ObjectiveTo explore the possible mechanisms by which ligustilide （LIG） exerts neuroprotective effects on ischemic stroke （IS） by inhibiting the release of neutrophil extracellular traps （NETs）， promoting blood-brain barrier repair， and alleviating post-ischemic neuroinflammation， thereby providing a new direction for IS treatment. MethodsA middle cerebral artery occlusion （MCAO） model was established in rats. The rats were divided into the sham operation （Sham） group， model （Model） group， low- and high-dose LIG groups （20， 40 mg·kg^-1）， and the NET inhibitor CI-amidine group （CI-amidine， 10 mg·kg^-1）. Drug treatments were administered for 3 days. Neurological injury after ischemia was evaluated by 2，3，5-triphenyltetrazolium chloride （TTC） staining， neurological deficit scoring， and brain index measurement. Flow cytometry and Western blot were used to analyze changes in neutrophil expression. Immunofluorescence was used to observe the fluorescence intensity of the NET marker citrullinated histone H3 （H3Cit）. Western blot was performed to detect the expression of blood-brain barrier tight junction-related proteins and inflammatory factors， including interleukin-18 （IL-18） and interleukin-1β （IL-1β）. ResultsCompared with the Sham group， the Model group exhibited significant brain tissue injury （P<0.05）， significantly increased neutrophil numbers and NET expression （P<0.05）， significantly impaired blood-brain barrier permeability （P<0.05）， and significantly increased expression of inflammatory factors （P<0.05）. Compared with the Model group， both low- and high-dose LIG significantly alleviated brain tissue injury in rats （P<0.01）， inhibited neutrophil numbers and NET expression （P<0.01）， reduced blood-brain barrier damage （P<0.01）， and suppressed the expression of inflammatory factors IL-18 and IL-1β （P<0.01）， thereby ultimately exerting a neuroprotective effect. ConclusionThe neuroprotective effect of LIG in rats with cerebral ischemia-reperfusion injury may be related to inhibition of neutrophils and the NETs induced by them.

ObjectiveThis paper aims to investigate the protective effects of the Tanyu Tongzhi Youhua prescription（TYTZP） against myocardial ischemia/reperfusion injury in rats via regulation of the cyclic GMP-AMP synthase （cGAS）/stimulator of interferon genes （STING） signaling pathway. MethodsFifty-six 8-week-old male Sprague-Dawley （SD） rats were randomly divided into sham group， model group， ticagrelor group （32.4 mg·kg^-1）， RU320521 （RU.521cGAS inhibitors） group （5 mL·kg^-1）， groups of TYTZP with low dose （3.6 g·kg^-1）， medium dose （7.2 g·kg^-1）， and high dose （14.4 g·kg^-1）， with eight rats per group. The ticagrelor group and groups of TYTZP with different doses received pre-treatment for seven days according to their respective protocols. The RU.521 group received an intraperitoneal injection one hour before modeling. A rat model of the no-reflow phenomenon in myocardial ischemia/reperfusion injury was established by ligating the left anterior descending coronary artery in situ. Myocardial no-reflow area was determined by thioflavin staining. Histopathological morphology of myocardial tissue was observed via hematoxylin and eosin （HE） staining. Cardiac function was detected by echocardiography. Myocardial microcirculation function change was observed by using real-time myocardial contrast echocardiography. The myocardial enzyme levels in the serum were measured by serum biochemical analysis. The double-stranded DNA （dsDNA） levels were detected by using PicoGreen. The protein expression of cGAS， STING， and nuclear factor-κB （NF-κB） p65 in myocardial tissue was detected by Western blot. The levels of cardiac troponin Ⅰ （cTNⅠ）， cardiac troponin T （cTNT）， interleukin-6 （IL-6）， interleukin-1β （IL-1β）， and tumor necrosis factor-α （TNF-α） in the peripheral blood were measured by enzyme-linked immunosorbent assay （ELISA）. ResultsCompared with the sham group， the model group showed a significantly increased myocardial no-reflow area （P<0.01）. Myocardial fiber rupture and disarray and inflammatory cell infiltration were observed by HE staining. The ultrasound results indicated that left ventricular ejection fraction （LVEF） and left ventricular fractional shortening （LVFS） （P<0.01） were significantly decreased. Real-time myocardial contrast echocardiography showed that the peak time of myocardial blood perfusion was significantly prolonged （P<0.01）， and the levels of creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， cTNⅠ， cTNT， and dsDNA were significantly elevated （P<0.01）. Western blot results showed that the myocardial protein expressions of cGAS， STING， and NF-κB p65 were upregulated （P<0.01）. ELISA results showed that the inflammatory factors in the serum such as IL-6， IL-1β， and TNF-α were increased （P<0.01）. Compared with the model group， the group of the TYTZP significantly reduced the levels of myocardial enzyme， troponins， and dsDNA （P<0.01， P<0.05）， improved cardiac function and myocardial microcirculation， alleviated histopathological morphology and inflammatory infiltration， inhibited activation of the cGAS/STING pathway， reduced the expression of NF-κB p65 （P<0.01， P<0.05）， and inhibited inflammatory response. ConclusionThe TYTZP mitigates the no-reflow phenomenon in myocardial ischemia/reperfusion injury， and its mechanism is associated with inhibiting the activation of the cGAS/STING pathway and attenuating inflammatory responses.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

Chronic obstructive pulmonary disease（COPD） is a common chronic respiratory disorder frequently accompanied by diaphragmatic dysfunction during its course， which significantly increases respiratory burden and impairs quality of life. As the primary inspiratory muscle， the diaphragm is prone to fatigue， atrophy， inflammation， and fibrosis during the long-term progression of COPD. Its pathological mechanisms involve multiple pathways such as inflammatory responses， oxidative stress， mitochondrial dysfunction， apoptosis， ion channel abnormalities， epigenetic regulation， autophagy disorder， and protein metabolism imbalance. In recent years， traditional Chinese medicine（TCM） has demonstrated multi-targeted and systemic regulatory advantages in improving diaphragmatic function in COPD. However， related studies remain fragmented， and integrated mechanistic understanding is lacking. This paper focuses on the mechanism-target-TCM intervention framework， systematically summarizing the molecular mechanisms of diaphragmatic dysfunction， while incorporating the TCM theory of Zongqi（ancestral Qi）. It highlights the therapeutic effects of Chinese herbal formulas， single herbs， and active components in modulating inflammation， oxidative stress， mitochondrial function， ion channels， epigenetic processes， autophagy， and protein homeostasis. Additionally， the review outlines existing challenges， including insufficient study volume， unbalanced selection of herbal prescriptions， limited mechanistic depth， inconsistent disease models and experimental designs， lack of standardized diaphragmatic function assessment， and weak clinical validation. Future research should strengthen the integration of TCM and modern medicine， identify additional therapeutic targets， deepen mechanistic research， and establish unified and standardized experimental systems to advance the theoretical foundation and clinical application of TCM in the prevention and treatment of COPD-related diaphragmatic dysfunction.

Objective To construct glucose oxidase（GOx）–loaded nanogels （GONGs）, optimize their formulation, and evaluate their capacity to inhibit the Warburg effect in glioma cells. Methods A responsive polymer （HAM） was synthesized and used to self-assemble GONGs, which were then characterized. Encapsulation efficiency and drug loading were determined using fluorescence spectrophotometry. Biocompatibility was tested by measuring cytotoxicity and hemolytic activity. Western blotting was used to evaluate the effects of GONGs on the expression of proteins associated with the Warburg phenotype and oxidative damage in glioma cells. Results GONGs prepared at a drug–to–polymer ratio of 1∶10 exhibited a particle size of 140.3 nm and a zeta potential of −27.2 mV. Compared with free GOx, GONGs markedly reduced cytotoxicity, increased the IC₅₀ in hUVEC cells from 2.150 nmol/L to 74.86 nmol/L, and significantly decreased hemolysis. At a GOx concentration of 2 nmol/L, GONGs effectively downregulated glycolysis-related proteins, such as HK2 and LDHA, and inhibited glutamine metabolism in glioma cells. Conclusion GONGs exhibited high GOx loading capacity, significantly reduced GOx-induced cytotoxicity, inhibited the Warburg effect in glioma cells and induced oxidative damage.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Objective: To explore the latent classes of peer victimization among junior high school students, and to analyze the association between the characteristics of different classes and non suicidal self injury(NSSI) behavior,so as to provide scientific basis for the prevention and intervention of NSSI behavior among junior high school students. Methods: A census method was used to select 19 738 students from 16 junior high schools in a central urban area of Wuhan as research subjects from November to December 2024. The Multidimensional Peer Victimization Scale and a self designed NSSI questionnaire were used to assess peer victimization and NSSI behaviors. Latent profile analysis (LPA) was used to identify latent classes of peer victimization among students by sex. Binary Logistic regression model was used to analyze the association between latent classes of peer victimization and NSSI behavior among junior high school students of different genders. Results: Latent patterns of peer victimization among boys were classified into 4 groups:no victimization group (85.8%, n =8 874), low victimization-verbal type group (6.6%, n =682), low victimization-mixed type group (5.7%, n =587) and high victimization group (1.9%, n =195); girls were classified into 4 groups:no victimization group (87.0%, n =8 179), low victimization group (7.5%, n =702), high victimization-social type group (3.8%, n =360) and high victimization-physical type group (1.7%, n =159). After controlling for only child status, place of residence, parenting style, and self rated family socioeconomic status, binary Logistic regression analysis showed that the risk of NSSI behavior among boys increased sequentially in the low victimization-verbal type group( OR =4.14, 95% CI =3.22-5.31), low victimization-mixed type group ( OR =4.75, 95% CI =3.68-6.13), and high victimization group ( OR =8.26, 95% CI =5.83-11.71) compared to the no victimization group; the risks of NSSI behavior among girls increased sequentially in the low victimization group ( OR =3.06, 95% CI = 2.51-3.72), high victimization-social type group ( OR =4.01, 95% CI =3.13-5.15), and high victimization-physical type group ( OR =6.18, 95% CI =4.38-8.73) compared to the no victimization group (all P <0.05). Conclusions There are gender differences in the latent classes of peer victimization among junior high school students and the risk of NSSI behavior varies across different victimization classes. Targeted prevention and intervention should be implemented based on the gender of junior high school students and the characteristics of peer victimization students experience.

Objective To investigate the impact of intraoperative red blood cell (RBC) transfusion volume on the postoperative oxygenation index in lung transplant recipients. Methods This retrospective study analyzed the clinical data of patients who underwent lung transplantation at Wuxi People's Hospital Affiliated to Nanjing Medical University from 2021 to 2023. Patients were divided into a non-severe primary graft dysfunction (PGD) group and a severe PGD group based on whether their postoperative oxygenation index was>200 mm Hg at 0, 24, and 48 h. General patient data and intraoperative RBC transfusion volumes were compared between the two groups. A binary logistic regression model was constructed to explore the effect size (OR and its 95%CI) of RBC transfusion volume on postoperative oxygenation status at different time points (0, 24, and 48 h). The area under the receiver operating characteristic curve was calculated to evaluate the model's diagnostic performance. Results A total of 351 patients were included (260 males, 91 females), with ages ranging from 20 to 77 years. The OR for the effect of intraoperative RBC transfusion on poor oxygenation was 1.486 (95%CI 0.982 to 2.248, P=0.061) at 0 h postoperatively, 3.111 (95%CI 1.793 to 5.399, P<0.001) at 24 h, and 1.583 (95%CI 1.026 to 2.442, P=0.038) at 48 h. This indicated that as time progressed, the postoperative oxygenation status of lung transplant recipients was affected by the intraoperative transfusion volume. Furthermore, an RBC transfusion volume>975 mLhad a significant impact on patient oxygenation at 24 and 48 h postoperatively. Conclusion The volume of intraoperative RBC transfusion has a significant impact on the oxygenation status at 24 and 48 h postoperatively. Intraoperative RBC transfusion volume is associated with the occurrence of severe PGD after lung transplantation. Controlling the volume of RBC transfusion during lung transplantation may help reduce the incidence of severe PGD.