ObjectiveTo investigate the mechanism by which the Zishen Huoxue prescription （ZSHXP） ameliorates cognitive dysfunction in rats with vascular dementia （VD） induced by the bilateral common carotid artery ligation （2-VO model rats） through regulating the glucose-regulated protein 78 （GRP78）/protein kinase R-like endoplasmic reticulum kinase （PERK）/activating transcription factor 4 （ATF4） signaling pathway. MethodsA VD rat model was established via the 2-VO method. A total of 72 male Sprague-Dawley （SD） rats were randomly divided into six groups： Sham group， Model group， donepezil hydrochloride group （0.45 mg·kg^-1）， and ZSHXP groups at low （8.90 g·kg^-1）， medium （17.80 g·kg^-1）， and high （35.60 g·kg^-1） doses，with 12 rats in each group. The Morris Water Maze test was utilized to assess spatial learning and memory abilities of rats， and the Novel Object Recognition test was used to evaluate cognitive performance. Hematoxylin-eosin （HE） and Nissl staining were applied to observe the histological and morphological changes in hippocampal tissues. Transmission electron microscopy （TEM） was used to observe the morphological changes of endoplasmic reticulum in rat hippocampal neurons. Immunofluorescence staining was adopted to detect the colocalization of neuronal nuclei antigen （NeuN） with GRP78 and βⅢ Tubulin with gasdermin D （GSDMD） in hippocampal neurons. Western blot was used to detect the expression levels of endoplasmic reticulum stress （ERS）-related proteins including GRP78， PERK， ATF4， phosphorylated protein kinase R-like endoplasmic reticulum kinase （p-PERK）， C/EBP homologous protein （CHOP）， NOD-like receptor protein 3 （NLRP3）， Caspase-1 and GSDMD. ResultsCompared with the sham operation group， the model group showed a significantly prolonged escape latency （P<0.01）， a significant decrease in the number of platform crossings and the residence time in the target quadrant （P<0.01）， and a markedly reduced recognition index （P<0.01）. Histological observations revealed that the hippocampal neurons in the model group were disorderly arranged with reduced quantity， deformed and shrunken cell bodies， and pyknotic and hyperchromatic nuclei. The number of Nissl bodies decreased significantly. The number of endoplasmic reticula reduced obviously， accompanied by abnormal dilation and swelling， and the loss of normal folding structure. The fluorescence colocalization of NeuN with GRP78 and βⅢ Tubulin with GSDMD in the hippocampus was significantly increased in the model group. The protein expression levels of GRP78， p-PERK/PERK， ATF4， CHOP， NLRP3， GSDMD and Caspase-1 in the model group were significantly elevated （P<0.01）. Compared with the model group， the donepezil hydrochloride group and the ZSHXP medium- and high-dose groups had a significantly shortened escape latency （P<0.01） and an increased number of platform crossings （P<0.05， P<0.01）. The residence time in the target quadrant was increased in the donepezil hydrochloride group and all ZSHXP groups （P<0.05， P<0.01）， with a significantly improved recognition index （P<0.01）. In the donepezil hydrochloride group and all ZSHXP groups， the number of hippocampal neurons increased with a more compact arrangement and reduced nuclear hyperchromasia. The number of Nissl bodies increased with morphological structures tending to be normal. In the ZSHXP high-dose group， the number of endoplasmic reticula increased and the folding structure was restored. The fluorescence colocalization of NeuN with GRP78 and βⅢ Tubulin with GSDMD in the hippocampus was significantly weakened in the treatment groups. In the donepezil hydrochloride group， the protein expressions of GRP78， ATF4 and CHOP were increased （P<0.01）， while the expression of p-PERK/PERK was decreased （P<0.05）. In the ZSHXP low-dose group， the expressions of GRP78， p-PERK/PERK and CHOP were elevated （P<0.05， P<0.01）. The ZSHXP medium- and high-dose groups showed a significant decrease in the protein expressions of p-PERK/PERK， ATF4 and CHOP （P<0.01）， and the high-dose group had a markedly reduced GRP78 protein expression （P<0.01）. In the donepezil hydrochloride group， the Caspase-1 protein expression was increased （P<0.01） and the NLRP3 protein expression was decreased （P<0.01）. In the ZSHXP low-dose group， the GSDMD expression was elevated （P<0.01） while the NLRP3 protein expression was reduced （P<0.01）. After treatment with medium and high doses of ZSHXP， the protein expression levels of NLRP3， GSDMD and Caspase-1 were significantly decreased （P<0.01）. ConclusionThe ameliorative effect of ZSHXP on cognitive function in 2-VO model rats may be associated with its regulation of the GRP78/PERK/ATF4 signaling pathway， which ameliorates ERS and inhibits neuronal pyroptosis.

