ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

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 investigate the effect and mechanism of Tangzhi formula（TZF） on improving glucose and lipid metabolism disorders in type 2 diabetes mellitus （T2DM） rats.METHODS Thirty SPF-grade SD rats were used to establish a T2DM rat model through high-fat diet feeding combined with intraperitoneal injection of streptozotocin. After successful modeling， the rats were divided into the model group， metformin group （positive control， 0.18 g/kg）， and TZF low-， medium-， and high-dose groups （5， 10， and 20 g/kg）， with 6 rats in each group. An additional 6 rats were selected as the blank group. The rats in each group were orally administered the corresponding volume of drug solution or saline， and continuous dosing was performed for 6 weeks， once daily. Fasting blood glucose （FBG）， area under the curve of oral glucose tolerance test （OGTT-AUC）， area under the curve of intraperitoneal insulin tolerance test （IPITT-AUC）， serum total cholesterol （TC）， triglyceride （TG）， low-density lipoprotein cholesterol （LDL-C）， and high-density lipoprotein cholesterol （HDL-C） levels were measured. Hematoxylin-eosin （HE） staining and oil red O staining were used to observe hepatic pathological morphology and lipid deposition. Differentially expressed proteins in liver tissues were screened by proteomics analysis， and key proteins in signaling pathways were verified by Western blot and immunofluorescence staining.RESULTS Compared with the blank group， the levels of FBG， OGTT-AUC， IPITT-AUC， LDL-C， TG， and TC in the model group were significantly increased （ P ＜0.05）， while HDL-C level was significantly decreased （ P ＜0.05）； the liver tissues showed disordered hepatic cords， punctate necrosis of hepatocytes， and significant lipid deposition， the NAFLD activity score and positive area of lipid droplets were significantly increased（ P ＜0.05）. Compared with the model group， the above indicators in TZF low-， medium-， and high-dose groups and metformin group were significantly reversed （ P ＜0.05）； hepatic pathological injury and lipid deposition were alleviated. Proteomics results showed that a total of 442 differentially expressed proteins were screened between the model group and the blank group， and 358 differentially expressed proteins were screened between the TZF high-dose group and the model group. Among these differentially expressed proteins， multiple proteins closely related to glucose and lipid metabolism showed a reversal trend after TZF intervention. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the peroxisome proliferator-activated receptor （PPAR） signaling pathway was significantly enriched. The validation experiment results showed that TZF could significantly up-regulate the expression of PPARα， PPARγ， and apolipoprotein A1 （ApoA1） in rat liver tissues （ P ＜0.05）， and down-regulate the expression of stearoyl-CoA desaturase 1 （SCD1） and perilipin 2 （PLIN2） （ P ＜0.05）.CONCLUSIONS TZF can improve glucose and lipid metabolism disorders in T2DM rats； its mechanism may be related to the activation of the PPAR signaling pathway and the regulation of downstream lipid metabolism-related proteins SCD1， PLIN2， and ApoA1.

ObjectiveTo investigate the biological reparative effects of platelet-rich fibrin （PRF） extract on injured endometrial stromal cells （ESCs） induced by mifepristone and the underlying molecular mechanisms. MethodsAn ESCs injury model was established using mifepristone treatment. Cells were divided into four groups： untreated control （Con）， mifepristone-injured group （M）， mifepristone treatment+PRF extract group （M+P）， and mifepristone treatment+PRF extract+growth factor inhibitors treatment group， including M+P+T， M+P+Me， and M+P+CJ. Cell viability was detected using the CCK-8 assay， and migration ability was evaluated via the scratch wound healing assay. The release kinetics of growth factors， including vascular endothelial growth factor （VEGF）， platelet-derived growth factor-BB （PDGF-BB）， and transforming growth factor-beta 1 （TGF-β1） from PRF extract were measured by ELISA. The mRNA and protein expression levels of apoptosis-related factors （Bcl-2， Bax， and Caspase-3） were analyzed by RT-qPCR and Western blot， respectively. ResultsVEGF， PDGF-BB， and TGF-β1 were continuously released from the PRF extract over two weeks， with peak release observed on days 3-7. The extract significantly restored the proliferation and migration of mifepristone-injured ESCs （all P<0.000 1）. PRF extract up-regulated the mRNA and protein expression of the anti-apoptotic factor Bcl-2 （all P<0.000 1） and down-regulated that of the pro-apoptotic factors Bax and Caspase-3 （all P<0.000 1） in mifepristone-injured ESCs. Inhibitors of VEGF， PDGF-BB， and TGF-β1 （Tanshinone IIA， Methylnissolin， and CJJ300） significantly reversed the protective effects of PRF extract on mifepristone-injured ESCs （all P<0.05）. ConclusionPRF extract promotes the repair of injured ESCs by enhancing cell proliferation， attenuating apoptosis， and increasing migration capacity， which involve multiple growth factors， including VEGF， PDGF-BB， and TGF-β1.

ObjectiveTo investigate the effects of 7-dehydrocholesterol reductase （DHCR7） in promoting proliferation， migration， and invasion of lung adenocarcinoma cells and the underlying signaling mechanisms. MethodsThe expression level of DHCR7 in lung adenocarcinoma and its prognosis were analyzed by using public databases. DHCR7 protein expression levels in the lung adenocarcinoma cell lines H1299 and A549 were assessed by Western blot， using the normal lung epithelial cell line BEAS-2B as a control. Small interfering RNA （siRNA） was used to knock down DHCR7 expression in H1299 and A549 cells. Assays including colony formation， CCK-8， wound healing， and Transwell experiments were conducted to assess the proliferation， migration， and invasion of the knockdown cells. Next， Western blot was employed to assess the phosphorylation levels of key signaling molecules in the phosphoinositide 3-kinase/protein kinase B （PI3K/AKT）， janus kinase/signal transducer and activator of transcription 3 （JAK/STAT3），mitogen-activated protein kinase/extracellular signal-regulated kinase pathway （MAPK/ERK） （p-AKT， p-STAT3， p-ERK）. ResultsBioinformatics results indicated that both DHCR7 mRNA and protein were highly expressed in lung adenocarcinoma compared with normal tissues adjacent to cancer. Furthermore， higher DHCR7 mRNA level was associated with poor prognosis （P<0.001）. The expression levels of DHCR7 were significantly higher in both H1299 and A549 cells than that in BEAS-2B cells （P<0.05， P<0.01）. Compared with si-control， the proliferation， migration， and invasion abilities of si-DHCR7 H1299 and A549 cells significantly decreased. Among the phosphorylated signaling molecules detected， p-ERK was significantly downregulated （P<0.000 1， P<0.01） whereas p-AKT and p-STAT3 levels were not significantly changed. ConclusionDHCR7 has prominent effects in promoting the proliferation， migration， and invasion of lung adenocarcinoma cells， and the underlying mechanisms are related to the MAPK/ERK signaling pathway.

AIM To study the chemical constituents from the sticks and leaves of Croton cascarilloides Raeusch.and their biological activities.METHODS The 95％ethanol extract from the sticks and leaves of C.cascarilloides was isolated and purified by MCI,silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.LPS-induced NO RAW264.7 cell model induced by LPS was used to evaluate its anti-inflammatory activity in vitro.GES-1 injury model induced by taurocholic acid was used to screen the gastric mucosal protection activity.RESULTS Fourteen compounds were isolated and identified as bullatantriol(1),(-)-boscialin(2),(+)-dehydrovomifoliol(3),3-(hydroxylacetyl)-indole(4),pinoresinol(5),3,7-dimethyl-octa-1,7-diene-3,6-ol(6),(+)-syringaresinol(7),curcasinlignan B(8),cleomiscosin C(9),cleomiscosinD(10),2,6-dimethyl-octa-1,7-dien-3,6-diol(11),vanillin(12),vanillic acid(13),methyl vanillate(14).Compound 4 had certain anti-inflammatory activity,with IC50 values of 73.62 μmol/L.The protective rates of 25 μmol/L compounds 1-4,6,9-12 and 14 on gastric mucosal epithelial cells were 30.07％,34.18％,23.91％,30.92％,17.51％,19.69％,31.76％,22.46％,30.56％and 14.49％,respectively.CONCLUSION Compounds 1-14 are isolated from this plant for the first time.Compound 4 shows anti-inflammatory activity,1-4,6,9-12 and 14 show different degrees of gastric mucosal epithelial cell protective activity.

Objective:To systematically evaluate the incidence and influencing factors of postoperative stroke in patients with acute type A aortic dissection (ATAAD).Methods:Nine Chinese and English databases, including PubMed, Embase, CINAHL, JAMA, The Cochrane Library, CNKI, Wanfang, Vip and Chinese Biomedicine, were searched by computer to include literatures evaluating the incidence of postoperative stroke and its influencing factors in ATAAD patients. The search period was from the establishment of the database to September 2024. Two researchers independently screened the literature, extracted data, and evaluated the risk of bias in the included studies. Stata 14.0 software was used to combine the prevalence rate, and descriptive analysis of influencing factors was performed.Results:A total of 22 articles were included, including 16 734 ATAAD patients, published from 2018 to 2024. Meta-analysis results showed that the incidence of postoperative stroke in ATAAD patients was 16% (14%-18%). Subgroup analyses showed a higher incidence of postoperative stroke in patients with ATAAD in Europe (19%, 95% CI: 15%-23%), with a sample size of 1 to 300 patients (18%, 95% CI: 14%-22%), and in 2024 (20%, 95% CI: 14%-28%). Descriptive analysis shows that the factors influencing the occurrence of postoperative stroke in ATAAD patients include preoperative history (preoperative hypotension, preoperative history of stroke, history of carotid artery disease, history of cardiac arrest), intraoperative measures (total arch replacement, femoral artery intubation, anterograde cerebral perfusion, intraoperative oxygen satiation), and various types of time (cryopreservation time, extracorporeal circulation time, operation time). Conclusion:The incidence of postoperative stroke is higher in ATAAD patients. Preoperative hypotension, history of stroke before surgery, history of carotid artery disease, history of cardiac arrest, total arch replacement, femoral artery intubation, anterograde cerebral perfusion, decrease of cerebral oxygen saturation during operation, and longer hypothermia stop time, cardiopulmonary bypass time and operation time may increase the risk of postoperative stroke in ATAAD patients.

In this work,a rapid and label-free sensing platform was designed for visual detection of p53 gene.The rolling circle amplification(RCA)process of the assay platform was activated by p53 gene to produce long DNA-wires,which could bound with berberine hydrochloride(BBH)and further enhanced its fluorescence.This method showed high sensitivity with a low detection limit of 5.63 pmol/L,and high specificity toward p53 gene over other interference materials,even for single-base mutation gene.The method could realize the visual detection of targets under the illumination of a UV lamp.In addition,the designed fluorescence detection platform was successfully applied to p53 gene analysis in 10% fetal bovine serum samples,and the relative standard deviation and the recoveries were 0.1% -1.2% and 99.5% -104.7%,respectively.This approach had satisfactory characteristics,such as low cost,label-free,rapidity,high sensitivity,good selectivity and anti-interference ability,and reliable detection capability for complex practical samples,demonstrating a promising prospect in the diagnosis and treatment of diseases,especially for cancer.