52.49%. Specifically, the prevalence rates of dyslipidemia, hypertension, coronary heart disease, diabetes, and stroke were 31.14%, 29.95%, 6.78%, 6.26%, and 2.47%, respectively, and the prevalence of CMM was 19.06%. Multivariate logistic regression analysis revealed that the associations between clinical and socioeconomic factors and CMM significantly increased with higher scores. Specifically, the OR rose from 1.75 (clinical factors) and 1.07 (socioeconomic factors) on a score of 1 to 4.41 and 1.93 on a score of 3, respectively. The association between lifestyle factors and CMM was only observed at higher scores ( OR=1.26, 95% CI:1.07~1.62). The trend test using the scores of each group as continuous variables in the model showed that the risk of disease increased with the accumulation of clinical, socioeconomic and lifestyle factors (all P<0.05). Restricted cubic spline analysis demonstrated a non-linear relationship between the total number of associated factors and CMM ( Poverall<0.05 and Pnon-linear<0.05). Network analysis identified hypertension (strength=0.42) as the “core node” among the five diseases. When analyzing the three types of influencing factors, hypertension (strength=0.68), dyslipidemia (strength=0.47), coronary heart disease (strength=0.37), and clinical factors (strength=0.53) emerged as “core nodes”. In the network of nine associated factors, abnormal waist circumference and BMI (strength=0.90 and 0.84) were identified as “key factors”, while hypertension (strength=0.68) and dyslipidemia (strength=0.52) were identified as “key diseases”. Conclusion:The prevalence of CMM among residents in southern Xinjiang is high, and there is a cumulative effect of multiple factors. Hypertension and dyslipidemia are key diseases in the multimorbidity network, while abnormal BMI and waist circumference are key associated factors.

Objective:To investigate the differences in clinical and imaging characteristics of patients with recent small subcortical infarct (RSSI) stratified by different etiological subtypes.Methods:A retrospective, consecutive analysis was conducted on 696 RSSI patients admitted to the West China Hospital, Sichuan University, from January 2019 to May 2024. Based on clinical and imaging data, patients were stratified into 3 etiological subgroups: presumed cerebral small vessel disease (CSVD)-related RSSI, coexisting carrier large artery stenosis, and coexisting proximal extracranial/intracranial large artery stenosis. The clinical characteristics, vascular risk factors, infarct imaging features, and CSVD markers were compared across the 3 groups. Additionally, the differences in clinical and imaging features based on the location of infarcts (anterior vs posterior circulation) and infarct size (<15 mm vs ≥15 mm) were examined. Results:Among the 696 patients, 557 (80.0%) had presumed CSVD-related RSSI, 68 (9.8%) had coexisting carrier large artery stenosis, and 71 (10.2%) had coexisting proximal extracranial/intracranial large artery stenosis. The patients with presumed CSVD-related RSSI were the youngest [60 (53, 69) years], followed by those with coexisting carrier large artery stenosis [64 (55, 69) years] and those with coexisting proximal extracranial/intracranial large artery stenosis [69 (55, 75) years; H=9.523, P=0.013]. Among RSSI patients with coexisting proximal extracranial/intracranial large artery stenosis, the proportion of those with diabetes (38/71, 53.5%) was the highest, whereas the proportion was 210/557 (37.7%) in the presumed CSVD-related group and 31/68 (45.6%) in the group with coexisting carrier large artery stenosis (χ 2=8.027, P=0.023). Patients with RSSI combined with proximal extracranial/intracranial large artery stenosis had more infarction sites in the pons and a higher proportion of proximal infarction. However, there were no significant differences among the 3 groups in terms of infarct size, or CSVD imaging markers. In the anterior versus posterior circulation comparison, patients with posterior circulation RSSI ( n=360) had a significantly higher age of onset [63(55, 72) years vs 60(52, 59) years, U=51 335.500, P<0.001], had higher prevalence of hypertension and diabetes, and showed higher NIHSS scores [3(2, 6) vs 3(1, 5), U=57 840.500, P=0.028]. The anterior circulation group ( n=366) showed a higher proportion of lacunas [152/336 (45.2%) vs 118/360 (32.8%), χ2=11.364, P<0.001], while the posterior circulation group had a greater prevalence of severe perivascular spaces in the basal ganglia [254/360 (70.6%) vs 203/336 (60.4%), χ2=7.879, P=0.005] and deep white matter hyperintensities grading≥2 [124/360 (34.4%) vs 90/336 (26.8%), χ2=4.787, P=0.029]. There were no statistically significant differences in the distribution of infarcts between anterior and posterior circulations or in CSVD imaging markers between RSSI patients with infarction lesions ≥15 mm ( n=290) and <15 mm ( n=406). Conclusions:Approximately 20% of RSSI cases are related to large artery stenosis. These patients tend to be older at onset and have a higher prevalence of diabetes. Compared to presumed CSVD-related RSSI cases, RSSI cases related to large artery stenosis show no significant differences in infarct imaging features and CSVD imaging markers, suggesting that large artery stenosis in RSSI may be an epiphenomenon rather than a direct causative factor.

Objective To evaluate the efficacy and safety of high-power,short-duration radiofrequency catheter ablation for the treatment of persistent atrial fibrillation.Methods This retrospective study included 392 patients diagnosed with persistent atrial fibrillation who underwent catheter radiofrequency ablation at Suzhou Kowloon Hospital,Shanghai Jiao Tong University School of Medicine,from January 2019 to December 2023.Of these,256 patients were treated with high-power,short-duration ablation,and 136 patients with low-power,long-duration ablation.The following parameters were compared:radiofrequency ablation time,total procedure time,single-circle pulmonary vein isolation rate,immediate procedural success rate,number of ablation points,and perioperative complications(including pericardial tamponade,pseudoaneurysm,arteriovenous fistula,stroke,etc.).Follow-up assessments were conducted at 3,6,and 12 months post-surgery to evaluate the 12-month sinus rhythm maintenance rate.Results The ablation time in the high-power group was significantly shorter than that in the low-power group[(14.6±2.3)min vs.(30.3±4.2)min,P＜0.001],as was the total procedure time[(113.8±24.8)min vs.(128.5±26.7)min,P=0.001].There were no significant differences between the two groups in terms of pulmonary vein isolation rate(97.7％vs.94.9％,P=0.823),number of ablation points[(71.2±8.0)vs.(74.3±14.3),P=0.168],or perioperative complications(3.1％vs.4.4％,P=0.571).Regarding the maintenance rate of sinus rhythm at 12 months post-operation,the high-power group showed a higher rate than the low-power group,but no statistically significant difference was observed(82.8％vs.79.4％,P=0.399).Conclusions High-power,short-duration radiofrequency catheter ablation can improve procedural efficiency in the treatment of persistent atrial fibrillation.Its efficacy and safety are similar to those of the low-power,long-duration technique.

Objective To investigate the changes of brain deep gray matter nucleus volume and iron content in patients with type 2 dia-betes mellitus(T2DM)based on quantitative MR technology,and their correlation and mediating effect with cognitive impairment.Methods A total of 60 T2DM patients(T2DM group)and 61 healthy controls(HC)(HC group)were prospectively selected.The volume of brain deep gray matter nucleus of 3D-T1 sequence map was measured by artificial intelligence(AI)automatic segmentation technique,the corresponding region of interest(ROI)was manually drawn and quantitative susceptibility mapping(QSM)value was measured on QSM,the cognitive score,QSM value and volume of nucleus were compared by independent sample t test and rank sum test,and the correlation analysis of imaging indexes with differences between the two groups was made.The mediating effect between fasting blood glucose(FBG)and Montreal cognitive assessment(MoCA)score was analyzed.Results The MoCA and mini-mental state examination(MMSE)scores in the T2DM group were lower than those in the HC group(P＜0.05),the volumes of bilateral caudate nucleus,putamen,globus pallidus,thalamus,and right hippocampus in the T2DM group were lower than those in the HC group(P＜0.05),and the QSM values of left caudate nucleus,thalamus and bilateral globus pallidus in the T2DM group were higher than those in the HC group(P＜0.05).In the T2DM group,the volumes of bilateral thalamus and right hippocampus were positively correlated with MoCA score(left thalamus:r=0.326,P=0.012;right thalamus:r=0.373,P=0.004;right hippocampus:r=0.509,P＜0.001),and the QSM value of left thalamus was negatively correlated with MoCA score(r=-0.263,P=0.044).The mediating effect of right hippocampus volume and left thalamus QSM value was significant(P＜0.05),and the direct effect of FBG on cog-nitive score was significant(P＜0.05).Conclusion Brain deep gray matter nucleus atrophy and brain iron deposition are closely related to T2DM and cognitive impairment,and there is a mediating effect.Brain iron deposition will increase the risk of cognitive impairment in T2DM.