ObjectiveTo investigate the mechanism by which the Zishen Huoxue prescription （ZSHXP） ameliorates cognitive dysfunction in rats with vascular dementia （VD） induced by the bilateral common carotid artery ligation （2-VO model rats） through regulating the glucose-regulated protein 78 （GRP78）/protein kinase R-like endoplasmic reticulum kinase （PERK）/activating transcription factor 4 （ATF4） signaling pathway. MethodsA VD rat model was established via the 2-VO method. A total of 72 male Sprague-Dawley （SD） rats were randomly divided into six groups： Sham group， Model group， donepezil hydrochloride group （0.45 mg·kg^-1）， and ZSHXP groups at low （8.90 g·kg^-1）， medium （17.80 g·kg^-1）， and high （35.60 g·kg^-1） doses，with 12 rats in each group. The Morris Water Maze test was utilized to assess spatial learning and memory abilities of rats， and the Novel Object Recognition test was used to evaluate cognitive performance. Hematoxylin-eosin （HE） and Nissl staining were applied to observe the histological and morphological changes in hippocampal tissues. Transmission electron microscopy （TEM） was used to observe the morphological changes of endoplasmic reticulum in rat hippocampal neurons. Immunofluorescence staining was adopted to detect the colocalization of neuronal nuclei antigen （NeuN） with GRP78 and βⅢ Tubulin with gasdermin D （GSDMD） in hippocampal neurons. Western blot was used to detect the expression levels of endoplasmic reticulum stress （ERS）-related proteins including GRP78， PERK， ATF4， phosphorylated protein kinase R-like endoplasmic reticulum kinase （p-PERK）， C/EBP homologous protein （CHOP）， NOD-like receptor protein 3 （NLRP3）， Caspase-1 and GSDMD. ResultsCompared with the sham operation group， the model group showed a significantly prolonged escape latency （P<0.01）， a significant decrease in the number of platform crossings and the residence time in the target quadrant （P<0.01）， and a markedly reduced recognition index （P<0.01）. Histological observations revealed that the hippocampal neurons in the model group were disorderly arranged with reduced quantity， deformed and shrunken cell bodies， and pyknotic and hyperchromatic nuclei. The number of Nissl bodies decreased significantly. The number of endoplasmic reticula reduced obviously， accompanied by abnormal dilation and swelling， and the loss of normal folding structure. The fluorescence colocalization of NeuN with GRP78 and βⅢ Tubulin with GSDMD in the hippocampus was significantly increased in the model group. The protein expression levels of GRP78， p-PERK/PERK， ATF4， CHOP， NLRP3， GSDMD and Caspase-1 in the model group were significantly elevated （P<0.01）. Compared with the model group， the donepezil hydrochloride group and the ZSHXP medium- and high-dose groups had a significantly shortened escape latency （P<0.01） and an increased number of platform crossings （P<0.05， P<0.01）. The residence time in the target quadrant was increased in the donepezil hydrochloride group and all ZSHXP groups （P<0.05， P<0.01）， with a significantly improved recognition index （P<0.01）. In the donepezil hydrochloride group and all ZSHXP groups， the number of hippocampal neurons increased with a more compact arrangement and reduced nuclear hyperchromasia. The number of Nissl bodies increased with morphological structures tending to be normal. In the ZSHXP high-dose group， the number of endoplasmic reticula increased and the folding structure was restored. The fluorescence colocalization of NeuN with GRP78 and βⅢ Tubulin with GSDMD in the hippocampus was significantly weakened in the treatment groups. In the donepezil hydrochloride group， the protein expressions of GRP78， ATF4 and CHOP were increased （P<0.01）， while the expression of p-PERK/PERK was decreased （P<0.05）. In the ZSHXP low-dose group， the expressions of GRP78， p-PERK/PERK and CHOP were elevated （P<0.05， P<0.01）. The ZSHXP medium- and high-dose groups showed a significant decrease in the protein expressions of p-PERK/PERK， ATF4 and CHOP （P<0.01）， and the high-dose group had a markedly reduced GRP78 protein expression （P<0.01）. In the donepezil hydrochloride group， the Caspase-1 protein expression was increased （P<0.01） and the NLRP3 protein expression was decreased （P<0.01）. In the ZSHXP low-dose group， the GSDMD expression was elevated （P<0.01） while the NLRP3 protein expression was reduced （P<0.01）. After treatment with medium and high doses of ZSHXP， the protein expression levels of NLRP3， GSDMD and Caspase-1 were significantly decreased （P<0.01）. ConclusionThe ameliorative effect of ZSHXP on cognitive function in 2-VO model rats may be associated with its regulation of the GRP78/PERK/ATF4 signaling pathway， which ameliorates ERS and inhibits neuronal pyroptosis.

ObjectiveTo investigate microbial contamination status and distribution characteristics in laboratory animal barrier facilities, so as to provide a scientific basis for environmental quality control in barrier facilities. MethodsIn accordance with the national standard "Laboratory Animals—Environment and Housing Facilities" and the "Standard Operating Procedures" of the barrier facility, bacterial monitoring was performed on samples of air-settling bacteria, materials, and personnel gloves in the single-corridor barrier facility of the Animal Core Facility, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences (CEMCS). The monitoring data from January 2020 to December 2024 were collected, organized and statistically analyzed, and partial samples were subjected to species identification using PCR and sequencing methods. ResultsA total of 7 898 samples were collected from 2020 to 2024, including 3 175 air-settling bacteria samples, 3 353 material samples, and 1 370 glove samples. The overall compliance rate was 95.7% (7 559/7 898), among which the compliance rate of air-settling bacteria was 97.1% (3 084/3 175), that of materials was 93.2% (3 125/3 353), and that of personnel gloves was 98.5% (1 350/1 370). Over the five years, the compliance rates of all three types of monitored samples were above 90%. There were statistically significant differences in the compliance rates of air-settling bacteria and material samples among different quarters (P<0.05). Further investigation was conducted on samples collected from January to March 2024, and 190 bacterial strains were obtained through isolation and culture, including 126 strains from air-settling bacteria, 52 strains from materials, and 12 strains from personnel gloves. The strains were identified by PCR amplification and sequencing, and the 190 bacterial strains belonged to 9 genera and 20 species. Gram-positive bacteria accounted for the majority, with Staphylococcus as the dominant genus, accounting for 77.9% (148/190). ConclusionMicroorganisms carried by air, materials, and personnel gloves in barrier facilities are mainly Gram-positive bacteria. Regular monitoring of air-settling bacteria, materials, and personnel gloves in barrier facilities enables timely detection and control of potential risks during husbandry management and facility operation, which is of great significance for maintaining the sound operation of the barrier facility system and ensuring the quality of animal experiments.

Objective To investigate the heterogeneity and key molecular features of epithelial cells in triple-negative breast cancer (TNBC), identify prognostic biomarkers, and develop a robust survival prediction model. Methods Using TNBC single-cell transcriptomic data, epithelial cells were extracted, normalized, and subclustered to characterize their molecular signatures and functional differences. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was applied to establish co-expression modules in epithelial cells. Multiple machine learning algorithms were integrated to select key prognostic genes and develop a risk-score model, whose performance was evaluated using receiver operating characteristic (ROC) curves and Kaplan-Meier (K-M) survival analysis. In addition, the immune microenvironment features and potential drug-response differences between the high- and low-risk groups were systematically assessed. Finally, PCR was performed to validate the expression differences of the key genes between tumor and normal tissues. Results We characterized the composition and molecular features of TNBC epithelial subpopulations and identified a TNBC-associated epithelial subset. By integrating hdWGCNA with machine learning approaches, 10 key genes were selected to construct a prognostic model, which effectively stratified patients into distinct survival-risk groups and demonstrated favorable predictive performance in ROC and K-M analyses. Immune profiling revealed the differences in the infiltration levels of seven immune cell types and immune function-related features between the high- and low-risk groups. Drug-sensitivity analysis suggested potential differential responses to eight agents across the risk groups. PCR validation further confirmed the differential expression of the ten signature genes between tumor and normal tissues. Conclusion This study reveals epithelial heterogeneity in TNBC at single-cell resolution and establishes a 10-gene prognostic model, which may facilitate the stratification of TNBC risk and the evaluation of immune characteristics and potential therapeutic strategies.

