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.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

BACKGROUND:In vitro construction of tissue-engineered intestinal models plays an important role in intestinal regeneration and intestinal disease research.The interaction of intestinal nervous system and intestinal epithelial barrier to maintain body homeostasis is a hot topic in the bionic construction of tissue-engineered intestinal tract.OBJECTIVE:To construct a bionic model that can mimic the enteric nervous system in vivo.METHODS:Using fibroin protein with villus structure as scaffold,human induced neural stem cells solidified with collagen were added to intestinal epithelial cells(Caco-2 and HT29-MTX-E12)for 3-day culture to construct a co-culture system of intestinal epithelial cells and nerve cells(co-culture group).Human induced neural stem cells or intestinal epithelial cells cultured alone that were inoculated with fibroin scaffolds were set as controls.Cell morphology was observed by scanning electron microscopy and hematoxylin-eosin staining.Cell activity was detected by Live/Dead cell staining.Human induced neural stem cell differentiation was detected by β-microtubulin immunofluorescence staining.Intestinal epithelial histological properties and barrier function were detected by microvillin,sucrase-isomaltase,tight junction protein 1,E-calmodulin,and mucin-2 immunofluorescence staining.The function of mucus secretion from intestinal epithelial cells was detected by Alcian blue staining.Alkaline phosphatase staining was performed to detect differentiation of intestinal epithelial cells,at the same time,sucrase-isomaltase,tight junction protein 1,and alkaline phosphatase mRNAs were detected by RT-qRCR.RESULTS AND CONCLUSION:The neuralized intestinal mucosal co-culture model with villi structure was successfully constructed,and neural stem cells and intestinal epithelial cells on the fibroin scaffold showed good cellular activities.After neuralization,the activity of alkaline phosphatase and sucrase-isomaltase in intestinal epithelial cells was enhanced,while the expression level of tight junction protein 1 was up-regulated.To conclude,the neuralized bionic intestinal epithelial model is beneficial to the maturation of intestinal mucosal epithelial cells and the formation of barrier function.

BACKGROUND:In vitro construction of tissue-engineered intestinal models plays an important role in intestinal regeneration and intestinal disease research.The interaction of intestinal nervous system and intestinal epithelial barrier to maintain body homeostasis is a hot topic in the bionic construction of tissue-engineered intestinal tract.OBJECTIVE:To construct a bionic model that can mimic the enteric nervous system in vivo.METHODS:Using fibroin protein with villus structure as scaffold,human induced neural stem cells solidified with collagen were added to intestinal epithelial cells(Caco-2 and HT29-MTX-E12)for 3-day culture to construct a co-culture system of intestinal epithelial cells and nerve cells(co-culture group).Human induced neural stem cells or intestinal epithelial cells cultured alone that were inoculated with fibroin scaffolds were set as controls.Cell morphology was observed by scanning electron microscopy and hematoxylin-eosin staining.Cell activity was detected by Live/Dead cell staining.Human induced neural stem cell differentiation was detected by β-microtubulin immunofluorescence staining.Intestinal epithelial histological properties and barrier function were detected by microvillin,sucrase-isomaltase,tight junction protein 1,E-calmodulin,and mucin-2 immunofluorescence staining.The function of mucus secretion from intestinal epithelial cells was detected by Alcian blue staining.Alkaline phosphatase staining was performed to detect differentiation of intestinal epithelial cells,at the same time,sucrase-isomaltase,tight junction protein 1,and alkaline phosphatase mRNAs were detected by RT-qRCR.RESULTS AND CONCLUSION:The neuralized intestinal mucosal co-culture model with villi structure was successfully constructed,and neural stem cells and intestinal epithelial cells on the fibroin scaffold showed good cellular activities.After neuralization,the activity of alkaline phosphatase and sucrase-isomaltase in intestinal epithelial cells was enhanced,while the expression level of tight junction protein 1 was up-regulated.To conclude,the neuralized bionic intestinal epithelial model is beneficial to the maturation of intestinal mucosal epithelial cells and the formation of barrier function.

Organophosphorus nerve agents are the most threatening chemical warfare agents and terrorist agents.The number of nerve agents and their related chemicals involved in the verification of Chemical Weapon Convention(CWC)exceeds ten million,with the majority being isomers.Accurate structural identification of these chemicals has always been one of the challenges in CWC related verification analysis.In this work,a total of 17 kinds of alkyl phosphonate isomers and structural analogs from 5 groups were designed and synthesized,and then analyzed by gas chromatography-mass spectrometry(GC-MS)and gas chromatography-infrared spectroscopy(GC-FTIR).The spectra of isomers or structural analogs obtained from two techniques as well as the structural information provided therein were compared and analyzed.The results showed that for isomers or structural analogs with similar MS spectra,FTIR spectra could provided more structural fingerprint information of compounds and had advantages in confirming structures.Combined with the excellent separation ability of GC,GC-FTIR can be used to assist GC-MS in the structural confirmation of alkyl phosphates,achieving rapid and accurate identification of isomers or structural analogues.

Apurinic/apyrimidinic endonuclease 1(APE 1)is a multifunctional protein that plays important roles in DNA repair and regulation of gene expression.Because APE 1 is overexpressed in various cancers,it can serve as a cancer biomarker for aiding clinical diagnosis,guiding therapy,and monitoring prognosis.On this basis,a label-free fluorescent probe was designed based on the primer exchange reaction(PER)strategy for highly sensitive detection of APE 1 activity.In the absence of APE 1,the structure of catalytic hairpin(HP)was stable and could not form G-quadruplex.Therefore,the background fluorescence of this sensing system was very low due to the dissociation of thioflavin T(ThT).In the presence of APE 1,the apurinic/apyrimidinic(AP)site of HP was cleaved by APE 1 and a short nucleic acid fragment that acted as a primer to initiate PER was generated.After PER reaction,a large number of G-quadruplex were produced,which could specifically bind with ThT and resulted in significant increase of fluorescence signal.The combination of low background design of HP and PER amplification made this biosensor had high sensitivity with a detection limit(3σ)of 0.0008 U/mL.Furthermore,the primer sequence was directly generated by the cleavage of APE 1 without additional addition,which not only increased the specificity of the reaction,but also simplified the experiment procedure.Moreover,the use of label-free fluorescence signal reduced the cost of the experiment,and realized rapid detection of APE 1.Finally,this sensor was used to detect APE 1 in human serum samples with spiked recoveries of 91%-104%,proving great potential in study of biological enzyme.

In this study,a sensitive lateral flow immunoassay(LFIA)platform based on carbon dots-mesoporous silica nanocomposite(CD-MSNs)fluorescent probes was constructed for high-performance detection of inflammatory marker interleukin-6(IL-6).Green fluorescent carbon dots(CDs)were prepared by hydrothermal method with 3,9-perylenic acid and 3-aminopropyltriethoxysilane(APTES)as raw materials,and highly fluorescent CD-MSNs composites were then constructed by encapsulating the prepared CDs in mesoporous silica nanoparticles(MSNs).Fluorescent probes were prepared by covalent coupling of CD-MSNs with IL-6 antibody.Fluorescent immunochromatographic test strips were constructed by spraying IL-6 capture antibody and goat anti-mouse IgG on nitrocellulose membrane as detection line(T-line)and quality control line(C-line),respectively.The fluorescence immunoassay analyzer was used to quantitatively detect the fluorescence intensity of T-line,and the experimental results showed that the LFIA platform based on this probe had a good linear relationship in IL-6 concentration range of 102-106 pg/mL,and the detection limit was 64 pg/mL,which was two orders of magnitude more sensitive than that of the traditional colloidal gold test strips.This method effectively solved the issue of insufficient sensitivity of traditional LFIA technique,and provided a rapid and highly sensitive detection method for early diagnosis of inflammatory diseases.

The holistic view is the key in the study of traditional Chinese medicine(TCM). The component structure theory is based on the holistic view to investigate the correlation between material basis and efficiency, which enriches the holistic "component-effect" research of TCM. Gintonin is a newly isolated non-saponin component of ginseng. Compared to ginsenosides, gintonin has many different pharmacological activities, and it provides new knowledge for the holistic research of ginseng. Thus, taking the discovery of gintonin from ginseng as an example, this paper explored the linkage between ginsenosides and gintonin from the perspective of "component-effect" correlations and systematically sorted out the similarities and differences between them in terms of structural characteristics, modes of action, and pharmacological activities. Starting from the collaborative interaction of TCM compounds, the study discussed the application and value of the holistic view in TCM "component-effect" research in the light of the component structure theory to provide new thoughts for the development of modern TCM research.
Panax/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Humans ; Ginsenosides/pharmacology* ; Animals