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.

With the rapid development of minimally invasive techniques in surgery, arti-ficial intelligence (AI), particularly deep learning, is playing an increasingly important role in mini-mally invasive surgery. By automated analysis of surgical videos, AI can efficiently perform key tasks such as instrument recognition, surgical phase identification, action analysis, anatomical structure recognition, intraoperative diagnosis, adverse event monitoring and smart desmoking. These appli-cations provide essential support for real-time monitoring, surgical navigation and skill assessment during surgery. The authors summarize the current research progress of AI in minimally invasive surgery, including its applications in the fields of hepatobiliary and pancreatic surgery, as well as gastrointestinal surgery. It also explores the potential of AI in enhancing surgical safety, efficiency and skill assessment. By synthesizing the latest research achievements of AI technology in the field of surgery, as well as analyzing its technical challenges and risks, it aims to provide guidance for future innovations and clinical applications, promoting the advancement and implementation of AI in minimally invasive surgery.

Objective:To investigate the clinical efficacy of extended abdominal wall resec-tion combined with reconstruction for abdominal wall aggressive fibromatosis (AF).Methods:The retrospective and descriptive study was conducted. The clinical data of 70 patients with abdominal wall AF who were admitted to 3 medical centers, including The First Affiliated Hospital of the University of Science and Technology of China, between January 2009 and July 2024 were collected. There were 6 males and 64 females, aged (36±13)years. All patients underwent extended abdominal wall resection combined with abdominal wall reconstruction. Observation indicators: (1) surgical situations; (2) tumor recurrence and postoperative complications. Comparisons of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Results:(1)Surgical situations. All 70 patients underwent extended abdominal wall resection combined with abdominal wall recons-truction. The operation time was 90(91)minutes and duration of postoperative hospital stay was 10(6)days. Of the 70 patients, 41 patients underwent abdominal wall AF resection plus polypropylene mesh abdominal wall reconstruction, with a defect area of 60(54)cm2. The mesh placement method was uniformly Sublay repair. The remaining 29 patients underwent abdominal wall AF resection plus direct suture repair, with a defect area of 34(31)cm2. There was a significant difference in the abdominal wall defect area between the two groups ( U=291.00, P<0.05). All 70 patients achieved R 0 resection. The distance from surgical margin to tumor edge was 2-3 cm in 39 cases and >3 cm in 31 cases. (2) Tumor recurrence and postoperative complications. All 70 patients were followed up for 78(90)months. During follow-up, 10 patients developed tumor recurrence (5 cases with mesh reinforced abdominal wall reconstruction and 5 cases with direct suture repair). Among them, one case was monitored, one case underwent radiotherapy, and neither received further surgical treatment. The remaining 8 patients underwent repeat R 0 resection, and no further recurrence occurred. There was no significant difference in recurrence rate between the patients with mesh reconstruction and patients with direct suture repair ( χ2=0.06, P>0.05). The postoperative recurrence rate was 9.7%(3/31) in patients with the distance from surgical margin to tumor edge >3 cm, versus 17.9%(7/39) in patients with the distance from surgical margin to tumor edge of 2-3 cm, showing no significant difference between them ( χ2=0.97, P>0.05). Sixty patients had no tumor recurrence. During follow-up, none of the 70 patients developed incisional hernia. Two patients experienced postoperative wound infection, and 6 cases developed postoperative chronic pain. Conclusion:Extended abdominal wall resection combined with reconstruction is safe and feasible for abdominal wall AF.

Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its role in HCC development.In the present study,we aim to explore how ALDOA is involved in HCC proliferation.HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout,which is consistent with ALDOA overexpression encouraging HCC prolifera-tion.Mechanistically,ALDOA knockout partially limits the glycolytic flux in HCC cells.Meanwhile,ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase;ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function.A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun,and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells.In HCC patients,the expression level of ALDOA was correlated with the phosphorylation level of c-Jun(Thr93)and poor prognosis.Remarkably,hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models,and the knockdown of Aldoa strikingly decreased HCC development in vivo.Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription,opening additional avenues for anti-cancer therapies.

With the rapid development of minimally invasive techniques in surgery, arti-ficial intelligence (AI), particularly deep learning, is playing an increasingly important role in mini-mally invasive surgery. By automated analysis of surgical videos, AI can efficiently perform key tasks such as instrument recognition, surgical phase identification, action analysis, anatomical structure recognition, intraoperative diagnosis, adverse event monitoring and smart desmoking. These appli-cations provide essential support for real-time monitoring, surgical navigation and skill assessment during surgery. The authors summarize the current research progress of AI in minimally invasive surgery, including its applications in the fields of hepatobiliary and pancreatic surgery, as well as gastrointestinal surgery. It also explores the potential of AI in enhancing surgical safety, efficiency and skill assessment. By synthesizing the latest research achievements of AI technology in the field of surgery, as well as analyzing its technical challenges and risks, it aims to provide guidance for future innovations and clinical applications, promoting the advancement and implementation of AI in minimally invasive surgery.

