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 construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

The chemical composition of Paeoniae Radix Alba(PRA) is complex, with primary secondary metabolites including monoterpenoids, tannins, triterpenoids, and flavonoids. In previous studies on the material basis of PRA, it was found that, in addition to the widely studied characteristic monoterpene glycosides, tannic acid components also play an important role in the efficacy of PRA. However, their pharmacological effects have not been thoroughly investigated. This paper reviews the tannic acid components in PRA, including pentagaloyl glucose(PGG), tetragaloyl glucose(TGG), trigaloyl glucose(TriGG), and gallic acid, along with their structures, properties, and characteristics to provide a detailed discussion of their pharmacological activities and related mechanisms, aiming to offer a theoretical basis for the material basis research and clinical application of PRA.
Paeonia/chemistry* ; Tannins/chemistry* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Animals ; Plant Extracts

OBJECTIVE: Cancer remains a significant global health challenge, necessitating the development of effective treatment approaches. Developing synergistic therapy can provide a highly promising strategy for anti-cancer treatment through combining the benefits of various mechanisms. METHODS: In this study, we developed a synergistic strategy for chemo-photothermal therapy by constructing nanocomposites using gold nanorods (GNRs) and tetrahedral framework nucleic acids (tFNA) loaded with the anti-tumor drug doxorubicin (DOX). RESULTS: Our in vitro studies have systematically clarified the anti-cancer behaviors of tFNA-DOX@GNR nanocomposites, characterized by their enhanced cellular uptake and proficient lysosomal escape capabilities. It was found that the key role of tFNA-DOX@GNR nanocomposites in tumor ablation is primarily due to their capacity to induce cytotoxicity in tumor cells via a photothermal effect, which generates instantaneous high temperatures. This mechanism introduces various responses in tumor cells, facilitated by the thermal effect and the integrated chemotherapeutic action of DOX. These reactions include the induction of endoplasmic reticulum stress, characterized by elevated reactive oxygen species levels, the promotion of apoptotic cell death, and the suppression of tumor cell proliferation. CONCLUSION This work exhibits the potential of synergistic therapy utilizing nanocomposites for cancer treatment and offers a promising avenue for future therapeutic strategies.
Doxorubicin/chemistry* ; Gold/chemistry* ; Nanotubes/chemistry* ; Humans ; Nanocomposites/chemistry* ; Cell Line, Tumor ; Nucleic Acids/chemistry* ; Antibiotics, Antineoplastic/pharmacology* ; Antineoplastic Agents/administration & dosage*

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective To investigate the effects of low background radiation environments in deep underground settings on the biological behavior of NP69 human nasopharyngeal epithelial cells(NP69 cells)and the underlying molecular mechanisms.Methods A parallel control experimental design was adopted and NP69 cells were synchronously cultured in settings of three underground depths at the China in situ Deep-Underground Facility&Life Observatory(DeUFO)—ground level(DeUFO-0 m),1 000 m underground(DeUFO-1 000 m),and 1 500 m underground(DeUFO-1 500 m).Changes in cell proliferation and migration capabilities were assessed using the Cell Counting Kit-8(CCK-8)assay and scratch assay,respectively.High-throughput RNA sequencing(RNA-Seq)was performed to identify differentially expressed genes(DEGs).Functional annotation and pathway enrichment analysis of the DEGs were performed using the Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)databases.Results CCK-8 assay revealed that,after 72 h of culture,the absorbance value of the DeUFO-0 m group was 1.35 times and 1.27 times those of the those of the DeUFO-1 000 m and DeUFO-1 500 m groups,respectively(both P<0.000 1).After 96 h of culture,the absorbance value of the DeUFO-0 m group was 1.52 times and 1.41 times those of the DeUFO-1 000 m and DeUFO-1 500 m groups,respectively(both P<0.000 1).Colony formation assays revealed that the number of cell colonies in the DeUFO-0 m group was 1.59 times and 1.27 times those in the DeUFO-1 000 m group and DeUFO-1 500 m group,respectively(both P<0.001).The scratch assay revealed that the 36-hour wound healing rate of the DeUFO-0 m group was 2.22 times and 4.00 times those of the DeUFO-1 000 m group and DeUFO-1 500 m group,respectively(both P<0.000 1).Transwell assays revealed that the number of migrating cells in the DeUFO-0 m group was 2.08 times and 2.56 times those in the DeUFO-1 000 m group and DeUFO-1 500 m group,respectively(both P<0.000 1).Transcriptome sequencing analysis revealed consistent upregulation of CELF2,CELF4,CGB8,GRHL2,and DMRTA2 genes in the DeUFO-1 000 m and DeUFO-1 500 m groups.Pathway enrichment analysis indicated significant enrichment of extracellular matrix(ECM)remodeling-associated pathways and gene expression regulation pathways in the experimental groups(false discovery rate[FDR]<0.05).Conclusion The low background radiation environment in deep underground settings suppresses the proliferation and migration activities of NP69 cells by mediating ECM remodeling and post-transcriptional regulatory mechanisms through the regulation of target genes such as the CELF family.This study provides experimental evidence for establishing a dose-response relationship between environmental radiation and cellular effects.

Objective To investigate the antitumor effects of triptolide against CT26 colon cancer and its impact on the expression of Polo-like kinase-1(PLK-1)protein.Methods Forty clean grade BALB/c mice,each mouse was implanted with 1×106 CT26 cells into the dorsal side of the right forelimb to establish a tumor-bearing mouse model.Experimental animals were randomly divided into four groups,the tumor model group(saline control),the positive drug group[oxaliplatin,5 mg/(kg·d)],the low-dose triptolide group[50 μg/(kg·/d)],and the high-dose triptolide group[100 μg/(kg·d)].The drugs were administered through intraperitoneal injection(10 times in total,once every other day).The in vitro effects of the drugs on the proliferation,migration,invasion,and mitosis of CT26 cells were also assessed.Results Triptolide significantly inhibited the proliferation,migration,and invasion of CT26 colon cancer cells,and disrupted the separation of centrosomes and the correct arrangement of chromosomes during the prophase of mitosis in tumor cells.The binding energy of triptolide and PLK-1 protein was-7.1 kcal/mol,and it could down-regulate the expression of PLK-1 in CT26 cells.Conclusion Triptolide exerts its antitumor effects against CT26 colon cancer by downregulating the expression of PLK-1.