Hepatocellular carcinoma (HCC) develops within a profoundly immunosuppressive tumor immune microenvironment (TIME), which limits the efficacy of immunotherapy. Polarization of tumor-associated macrophages (TAMs) toward a pro-tumorigenic M2 phenotype is a major driver of immune escape. Ferroptosis, an iron-dependent regulated cell death program, intersects with hepatic iron metabolism and immune regulation and thus offers promising points of therapeutic intervention. This review systematically elucidates the mechanistic role of TAM ferroptosis in HCC immune evasion and highlights a “bidirectional regulation” intervention strategy grounded in the Traditional Chinese medicine (TCM) principle of “fortifying healthy qi and eliminating pathogens” (Fuzheng Quxie). This strategy employs “eliminating pathogens” (Quxie) approaches to exploit the metabolic vulnerability of M2-like TAMs and precisely induce their ferroptosis. Moreover, it utilizes “fortifying healthy qi” (Fuzheng) approaches to protect M1-like TAMs and CD8⁺ T cells from oxidative damage. This parallel “induction-protection” paradigm demonstrates the unique advantages of TCM in systemically remodeling TIME through multitarget synergistic actions. Accordingly, precision regulation of TAM ferroptosis based on the Fuzheng Quxie theory represents a promising integrative Chinese-Western medicine strategy for overcoming current bottlenecks in HCC immunotherapy, although its clinical translational potential warrants further validation.

Background In 2021, chronic obstructive pulmonary disease (COPD) emerged as the forth leading cause of death in the world. However, the impact of air pollutants on COPD is still inconsistent across current studies. Objective To analyze the relationship between ambient sulfur dioxide (SO₂) exposure and hospital admissions for COPD in Lanzhou, and to examine the modified effects of SO₂ across different genders, age groups, and seasons. Methods A total of 20718 hospital admission records for COPD were collected from Lanzhou between 2016 and 2020, alongside synchronized data on SO₂ concentration and meteorological variables. A generalized additive model integrated with a distributed lag nonlinear model was used to assess the relationship and the lag effects between SO₂ exposure and COPD admissions. Potential confounders, including meteorological factors, day-of-the-week effect, and holidays, were controlled for, with a maximum lag period set at 7 d. Two-pollutant models and sensitivity analyses were conducted to ensure robustness. Results are expressed as relative risks (RR) with 95% confidence intervals (95%CI). Results During the study period, the average daily number of COPD admissions was 11.34±7.03. The average mass concentration of SO₂ was (23.72±12.35) μg·m⁻³. SO₂ exposure was positively correlated with COPD admissions; specifically, each 10 μg·m⁻³ increase in SO₂ concentration was associated with an RR of 1.440 (95%CI: 1.317, 1.573). Stratified analyses found that at a cumulative lag of 7 d, the RRs were higher among females, individuals aged ≥65 years, and during the cold season. Conversely, no significant increase in COPD admission risk related to SO₂ was observed during the warm season. For every 10 μg·m⁻³ increase in SO₂ concentration, the RR was 1.483 (95%CI: 1.311, 1.678) for females, 1.441 (95%CI: 1.311, 1.583) for those aged > 65 years， and 1.595 (95%CI: 1.313, 1.937) during the cold season. Conclusion Short-term exposure to ambient SO₂ exposure in Lanzhou is associated with an increased risk of COPD admission. The association is more pronounced among females, the elderly (aged> 65 years) and during the cold season.

Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

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.