Objective:To investigate the clinical efficacy of extended abdominal wall resec-tion combined with reconstruction for abdominal wall aggressive fibromatosis (AF).Methods:The retrospective and descriptive study was conducted. The clinical data of 70 patients with abdominal wall AF who were admitted to 3 medical centers, including The First Affiliated Hospital of the University of Science and Technology of China, between January 2009 and July 2024 were collected. There were 6 males and 64 females, aged (36±13)years. All patients underwent extended abdominal wall resection combined with abdominal wall reconstruction. Observation indicators: (1) surgical situations; (2) tumor recurrence and postoperative complications. Comparisons of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Results:(1)Surgical situations. All 70 patients underwent extended abdominal wall resection combined with abdominal wall recons-truction. The operation time was 90(91)minutes and duration of postoperative hospital stay was 10(6)days. Of the 70 patients, 41 patients underwent abdominal wall AF resection plus polypropylene mesh abdominal wall reconstruction, with a defect area of 60(54)cm2. The mesh placement method was uniformly Sublay repair. The remaining 29 patients underwent abdominal wall AF resection plus direct suture repair, with a defect area of 34(31)cm2. There was a significant difference in the abdominal wall defect area between the two groups ( U=291.00, P<0.05). All 70 patients achieved R 0 resection. The distance from surgical margin to tumor edge was 2-3 cm in 39 cases and >3 cm in 31 cases. (2) Tumor recurrence and postoperative complications. All 70 patients were followed up for 78(90)months. During follow-up, 10 patients developed tumor recurrence (5 cases with mesh reinforced abdominal wall reconstruction and 5 cases with direct suture repair). Among them, one case was monitored, one case underwent radiotherapy, and neither received further surgical treatment. The remaining 8 patients underwent repeat R 0 resection, and no further recurrence occurred. There was no significant difference in recurrence rate between the patients with mesh reconstruction and patients with direct suture repair ( χ2=0.06, P>0.05). The postoperative recurrence rate was 9.7%(3/31) in patients with the distance from surgical margin to tumor edge >3 cm, versus 17.9%(7/39) in patients with the distance from surgical margin to tumor edge of 2-3 cm, showing no significant difference between them ( χ2=0.97, P>0.05). Sixty patients had no tumor recurrence. During follow-up, none of the 70 patients developed incisional hernia. Two patients experienced postoperative wound infection, and 6 cases developed postoperative chronic pain. Conclusion:Extended abdominal wall resection combined with reconstruction is safe and feasible for abdominal wall AF.

Objective To explore the effect and underlying molecular mechanism of miR-101 on ventricular remod-eling in rats after acute myocardial infarction(AMI).Methods The AMI rat model was established using the left anterior descending coronary artery ligation method.The AMI rats were randomly divided into AMI group,agomir-NC group,miR-101 agomir group and coumermycin A1 group,another 12 rats were selected as sham group with 12 in each.The targeting relationship between miR-101 and JAK2 was analyzed by Target Scan 8.0 database and double luciferase reporter gene assay.The expression of miR-101 in rat myocardium was detected by RT-qPCR.LVESD,LVEDD,LVEF and LVFS were measured by ultrasonography.The level of IL-1β,IL-6 and TNF-α in rats serum was determined by ELISA.The myocardial tissue lesion and fibrosis were detected by HE staining and Mas-son staining.The expression of collagenⅠand TGF-β in rat myocardial tissue was detected by immunohistochemical staining.The expression of E-cadherin,N-cadherin,Vimentin,p-JAK2,JAK2,p-STAT3 and STAT3 proteins was detected by Western blot.Results Compared with AMI group and agomir-NC group,the myocardial tissue lesions and fibrotic area in miR-101 agomir group were significantly decreased(P＜0.05),the level of LVESD,LVEDD,L-1β,IL-6,TNF-α,collagenⅠ,TGF-β,N-cadherin,vimentin,p-JAK2 and p-STAT3 decreased(P＜0.05).The levels of miR-101,LVEF,LVFS and E-cadherin were increased(P＜0.05).Compared with miR-101 agomir group,the myocardial tissue lesions and fibrotic area in coumermycin A1 group significantly increased(P＜0.05),the level of LVESD,LVEDD,L-1β,IL-6,TNF-α,collagenⅠ,TGF-β,N-cadherin,vimentin,p-JAK2 and p-STAT3 was increased(P＜0.05).The level of miR-101,LVEF,LVFS and E-cadherin was decreased(P＜0.05).Conclusions miR-101 inhibits myocardial inflammatory lesions,myocardial fibrosis and epithelial-mesenchymal fransition(EMT)process after AMI with a mechanism targeting at JAK2/STAT3 signaling pathway,thus alleviates ventricular remodeling in rats after AMI.

