ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

Objective To investigate the protective effect and underlying mechanism of human umbilical cord mesenchymal stem cell-derived exosomes (hucMSC-Exo) on renal ischemia-reperfusion injury (IRI). Methods hucMSC-Exos were isolated and characterized. A mouse renal IRI model was established and the animals were divided into Sham, IRI, IRI+hucMSC-Exo, IRI+hucMSC-Exo+JY-2 and Sham+JY-2 groups. Serum creatinine (Scr) and blood urea nitrogen (BUN) were measured. Hematoxylin-eosin (HE) staining was used to evaluate renal histopathology. Enzyme-linked immune absorbent assay was performed to determine serum interleukin (IL)-1β and IL-18 levels. Western blotting was used to detect the expression of activating transcription factor 3 (ATF3), Toll-like receptor 4 (TLR4), nuclear factor (NF)-κB, NOD-like receptor protein 3 (NLRP3), cysteineyl aspartate specific proteinase (Caspase)-1 p20 and Gasdermin D(GSDMD). Real-time fluorescent quantitative polymerase chain reaction was employed to measure ATF3, TLR4 and NF-κB messenger RNA (mRNA). Immunohistochemistry was conducted to examine NLRP3, Caspase-1 p20 and GSDMD. An in vitro hypoxia/reoxygenation (H/R) model was established in HK-2 cells and divided into Control, H/R, H/R+hucMSC-Exo, H/R+hucMSC-Exo+JY-2 and Control+JY-2 groups. Western blotting was used to detect the expression of ATF3, TLR4 and NF-κB. Real-time fluorescent quantitative polymerase chain reaction was used to measure NLRP3, GSDMD and Caspase-1 mRNA. Results HucMSC-Exos were successfully isolated and identified. Compared with the Sham group, the IRI group exhibited elevated Scr and BUN, higher tubular injury scores, increased protein expression levels of ATF3, TLR4, NF-κB p65, NLRP3, Caspase-1 p20 and GSDMD, and raised mRNA expression levels of ATF3, TLR4, NF-κB. Compared with the IRI group, the IRI+hucMSC-Exo group showed decreased Scr and BUN, lower tubular injury scores, up-regulated ATF3 protein and mRNA, down-regulated TLR4, NF-κB p65, NLRP3, Caspase-1 p20 and GSDMD protein, and declined TLR4 and NF-κB mRNA. Compared with the IRI+hucMSC-Exo group, the IRI+hucMSC-Exo+JY-2 group exhibited increased Scr and BUN levels, elevated renal tubular injury scores, decreased ATF3 protein expression levels, elevated protein expression levels of TLR4, NF-κB p65, NLRP3, Caspase-1 p20, and GSDMD, decreased ATF3 mRNA expression levels, and elevated mRNA expression levels of TLR4 and NF-κB. (all P < 0.05). Compared with the Control group, the expression levels of ATF3, TLR4 and NF-κB p65 proteins were increased in the H/R group, and the expression levels of NLRP3, Caspase-1 and GSDMD mRNA were increased. Compared with the H/R group, the expression level of ATF3 protein was increased, the expression levels of TLR4 and NF-κB p65 proteins were decreased, and the expression levels of NLRP3, Caspase-1 and GSDMD mRNA were decreased in the H/R+hucMSC-Exo group. Compared with the H/R+hucMSC-Exo group, the expression level of ATF3 protein was decreased, the expression levels of TLR4 and NF-κB p65 proteins were increased, and the expression levels of NLRP3, Caspase-1 and GSDMD mRNA were increased in the H/R+hucMSC-Exo+JY-2 group (all P < 0.05). Conclusions HucMSC-Exos alleviate renal IRI by up-regulating ATF3, thereby negatively regulating the TLR4/NF-κB signaling pathway and subsequently inhibiting pyroptosis.

Objective To analyze the main causes and risk factors of unplanned reoperation after liver transplantation. Methods The clinical data of 242 liver transplant recipients in the First Affiliated Hospital of Anhui Medical University from January 2015 to December 2024 were retrospectively analyzed. According to whether unplanned reoperation was performed during the same hospitalization after surgery, the recipients were divided into the reoperation group (n=36) and the non-reoperation group (n=206). The preoperative, intraoperative and postoperative data of the two groups, as well as donor and graft-related data, were compared to analyze the risk factors of unplanned reoperation after liver transplantation and the survival status of the two groups. Results Among the 242 liver transplant recipients, 36 underwent unplanned reoperations, with a total of 54 procedures including various laparotomies, endoscopic and interventional surgeries, among which there were 20 laparotomies, 18 endoscopic surgeries and 16 interventional surgeries. The most common cause of unplanned reoperation was biliary complications (20 times), followed by vascular complications (17 times). Compared with the non-reoperation group, the reoperation group had longer graft cold ischemia time, higher postoperative fatality rate of recipients, longer length of stay in the intensive care unit and postoperative hospital stay, and higher total hospitalization costs (all P<0.05). The incidence of unplanned reoperation was higher in recipients who underwent split liver transplantation (P<0.05). Multivariate analysis showed that intraoperative blood loss ≥1 000 mL, positive culture of graft perfusate and split liver transplantation were independent risk factors for unplanned reoperation (all P<0.05). The postoperative 7-day, 1-month, 3-month and 6-month survival rates of recipients in the reoperation group and the non-reoperation group were 100% vs. 98.1%, 88.9% vs. 94.2%, 69.4% vs. 90.8% and 66.7% vs. 90.8%, respectively, and the postoperative survival rate of recipients in the reoperation group was lower than that in the non-reoperation group (P<0.05). Conclusions The main causes of unplanned reoperation after liver transplantation are biliary complications, vascular complications, abdominal incision infection and intra-abdominal hemorrhage. Intraoperative massive blood loss, positive culture of graft perfusate and split liver transplantation are the risk factors associated with unplanned reoperation after liver transplantation.

Objective To construct prostate cancer(PCa)prediction models based on machine learning algorithms, so as to improve the accuracy of early diagnosis of PCa. Methods A retrospective analysis was performed on the clinical data of 504 patients who underwent prostate biopsy at our hospital during Jan. 2020 and Nov. 2024. Patients' age, body mass index(BMI), history of hypertension, diabetes and smoking, total prostate-specific antigen(tPSA), free prostate-specific antigen(fPSA), f/tPSA, prostate volume(PV), neutrophil count, lymphocyte count, neutrophil-to-lymphocyte ratio(NLR), Prostate Imaging Reporting and Data System(PI-RADS)score, digital rectal examination(DRE)results, and pathological findings were collected. The patients were divided into the training and testing sets at a ratio of 7:3. Ten early diagnosis prediction models of PCa were constructed using 10 supervised machine learning algorithms. Model performance was evaluated and validated using metrics including area under the receiver operating characteristic curve(AUC), accuracy, sensitivity, specificity, calibration curves, and decision curve analysis(DCA). SHAP analysis was used to interpret the models, and to clarify the importance of each feature and the basis for model decisions. Results All models showed good predictive value, with the gradient boosting machine(GBM)model performing the best(AUC=0.905, accuracy=84.1%, sensitivity=90.2%, specificity=80.0%). Calibration curves indicated good calibration and fitting of the GBM model, while DCA demonstrated favorable clinical net benefits. SHAP analysis identified the most significant features affecting PCa occurrence in descending order:tPSA, f/tPSA, PIRADS score, PV, age, and DRE. Conclusion The GBM model exhibits the optimal performance among the 10 models. The importance of features for predicting the occurrence of PCa, from the highest to the lowest, is as follows:tPSA, f/tPSA, PIRADS score, PV, age, and DRE.

Objective:To elucidate the causal association between gut microbiota and osteoporosis, we conducted a two-sample Mendelian randomization(MR)analysis to evaluate the causality between gut microbiota and osteoporosis.Methods:We assessed genome-wide association study (GWAS)summary statistics for gut microbiota and osteoporosis in older patients to perform the MR analysis.Independent single nucleotide polymorphisms closely associated with 211 gut bacterial taxa were identified as instrumental variables.The summary statistic data for osteoporosis were obtained from the latest release from the FinnGen consortium as the outcome of interest.Two-sample MR was performed to evaluate the causal effect of gut microbiota on osteoporosis, including the inverse-variance-weighted(IVW)method, weighted median method, MR-Egger, mode-based estimation, and MR-PRESSO.A series of sensitivity analyses were conducted to validate the robustness of the results.The robustness of the estimation was assessed through a series of sensitivity analyses, including Cochran's Q test, MR-Egger intercept analysis, leave-one-out analysis, and funnel plot to evaluate the causal association. Results:The population primarily consisted of individuals from Europe, with a total sample size of 7 300, including 1 762 males and 5 538 females, and average ages of 65.6 years for males and 67.8 years for females, respectively.The mean ages of the 5 538 patients were 65.6 years for males and 67.8 years for females, respectively.Through MR analysis in this study, 10 intestinal flora(comprising 1 class, 7 genera, and 2 orders)were identified as being associated with senile osteoporosis.Notably, the phylum Firmicutes( OR=1.324, P=0.019), Clostridium difficile( OR=1.274, P=0.038), fecal coliforms( OR=1.565, P=0.009), Verrucomicrobium( OR=1.231, P=0.033), and Selenomonas( OR=1.324, P=0.019)may serve as risk factors for senile osteoporosis.Conversely, Coprococcus( OR=0.620, P=0.024), Haemophilus( OR=0.815, P=0.016), Prevotella( OR=0.813, P=0.027), Sellimonas( OR=0.858, P=0.034), and RF9( OR=0.821, P=0.021)may function as protective factors against senile osteoporosis. Conclusions:This study suggests a causal relationship between the Firmicutes phylum and its nine subgroups and senile osteoporosis, thereby providing new insights into the mechanisms by which gut microbiota mediate senile osteoporosis and confirming the significant role of gut microbiota in this condition.

Objective: To investigate the efficacy and safety of intelligent temperature-pressure-controlled flexible ureteroscopy combined with negative-pressure suction sheath lithotripsy in the treatment of upper urinary tract stones ≤2.5 cm. Methods: The clinical data of 225 patients with ≤2.5 cm upper urinary tract stones treated with this surgical method in our department during Aug. 2023 and Jul. 2024 were retrospectively analyzed. The patients were divided into the dual-control group (n=36) and conventional group (n=189) according to whether or not the intelligent temperature and pressure control device was used during operation. In the dual-control group，the intraoperative temperature and pressure in the renal pelvis were monitored and controlled in real time by the temperature and pressure sensors distributed at the end of the ureteral soft lens. The perioperative parameters，stone-removal rate，complication rate and renal function were compared between the two groups. Results: All operations were successfully completed in both groups. The postoperative procalcitonin (PCT) level [(22.75±5.85) ng/L vs. (29.08±6.60) ng/L，P=0.001]，difference in the white blood cell (WBC) level [(0.24±2.12)×10 cells/L vs. (1.19±2.17)×10 cells/L，P=0.016]，incidence of fever (2.8% vs. 16.9%，P=0.028) and overall complication rate (5.6% vs. 19.6%，P=0.042) were significantly lower in the dual-control group than in the conventional group，while the stone-clearance rate was slightly higher (88.9% vs. 82.5%，P=0.346)，with no significant difference. Conclusion: For upper urinary tract stones ≤2.5 cm，intelligent temperature-pressure-controlled ureteroscopy combined with negative-pressure suction sheath lithotripsy has a satisfactory stone-removal rate and a low rate of complications，which is worthy of clinical promotion.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

OBJECTIVE: To investigate the regulatory effect of electroacupuncture (EA) at "Neiguan" (PC6) on mitochondrial autophagy in rats with myocardial ischemia-reperfusion injury (MIRI) at different phases (ischemia and reperfusion phases), and to explore the bidirectional regulatory effects of EA at "Neiguan" (PC6) and its potential mechanism. METHODS: Forty-five male SD rats were randomly divided into 6 groups according to the random number table method, namely, sham-operation group (n=9), model-A group (n=6), model-B group (n=9), EA-A1 group (n=6), EA-B1 group (n=6), and EA-B2 group (n=9). Except the rats in the sham-operation group, the MIRI model was established in the other groups with the physical ligation and tube pushing method. In the model-A group, the samples were collected directly after ligation, and in the model-B group, the samples were collected after ligation and reperfusion. In the EA-A1 group, EA was delivered while the ligation was performed, and afterwards, the samples were collected. In the EA-B1 group, while the ligation was performed, EA was operated at the same time, and after reperfusion, the samples were collected. In the EA-B2 group, during ligation and the opening of the left anterior descending branch of the coronary artery, EA was delivered, and after reperfusion, the samples were collected. EA was performed at bilateral "Neiguan" (PC6), with a disperse-dense wave, a frequency of 2 Hz/100 Hz, a current of 1 mA, and a duration of 30 min. HE staining was employed to observe the morphology of cardiomyocytes, TUNEL was adopted to detect the apoptosis of cardiomyocytes, transcriptome sequencing was to detect the differentially expressed genes in the left ventricle, JC-1 flow cytometry was to detect the mitochondrial membrane potential (MMP) of cardiomyocytes, Western blot was to detect the protein expression of phosphatase and tensin homolog-induced kinase 1 (Pink1), Parkin and p62 in the left ventricle of rats, and ELISA was to detect the levels of serum creatine kinase isoenzyme (CK-MB) and cardiac troponin I (cTn-I) in the rats. RESULTS: Compared with the sham-operation group, the cardiomyocytes of rats in the model-B group were severely damaged, with disordered arrangement, unclear boundaries, broken muscle fibers, edema and loose distribution; and the cardiomyocytes in the EA-B2 group were slightly damaged, the cell structure was partially unclear, the cells were arranged more regularly, and the intact cardiomyocytes were visible. Compared with the sham-operation group, the apoptosis of cardiomyocytes increased in the model-B group (P<0.001); and when compared with the model-B group, the apoptosis alleviated in the EA-B2 group (P<0.001). The differentially expressed genes among the EA-B2 group, the sham-operation group and the model-B group were closely related to cell autophagy and mitochondrial autophagy. Compared with the sham-operation group, MMP of cardiomyocytes was reduced (P<0.001), the protein expression of Pink1, Parkin, and p62 of the left ventricle and the levels of serum CK-MB and cTn-I were elevated in the model B group (P<0.001). In comparison with model-A group, the MMP of cardiomyocytes and the levels of serum CK-MB and cTn-I were reduced (P<0.001, P<0.05), and the protein expression of Pink1 in the left ventricle rose in the EA-A1 group (P<0.01). Compared with the model-B group, MMP of cardiomyocytes increased (P<0.001), the protein expression of Pink1, Parkin, and p62 of the left ventricle, and the levels of serum CK-MB and cTn-I decreased (P<0.001) in the EA-B1 group and the EA-B2 group. When compared with the EA-A1 group, MMP of cardiomyocytes increased (P<0.001), and the protein expression of Pink1, Parkin, and p62 of the left ventricle, and the levels of serum CK-MB and cTn-I decreased in the EA-B1 group (P<0.01). CONCLUSION EA at "Neiguan" (PC6) can ameliorate MIRI in rats, which may be achieved through the Pink1/Parkin-mediated mitochondrial autophagy pathway. EA can alleviate myocardial injury by enhancing mitochondrial autophagy at the ischemia phase, and it can reduce reperfusion injury by weakening mitochondrial autophagy at the reperfusion phase.
Animals ; Electroacupuncture ; Male ; Myocardial Reperfusion Injury/metabolism* ; Rats, Sprague-Dawley ; Rats ; Acupuncture Points ; Autophagy ; Humans ; Mitochondria/genetics*

BackgroundNon-suicidal self-injury （NSSI） behaviors have become a serious global public health issue.The detection rate of NSSI behaviors among college students in China ranges from 9.8% to 13.53%. Integrated theoretical models suggest that distal family risk factors influence NSSI behaviors through emotional regulation mechanisms. However， existing researches have predominantly focused on single family risks， leaving the relationship between cumulative family risks and NSSI behaviors， as well as the underlying pathways， remain unclear. ObjectiveTo explore the effects of cumulative family risk on NSSI behaviors among college students， analyze the chain mediating roles of emotional regulation difficulties and depression， and examine the moderating effect of gender， so as to provide references for targeted interventions for NSSI behaviors in college students. MethodsOn March 1， 2024， a cluster sampling method was employed to select 518 college students from two universities in Heilongjiang Province. Assessments were conducted using Chinese version of the Childhood Trauma Questionnaire （CTQ）， the Difficulties in Emotion Regulation Scale （DERS）， the Patient Health Questionnaire Depression Scale-9 item （PHQ-9） and the Adolescent Self-Injury Questionnaire. Logistic regression analysis was used to examine the impact of cumulative family risk factors on NSSI behaviors among college students. Model 6 in Process 4.1 was applied to test the chain mediating roles of emotional regulation difficulties and depression in the relationship between cumulative family risk and NSSI behaviors， while model 83 was utilized to analyze the moderating effects of gender on the path "cumulative family risk → emotion regulation difficulties". ResultsA total of 475 （91.70%） college students completed valid questionnaires. Logistic regression analysis revealed that childhood abuse （OR=2.561， 95% CI： 1.566-2.561）， non-parental family structure （OR=2.108， 95% CI：1.102-4.029） and left-behind experience （OR=2.356， 95% CI： 1.021-5.439） were risk factors for NSSI behaviors among college students. Cumulative family risk positively predicted NSSI behaviors （β=0.345，95% CI：1.059-4.286， P<0.01）， and this relationship was mediated by a chain pathway involving emotional regulation difficulties （β=0.136，95% CI： 0.882-4.681， P<0.05） and depression （β=0.160， 95% CI： 0.316-1.073， P<0.01）. Gender moderated the relationship between cumulative family risk and emotional regulation difficulties （β=0.103， 95% CI： 1.567-8.316， P<0.01）， with cumulative family risk significantly predicting emotional regulation difficulties in female students （β=0.374， 95% CI： 0.099-0.084， P<0.01）. ConclusionCumulative family risk can directly influence college students' NSSI behaviors， and may also indirectly affect NSSI behaviors through the mediating roles of emotional regulation difficulties and depression. The path "cumulative family risk → emotional regulation difficulties" in this mediating model is moderated by gender.［Funded by Heilongjiang Philosophy and Social Sciences Research Planning Project （number， 24SHB007）］

Xiaoyao Powder has pharmacological action such as neuroprotection, anti-tumor, anti-depression, liver protection, regulation of intestinal flora, anti-fatigue and so on. Based on the five aspects of quality transfer and traceability, component measurability, component effectiveness, component specificity and compound compatibility environment, the quality marker (Q-marker) of Xiaoyao Powder was predicted and analyzed. It was considered that paeoniflorin, atractylenolide Ⅰ, atractylenolid Ⅱ, atractylenolide Ⅲ, liquiritin,glycyrrhizic acid, Saikosaponin A, Saikosaponin D, ferulic acid, Z-ligustilide, pachymic acid, Menthol,6-gingerol 8-gingerol and 10-gingerol have strong measurability and can be used as Q-marker of Xiaoyao Powder.