Objective: To investigate the association of special family structure and physical activity with psychological sub health among secondary vocational school students, so as to provide reference to inform mental health promotion in the population. Methods: From September to December 2024, a convenience sample was drawn from 16 schools including 5 141 secondary vocational school students across 8 provinces (municipalities) in China (Fujian, Chongqing, Guangdong, Guangxi, Hubei, Jiangxi, Shanghai, Zhejiang). A self developed questionnaire, Multidimensional Sub health Questionnaire of Adolescents and International Physical Activity Questionnaire Short Form were used to investigate and evaluate basic information, family structure, psychological sub health status and physical activity. Descriptive statistics and Logistic regression analysis were performed to explore relationships of special family structures and physical activity with psychological sub health in secondary vocational school students. Results: The detection rate of psychological sub health among secondary vocational school students was 11.0%. The reporting rates for secondary vocational school students who lost their father or lost their mother, whose parents divorced, whose parents remarried, and those from special family structures were 2.8%, 0.8%, 11.8%, 3.9%, and 14.7%, respectively. Moreover, the detection rates of psychological sub health and its sub dimensions significantly differed among secondary vocational school students grouped by family type (divorced parental families, remarried parental families and special family structures)( χ 2=5.90-22.67, all P <0.05). Binary Logistic regression indicated that maternal bereavement was associated with a higher risk of conduct problems [ AOR ( 95% CI )= 2.90(1.15-7.33)], and parental divorce was associated with a higher risk of psychological sub health ( AOR= 2.71 , 95%CI =1.04- 7.06 ) among secondary vocational school students (both P <0.05). Interaction analysis showed that both students with a special family structure and insufficient physical activity [ AOR (95% CI )=1.99(1.44-2.75)] and those with a non-special family structure and insufficient physical activity [ AOR (95% CI )=1.81(1.48-2.22)] were associated with increased risks of psychological sub health among secondary vocational school students (both P <0.01). Conclusion Special family structure and physical activity are associated with psychological sub health among secondary vocational school students; early identification and assessment based interventions for those with a special family structure should be strengthened, while school based physical activity should be implemented to increase physical activity levels,thereby reducing the risk of psychological sub health.

Objective To explore factors associated with early postoperative hormonal remission in patients with prolactinoma and to develop prediction models based on clinical and radiological features. Methods Data from 107 patients with prolactinoma who underwent transsphenoidal surgery at The First People’s Hospital of Huai’an, Nanjing Medical University between January 2020 and December 2024 was collected, included general clinical characteristics, preoperative laboratory indicators, and imaging features. Based on whether early postoperative prolactin (PRL) levels normalized, patients were divided into a remission group (n=76) and a non-remission group (n=31). Univariate logistic regression was used for preliminary evaluation of candidate variables, followed by LASSO regression for feature selection. Multiple machine learning models were constructed, including logistic regression, random forest, support vector machine, K-nearest neighbors, naive Bayes, decision tree, neural network, and gradient boosting decision tree (GBDT). All models were trained and evaluated using ten-fold cross-validation, with comprehensive assessment of model performance based on the area under the ROC curve (AUC), accuracy, sensitivity, specificity, precision, and F1 score. Results The maximum diameter of tumors in the non remission group was larger than that in the remission group (P=0.019), and the incidence of tumor stroke and preoperative PRL levels were significantly higher than those in the remission group (P＜0.001). Univariate analysis showed that sex, maximum tumor diameter, tumor stroke, and preoperative PRL levels were influencing factors for early postoperative hormone response in patients with prolactinoma (P＜0.05). The comparison results of machine learning models show that the neural network model performs the best (AUC=0.921) and has good clinical application value, followed by the GBDT model (AUC=0.893) and the support vector machine model (AUC=0.884). Other models also show certain predictive ability. Conclusions Sex, preoperative PRL levels, maximum tumor diameter, Hounsfield unit value, and tumor stroke are important factors affecting early hormone response after prolactinoma surgery. The machine learning model constructed based on the above variables has good predictive performance, and performs the best and has good clinical application value.

Objective To investigate the cross-sectional associations between different fatty liver classifications and cardiac structure and function in people undergo health examination. Methods A total of 6 545 adults who underwent health examinations at the Health Management Center of Zhongshan Hospital, Fudan University between January 1 and December 31, 2017, were retrospectively included. Demographic characteristics and laboratory data were collected. The hepatic steatosis was graded by ultrasonography. And patients with fatty liver were further stratified according to alanine aminotransferase (ALT) or aspartate aminotransferase (AST) levels, as well as the degree of liver fibrosis. Cardiac morphology and function were assessed by transthoracic echocardiography, and left ventricular geometric patterns were classified accordingly. Multivariate logistic regression analysis was performed to evaluate the associations between fatty liver classifications and cardiac abnormalities. Results There were 2 795 patients (42.7%) with fatty liver, of whom 832 (29.8%) had significant cardiac structural alterations and 1 500 (53.7%) had diastolic dysfunction. Severe fatty liver was risk factor for concentric remodeling and increased relative wall thickness (RWT), with odds ratios (ORs) of 1.27 (P＝0.012) and 1.27 (P＝0.009), respectively. Fatty liver accompanied by elevated ALT or AST was risk factor for concentric remodeling (OR＝1.45,1.56; P＝0.001, 0.001), increased RWT (OR＝1.48,1.57; P＜0.001, ＜0.001), and diastolic dysfunction (OR＝1.27, 1.32; P＝0.035, 0.040), respectively. Fatty liver with liver fibrosis was risk factor for concentric remodeling (OR＝1.83, P＝0.046) and diastolic dysfunction (OR＝2.64, P＝0.034). Conclusions Advanced fatty liver, including severe hepatic steatosis, accompanied by elevated liver enzymes or liver fibrosis, could increase risks of cardiac remodeling and diastolic dysfunction, while systolic function is preserved. For patients with fatty liver, it is recommended to undergo regular ultrasonography examination.

ObjectiveThis paper aims to observe the syndrome improvement and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome）. MethodsThrough a multi-center randomized controlled methodology design，confirmed influenza cases were collected from October 2022 to April 2023 in the pediatrics department of eight hospitals，such as Dongfang Hospital of Beijing University of Chinese Medicine. A total of 180 children with influenza and heat accumulation in the lung and stomach syndrome conforming to the standard were recruited through the clinic. The sick children meeting the inclusion criteria were randomly divided into groups by a block-randomized method. The children in the experimental group were treated with Qingxuan Daozhi formula for five days，and those in the control group were treated with Oseltamivir Phosphate Granules for five days. The primary efficacy indicator was the negative conversion rate of influenza antigen detection. Secondary efficacy indicators were the Canadian acute respiratory illness and flu scale （CARIFS） and the incidence of complications，severe cases， and critical cases. Follow-up observation was conducted on the day of enrollment，48 hours after medication，72 hours after medication， and （6+1） d after medication. ResultsOne hundred and eighty participants were randomly assigned to the experimental group （90 cases） or the control group （90 cases）. All participants were followed up during the study. Comparison of influenza antigen detection results in the primary efficacy indicators showed that the average time of negative influenza antigen conversion in the experimental group was （5.29±1.25） d，and that in the control group was （5.40±1.68） d，without a statistically significant difference. After five days of intervention，52 cases in the experimental group and 51 cases in the control group converted to negative，without a statistically significant difference. CARIFS score results in the secondary efficacy indicators showed that during 72 hours after intervention，there were statistically significant differences between the experimental group and the control group in three dimensions， including headache，muscle soreness， and the need for extra care （P<0.05）. On the （6+1） days after the intervention，the differences in both the experimental group and the control group were statistically significant in 10 dimensions， including sore throat，bad sleep，uncomfortable feeling，poor spirit and fatigue，crying more than usual，the need for extra care，symptom，function，influence on parents，and total score （P<0.05）. The comparison results within the group in the dimensional scores of symptom， function， and influence on parents，as well as the CARIFS total score showed that with the delay of follow-up time，scores of both groups decreased significantly，with a statistically significant difference （P<0.01）. Inter-group comparison results showed that the mean score of the experimental group was higher than that of the control group at the time of enrollment. With the progress of intervention，the score of the experimental group was significantly decreased compared with that of the control group. At the end of follow-up，the mean score of the experimental group was lower than that of the control group，with no statistically significant difference. In terms of the incidence of complications，severe cases， and critical cases， there were no complications，severe cases， and critical cases in the two groups，without a statistically significant difference. ConclusionThe symptom improvement effect and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome） are not inferior to Oseltamivir Phosphate granules， and children's acceptance is better. It can be more widely used in clinical treatment of influenza in children （heat accumulation in the lung and stomach syndrome）.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

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.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

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.