Objective:To investigate the role of microglial polarization modulated by triggering receptor expressed on myeloid cells 2/insulin-like growth factor-1(TREM2/IGF-1) in hypertensive model mice exposed to diesel exhaust particulate matter (DPM), with a focus on its implications for anxious- and depressive-like behaviors.Methods:SPF-grade male C57BL/6J mice were divided into the control group, the hypertension group, the DPM group, and the hypertension+ DPM group according to the principle of weight-matching, with 10 mice in each group. The hypertension model was established by intraperitoneal injection of angiotensin Ⅱ (AngⅡ) in hypertension group and hypertension+ DPM group, and mice in the control group and DPM group were intraperitoneally injected with an equivalent amount of 0.9% NaCl solution.DPM suspension was instilled into the nasal cavity of the mice in DPM group and hypertension+ DPM group(1 μg/μL, 10 μL, once a day for 56 days).Behavioral tests, including the sucrose preference test, tail suspension test, elevated plus maze test, and open field test, were conducted to evaluate anxious- and depressive-like behaviors.TREM2-overexpressing BV2 cell model was established through plasmid transfection technology.Western blot was applied to measure the protein expression of IL-1β, IL-6, TNF-α, iNOS, Arg-1, TREM2 and IGF-1.SPSS 23.0 software was used for statistical analysis, one-way ANOVA was used for comparison among multiple groups, and LSD- t test was used for post-hoc testing. Results:(1)There were statistically significant differences in the sucrose preference rate, immobility time in the tail suspension test, percentage of time and number of entries into the open arms in the elevated plus maze, as well as the total distance, percentage of time spent in the central area in the open field test among the four groups of mice( F=22.82, 21.60, 36.17, 20.99, 5.85, 13.24, all P<0.01).The sucrose preference rate, percentage of time spent in the open arms, percentage of number of entries into the open arms, total distance and percentage of time spent in the central area of the DPM group and the hypertension group were lower than those of the control group( P<0.05), while the immobility time of the two group was higher than that of the control group( P<0.05). The sucrose preference rate((55.62±4.46)%) and percentage of time spent in the open arms((4.17±0.62)%) of the hypertension+ DPM group were lower than those of the DPM group((60.78±3.21)%, (6.44±0.89)%) and the hypertension group((66.26±4.25)%, (6.53±1.29)%)(all P<0.05), while the immobility time((155.42±12.50)s) was higher than that of the DPM group((129.03±5.43)s) and the hypertension group((129.28±10.55)s)(both P<0.05).(2)Western blot analysis revealed statistically significant differences in protein expression of IL-1β, IL-6, TNF-α, iNOS, Arg-1, and TREM2/IGF-1 in the medial prefrontal cortex(mPFC) among the four experimental groups( F=12.23, 10.51, 33.89, 145.40, 11.85, 15.56, 33.11, all P<0.05).The hypertension+ DPM group demonstrated significantly higher protein expression of IL-1β and IL-6 compared to the hypertension group (all P<0.05). Relative to the hypertension+ DPM group, TNF-α and iNOS protein expression was elevated in both the hypertension group and DPM group, whereas Arg-1 protein expression was lower in the hypertension group(all P<0.05). Additionally, TREM2 and IGF-1 protein expression in the hypertension and DPM groups were lower than those in the control group but higher than those in the hypertension+ DPM group(all P<0.05).(3)The protein expressions of IL-1β, IL-6 and TNF-α in BV2 cells of the DPM+ AngⅡ-TREM2 overexpression group were lower than those of the DPM+ AngⅡ group. The expression of iNOS was lower than that in the DPM+ AngⅡ group, while the expression of Arg-1 was higher than that in the DPM+ AngⅡ group(all P<0.05). Conclusion:DPM exposure aggravates anxious- and depressive-like behaviors in hypertensive model mice, with TREM2/IGF-1-regulated microglial polarization playing a significant role in this process.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome