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 develop and compare multiple machine learning models for identifying high-risk college students exhibiting phubbing behavior and to determine key predictive factors, so as to provide evidence for precise screening and early intervention strategies. Methods: In December 2025, 1 828 undergraduate students, selected from three universities in Wuhan by using convenience sampling method, were surveyed via online qustionnaire for sociodemographic characteristics, phubbing behavior, family cohesion index, mature happiness, fear of negative evaluation, multidimensional state boredom, and psychological vulnerability. Four machine learning algorithms, including multilayer perceptron (MLP), extreme gradient booting (XGBoost), K-nearest neighbors (KNN), and gradient boosting decision tree (GBDT), were applied. The dataset was randomly split into a training set and a test set at a ratio of 7∶3. Model performance was evaluated using accuracy, recall, F1-score, and area under the receiver operating characteristic curve (AUC). The best performing model was further interpreted using shapley additive explanation (SHAP) analysis to assess feature importance. Results: In the training set,955 participants were classified as having low level phubbing behavior, and 325 participants were classified as having high level phubbing behavior. Significant differences were observed in psychological vulnerability, multidimensional state boredom, family cohesion index, and mature happiness between groups ( Z =-10.29, -11.72, -8.17, -7.83, all P <0.05). Significant differences were also found in the detection rate of high level phubbing behavior according to family residence, family status, left behind experience,interpersonal relationships,exercise frequency,physical flexibility,and sleep status ( χ 2=12.22, 38.93, 16.90, 44.64, 58.17, 82.14, 37.89, all P <0.05). Among the four machine learning models (MLP, KNN, GBDT, XGBoost),all showed good discrimination ability, with XGBoost performing best (accuracy 79%, recall 71%, F1-score=0.70, AUC=0.78), while GBDT achieved the highest precision (78%). Feature importance analysis showed that multidimensional state boredom was the most important predictor of phubbing behavior, followed by psychological vulnerability, family cohesion, mature happiness, and fear of negative evaluation. SHAP analysis indicated that multidimensional state boredom, psychological vulnerability, and fear of negative evaluation had positive risk effects, while family cohesion and hedonic well being had protective effects for high risk of phubbing behavior. Conclusions Multidimensional state boredom is the core predictor of phubbing behavior among college students. The XGBoost model demonstrates good predictive performance and can provide a reference for identifying high risk individuals and implementing targeted interventions.

ObjectiveTo investigate the effect of Shaoyaotang on T helper cell 17/regulatory T lymphocyte（Th17/Treg） cell balance in ulcerative colitis and decipher the intervention mechanism based on glucose metabolism reprogramming. MethodsThe mouse model of ulcerative colitis was established by the dextran sulfate sodium （DSS） method. Forty-eight C57BL/6 mice were randomly allocated into normal， model， Western drug control （mesalazine， 0.39 g·kg^-1·d^-1）， Shaoyaotang （15.54 g·kg^-1·d^-1）， inhibitor （2-deoxy-D-glucose， 2-DG， 100 mg·kg^-1·d^-1）， and inhibitor （2-DG， 100 mg·kg^-1·d^-1） + Shaoyaotang （15.54 g·kg^-1·d^-1） groups. Mice were administrated with the corresponding drugs by gavage for 7 days. The general conditions and the colon injury degree were observed 24 h after the last administration. The expression of interleukin （IL）-10 and IL-17 in the colon tissue was detected by immunohistochemical staining. Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） were performed to determine the protein and mRNA levels， respectively， of hypoxia-inducing factor-1α （HIF-1α）， lactate dehydrogenase （LDHA）， and hexokinase 2 （HK2） in the colon tissue. Th17/Treg cell differentiation was detected by flow cytometry. Enzyme-linked immunosorbent assay was employed to measure the levels of lactic acid and glucose in the colon tissue and IL-10， IL-17， and IL-6 in the serum. ResultsCompared with the normal group， the model group showed decreases in body weight and disease activity index （DAI） （P<0.05）， elevations in levels of HIF-1α， LDHA， HK2， IL-17， IL-6， Th17 cells， lactic acid， and glucose in the colon tissue （P<0.05）， and declines in the levels of of IL-10 and Treg cells （P<0.05）. Compared with the model group， the drug administration groups showed increases in body weight and DAI （P<0.05）， declines in levels of HIF-1α， LDHA， HK2， IL-17， IL-6， Th17 cells， lactic acid， and glucose in the colon tissue （P<0.05）， and rises in levels of IL-10 and Treg cells （P<0.05）. Shaoyaotang+2-DG group had the most obvious effect. ConclusionShaoyaotang can relieve diarrhea and bloody stool in mice with ulcerative colitis by restoring the Th17/Treg cell balance via regulation of glucose metabolism reprogramming， thus playing a role in the treatment of ulcerative colitis.

ObjectiveTo explore the regulation of Shaoyaotang on glucose metabolism reprogramming of macrophages and the mechanism of this decoction in inhibiting macrophage polarization toward the M1 phenotype. MethodsHuman monocytic leukemia-1 （THP-1） cells were treated with 100 ng·L^-1 phorbol myristate acetate for induction of macrophages as the normal control group. The cells treated with 100 ng·L^-1 lipopolysaccharide combined with 20 ng·L^-1 interferon （IFN）-γ for induction of M1-type macrophages were taken as the M1 model group. M1-type macrophages were treated with the blank serum， Shaoyaotang-containing serum， 0.5 mol·L^-1 2-deoxy-D-glucose （2-DG）， and Shaoyaotang-containing serum + 2-DG， respectively. After intervention， the expression of CD86 and CD206 was examined by flow cytometry. The levels of interleukin （IL）-6， tumor necrosis factor （TNF）-α， IL-10， and transforming growth factor （TGF）-β were assessed by ELISA. Real-time PCR and Western blot were employed to determine the mRNA and protein levels， respectively， of hypoxia-inducible factor-1 alpha （HIF-1α）， glucose transporter 1 （GLUT1）， hexokinase 2 （HK2）， glyceraldehyde-3-phosphate dehydrogenase （GAPDH）， and 6-phosphofructo-2-kinase/fructose-2，6-bisphosphatase 3 （PFKFB3）. ResultsCompared with that in the normal control group， the expression of CD86， the marker of M1-type macrophages， increased in the M1 model group and blank serum group （P<0.01）， which indicated that the M1 inflammatory model was established successfully. In addition， the M1 model group was observed with up-regulated mRNA and protein levels of proinflammatory cytokines IL-6 and TNF-α and glycolysis-related factors HIF-1α， GLUT1， HK2， GAPDH， and PFKFB3 （P<0.01）. Compared with the M1 model group， the Shaoyaotang-containing serum， 2-DG， and combined intervention groups showed decreased expression of CD86 （P<0.01）， down-regulated mRNA and protein levels of proinflammatory factors IL-6 and TNF-α and glycolysis-related factors HIF-1α， GLUT1， HK2， GAPDH， and PFKFB3 produced by M1-type macrophages （P<0.01）， increased expression of CD206 （marker of M2-type macrophages） （P<0.01）， and elevated levels of IL-10 and TGF-β produced by M2-type macrophages （P<0.01）. ConclusionShaoyaotang inhibits macrophage differentiation toward pro-inflammatory M1-type macrophages and promotes the differentiation toward anti-inflammatory M2-type macrophages by regulating glucose metabolism reprogramming. The evidence gives insights into new molecular mechanisms and targets for the treatment of ulcerative colitis with Shaoyaotang.

ObjectiveTo investigate the effect of Shaoyaotang on T helper cell 17/regulatory T lymphocyte（Th17/Treg） cell balance in ulcerative colitis and decipher the intervention mechanism based on glucose metabolism reprogramming. MethodsThe mouse model of ulcerative colitis was established by the dextran sulfate sodium （DSS） method. Forty-eight C57BL/6 mice were randomly allocated into normal， model， Western drug control （mesalazine， 0.39 g·kg^-1·d^-1）， Shaoyaotang （15.54 g·kg^-1·d^-1）， inhibitor （2-deoxy-D-glucose， 2-DG， 100 mg·kg^-1·d^-1）， and inhibitor （2-DG， 100 mg·kg^-1·d^-1） + Shaoyaotang （15.54 g·kg^-1·d^-1） groups. Mice were administrated with the corresponding drugs by gavage for 7 days. The general conditions and the colon injury degree were observed 24 h after the last administration. The expression of interleukin （IL）-10 and IL-17 in the colon tissue was detected by immunohistochemical staining. Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） were performed to determine the protein and mRNA levels， respectively， of hypoxia-inducing factor-1α （HIF-1α）， lactate dehydrogenase （LDHA）， and hexokinase 2 （HK2） in the colon tissue. Th17/Treg cell differentiation was detected by flow cytometry. Enzyme-linked immunosorbent assay was employed to measure the levels of lactic acid and glucose in the colon tissue and IL-10， IL-17， and IL-6 in the serum. ResultsCompared with the normal group， the model group showed decreases in body weight and disease activity index （DAI） （P<0.05）， elevations in levels of HIF-1α， LDHA， HK2， IL-17， IL-6， Th17 cells， lactic acid， and glucose in the colon tissue （P<0.05）， and declines in the levels of of IL-10 and Treg cells （P<0.05）. Compared with the model group， the drug administration groups showed increases in body weight and DAI （P<0.05）， declines in levels of HIF-1α， LDHA， HK2， IL-17， IL-6， Th17 cells， lactic acid， and glucose in the colon tissue （P<0.05）， and rises in levels of IL-10 and Treg cells （P<0.05）. Shaoyaotang+2-DG group had the most obvious effect. ConclusionShaoyaotang can relieve diarrhea and bloody stool in mice with ulcerative colitis by restoring the Th17/Treg cell balance via regulation of glucose metabolism reprogramming， thus playing a role in the treatment of ulcerative colitis.

ObjectiveTo explore the regulation of Shaoyaotang on glucose metabolism reprogramming of macrophages and the mechanism of this decoction in inhibiting macrophage polarization toward the M1 phenotype. MethodsHuman monocytic leukemia-1 （THP-1） cells were treated with 100 ng·L^-1 phorbol myristate acetate for induction of macrophages as the normal control group. The cells treated with 100 ng·L^-1 lipopolysaccharide combined with 20 ng·L^-1 interferon （IFN）-γ for induction of M1-type macrophages were taken as the M1 model group. M1-type macrophages were treated with the blank serum， Shaoyaotang-containing serum， 0.5 mol·L^-1 2-deoxy-D-glucose （2-DG）， and Shaoyaotang-containing serum + 2-DG， respectively. After intervention， the expression of CD86 and CD206 was examined by flow cytometry. The levels of interleukin （IL）-6， tumor necrosis factor （TNF）-α， IL-10， and transforming growth factor （TGF）-β were assessed by ELISA. Real-time PCR and Western blot were employed to determine the mRNA and protein levels， respectively， of hypoxia-inducible factor-1 alpha （HIF-1α）， glucose transporter 1 （GLUT1）， hexokinase 2 （HK2）， glyceraldehyde-3-phosphate dehydrogenase （GAPDH）， and 6-phosphofructo-2-kinase/fructose-2，6-bisphosphatase 3 （PFKFB3）. ResultsCompared with that in the normal control group， the expression of CD86， the marker of M1-type macrophages， increased in the M1 model group and blank serum group （P<0.01）， which indicated that the M1 inflammatory model was established successfully. In addition， the M1 model group was observed with up-regulated mRNA and protein levels of proinflammatory cytokines IL-6 and TNF-α and glycolysis-related factors HIF-1α， GLUT1， HK2， GAPDH， and PFKFB3 （P<0.01）. Compared with the M1 model group， the Shaoyaotang-containing serum， 2-DG， and combined intervention groups showed decreased expression of CD86 （P<0.01）， down-regulated mRNA and protein levels of proinflammatory factors IL-6 and TNF-α and glycolysis-related factors HIF-1α， GLUT1， HK2， GAPDH， and PFKFB3 produced by M1-type macrophages （P<0.01）， increased expression of CD206 （marker of M2-type macrophages） （P<0.01）， and elevated levels of IL-10 and TGF-β produced by M2-type macrophages （P<0.01）. ConclusionShaoyaotang inhibits macrophage differentiation toward pro-inflammatory M1-type macrophages and promotes the differentiation toward anti-inflammatory M2-type macrophages by regulating glucose metabolism reprogramming. The evidence gives insights into new molecular mechanisms and targets for the treatment of ulcerative colitis with Shaoyaotang.

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

OBJECTIVES: To investigate the association between insulin resistance and uterine volume in girls with idiopathic central precocious puberty (ICPP). METHODS: A retrospective study was conducted involving 61 girls diagnosed with ICPP who visited the pediatric growth and development clinic of the Third Affiliated Hospital of Zhengzhou University between January 2022 and September 2024, designated as the ICPP group, and 61 normally developing girls as the control group. The differences in insulin resistance index (homeostasis model assessment of insulin resistance, HOMA-IR), uterine volume, and other indicators between the two groups were compared, and the relationship between insulin resistance and uterine volume in these girls was analyzed. RESULTS: The uterine volume and HOMA-IR level in the ICPP group were significantly higher than those in the control group (P<0.05). Correlation analysis revealed that there was a positive correlation between HOMA-IR level and uterine volume in the ICPP group (r_s=0.643, P<0.001). Multiple linear regression analysis indicated that as HOMA-IR increased,uterine volume in the girls tended to increase (P<0.05). CONCLUSIONS There is an association between insulin resistance and uterine volume in girls with ICPP, and as HOMA-IR increases, uterine volume in the girls also increases.
Humans ; Female ; Insulin Resistance ; Puberty, Precocious/metabolism* ; Uterus/pathology* ; Child ; Retrospective Studies ; Organ Size ; Linear Models

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.