Objective To investigate the regulatory mechanism of transforming growth factor-β1 (TGF-β1) in different types of mitral valvular disease (MVD) with atrial fibrillation (AF). Methods From August 2011 to August 2012, patients with moderate to severe MVD accompanied by AF who required mitral valve replacement at the Department of Cardiovascular Surgery, West China Hospital, Sichuan University, were included. Based on echocardiographic results, patients were divided into two groups: a mitral regurgitation (MR) with AF (MR-AF) group and a mitral stenosis (MS) with AF (MS-AF) group. Left atrial tissue samples were collected during surgery. Techniques such as enzyme-linked immunosorbent assay, real-time fluorescence quantitative polymerase chain reaction, immunohistochemistry, and Western blotting were used to detect key molecules in the TGF-β1/JNK pathway. Results Sixteen patients were enrolled. There were 8 patients in the MR-AF group, including 5 males and 3 females, with an average age of (41.38±11.19) years; and 8 patients in the MS-AF group, including 6 males and 2 females, with an average age of (43.12±5.30) years. The left atrial volume load was higher in MR-AF patients, while the left atrial pressure load was higher in MS-AF patients. In MS-AF patients, the relative expression levels of MAPK9, JUN, CASP3, BAX, and BCL2 mRNA in left atrial tissues were significantly upregulated. The serum TGF-β1 protein level and the relative expression levels of p-JNK, p-c-Jun, and Caspase-3 proteins in the left atrial tissues of the MR-AF group were higher. Myocardial cell damage was more severe in the MS-AF group, and the protein expression level of Bcl-2 was higher. Conclusion Different MVD have distinct hemodynamic characteristics. The myocardium of the left atrium in MR-AF patients is more prone to apoptosis, possibly through the activation of the TGF-β1/JNK signaling pathway.

ObjectiveTo explore the changes in color， odor and chemical components during wine-processing of Chuanxiong Rhizoma（CR）， identify differential markers， and provide a basis for standardizing the process and establishing quality standards. MethodsFifteen batches of CR samples from 4 producing areas were collected. Colorimeter and electronic nose were used to detect the color changes and odor components of CR before and after wine-processing. Multivariate statistical methods including partial least squares-discriminant analysis（PLS-DA）， principal component analysis（PCA）， discriminant factor analysis（DFA） and Fisher discriminant analysis were applied to identify wine-processed CR at different processing stages and establish discriminant models， and differential components were screened out based on variable importance in the projection（VIP） value1. Then， high performance liquid chromatography（HPLC） was employed to detect the content changes of four components（ferulic acid， senkyunolide I， senkyunolide A and ligustilide） during the processing stages. ResultsThe differences of wine-processed CR at various stages were primarily reflected in color parameters L^*（brightness value）， a^*（red-green value） and b^*（yellow-blue value）. Based on chromaticity differences， the color reference ranges were established for moderately processed CR， including L^* of 46.75-48.24， a^* of 5.37-6.07 and b^* of 20.32-21.70. In odor analysis， DFA revealed significant differences among processing stages， and 11 odor markers were identified， with four differential markers（4-hydroxy-3-butylphthalide， isopropyl butyrate， L-limonene and 1-methoxyhexane） based on VIP values. HPLC results showed that there was no significant difference of the four components except for ligustilide in wine-processed CR at different stages. ConclusionThis study achieved rapid identification of wine-processed CR with different processing degrees by electronic sensory technology and differential component content detection， with discrimination accuracy rates of 92.4% and 93.272% for color and odor， respectively. This paper also established the reference ranges of main colorimetric parameters for wine-processed CR at different stages， and four differential components were screened out， providing a basis for standardizing the processing of wine-processed CR and establishing quality standards for this decoction pieces.

ObjectiveTo explore the changes in color， odor and chemical components during wine-processing of Chuanxiong Rhizoma（CR）， identify differential markers， and provide a basis for standardizing the process and establishing quality standards. MethodsFifteen batches of CR samples from 4 producing areas were collected. Colorimeter and electronic nose were used to detect the color changes and odor components of CR before and after wine-processing. Multivariate statistical methods including partial least squares-discriminant analysis（PLS-DA）， principal component analysis（PCA）， discriminant factor analysis（DFA） and Fisher discriminant analysis were applied to identify wine-processed CR at different processing stages and establish discriminant models， and differential components were screened out based on variable importance in the projection（VIP） value1. Then， high performance liquid chromatography（HPLC） was employed to detect the content changes of four components（ferulic acid， senkyunolide I， senkyunolide A and ligustilide） during the processing stages. ResultsThe differences of wine-processed CR at various stages were primarily reflected in color parameters L^*（brightness value）， a^*（red-green value） and b^*（yellow-blue value）. Based on chromaticity differences， the color reference ranges were established for moderately processed CR， including L^* of 46.75-48.24， a^* of 5.37-6.07 and b^* of 20.32-21.70. In odor analysis， DFA revealed significant differences among processing stages， and 11 odor markers were identified， with four differential markers（4-hydroxy-3-butylphthalide， isopropyl butyrate， L-limonene and 1-methoxyhexane） based on VIP values. HPLC results showed that there was no significant difference of the four components except for ligustilide in wine-processed CR at different stages. ConclusionThis study achieved rapid identification of wine-processed CR with different processing degrees by electronic sensory technology and differential component content detection， with discrimination accuracy rates of 92.4% and 93.272% for color and odor， respectively. This paper also established the reference ranges of main colorimetric parameters for wine-processed CR at different stages， and four differential components were screened out， providing a basis for standardizing the processing of wine-processed CR and establishing quality standards for this decoction pieces.

Background: Disorders of the blood-brain barrier (BBB) arising from diabetes mellitus are closely related to diabetic encephalopathy. Previous research has suggested that neuron-glia antigen 2 (NG2)-glia plays a key role in maintaining the integrity of the BBB. However, the mechanism by which NG2-glia regulates the diabetic BBB remains unclear. Methods: Type 2 diabetes mellitus (T2DM) db/db mice and db/m mice were used. Evans-Blue BBB permeability tests and transmission electron microscopy techniques were applied. Tight junction proteins were assessed by immunofluorescence and transmission electron microscopy. NG2-glia number and signaling pathways were evaluated by immunofluorescence. Detection of matrix metalloproteinase-9 (MMP-9) in serum was performed using enzyme-linked immunosorbent assay (ELISA). Results: In T2DM db/db mice, BBB permeability in the hippocampus significantly increased from 16 weeks of age, and the structure of tight junction proteins changed. The number of NG2-glia in the hippocampus of db/db mice increased around microvessels from 12 weeks of age. Concurrently, the expression of MMP-9 increased in the hippocampus with no change in serum. Sixteen- week-old db/db mice showed activation of the Wnt/β-catenin signaling in hippocampal NG2-glia. Treatment with XAV-939 improved structural and functional changes in the hippocampal BBB and reduced MMP-9 secretion by hippocampal NG2-glia in db/db mice. It was also found that the upregulation of β-catenin protein in NG2-glia in the hippocampus of 16-week-old db/db mice was significantly alleviated by treatment with XAV-939. Conclusion The results indicate that NG2-glia can lead to structural and functional disruption of the diabetic BBB by activating Wnt/β-catenin signaling, upregulating MMP-9, and degrading tight junction proteins.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

ObjectiveTo investigate the detection status of scoliosis and its influencing factors among primary and secondary school students in Jiangqiao Town in Jiading District of Shanghai, thereby providing evidence for the prevention and management of scoliosis in children and adolescents. MethodsA stratified cluster random sampling was conducted in March 2025. Three primary schools and two secondary schools in Jiangqiao Town were randomly selected; within each school, 3‒4 entire classes were randomly chosen. Screening was performed in accordance with the criteria specified in GB/T 16133‒2014 Screening for Abnormal Spinal Curvature in Children and Adolescents, and a self-designed structured questionnaire was administered to conduct face-to-face surveys (Cronbach’s α=0.730). ResultsA total of 772 valid questionnaires were collected on-site, representing a 100% response rate. The sample consisted of 413 males (53.50%) and 359 females (46.50%), including 385 primary school students (49.87%) and 387 secondary school students (50.13%). The detection rate of scoliosis in primary and secondary school students was 12.05%. The detection rates were 8.72% for males and 15.88% for females, with the female rate being significantly higher than the male rate (χ²=9.29, P=0.002). For primary and secondary school students, the detection rates were 6.75% and 17.31%, respectively, with the secondary school student rate being significantly higher (χ²=20.31, P<0.001). The results of univariate analysis revealed that students with sufficient sleep and standard sitting postures during reading/writing had a significantly lower scoliosis detection rate compared to those with insufficient sleep and non-standard sitting postures (χ²=5.90, P=0.015 and χ²=5.09, P=0.024). Multivariate logistic regression analyses revealed that the detection rate of scoliosis was significantly higher in females than in males (OR=1.846， 95%CI: 1.156‒2.984), and significantly higher in secondary school students than in primary school students (OR=2.722， 95%CI: 1.656‒4.472). ConclusionThe scoliosis detection rate among primary and secondary school students in Jiangqiao Town in Jiading District is relatively high. Females and secondary school students are key populations requiring targeted prevention and control efforts. It is imperative to strengthen health education on scoliosis, promote early screening and diagnosis, and implement timely targeted interventions.

Objective To explore the relationship between systemic immune inflammatory index and ferritin(SF)and the clinicopathologic features and prognosis of gastric cancer(GC).Methods A retrospective analysis was conducted on 152 gastric cancer patients who underwent D2 gastrectomy at the Radiation Oncology Department of Qingbaijiang District People's Hospital in Chengdu from January 2017 to December 2020.Neutrophil count was divided by lymphocyte count to calculate Neutrophil to lymphocyte ratio(NLR).The SF level in plasma was evaluated by ELISA kit.According to the results of multivariate analysis,a new prognosis prediction system including NLR-SF score(NSS)was established.Results Multivariate Cox regression analysis showed that NLR(HR=1.053,95%CI=1.014～1.094,P=0.007),tumor grade(HR=1.944,95%CI=1.279～2.955,P=0.002)and SF(HR=1.005,95%CI=1.002～1.008,P=0.002)were independent factors affecting the prognosis of GC patients.ROC analysis showed that when the cutoff value of SF was 215.5,the AUC of predicting the death of GC patients was 0.800(95%CI=0.731～0.869),the sensitivity was 68.5%,and the specificity was 86.7%.When the cutoff value of NLR was 3.36,the AUC of predicting the death of GC patients was 0.869(95%CI=0.810～0.928),the sensitivity was 81.5%,and the specificity was 91.7%.Higher NSS was significantly correlated with the number of lymph node metastasis>3 cases,the number of deaths,the increase of neutrophil,platelet,SF,NLR and PLR levels(P<0.05),and the decrease of lymphocytes(P<0.05).Kaplan-Meier survival curve analysis showed that the higher the NSS,the shorter the survival time(χ2=75.168,P<0.001).ROC analysis showed that the AUC of NSS in predicting the death of GC patients was 0.902(95%CI=0.852～0.952),the sensitivity was 90.2%,and the specificity was 80.0%.Conclusions This study confirms that NLR and SF are independent prognostic factors of GC patients,and the NSS constructed by combining them is of great value in predicting the overall postoperative survival.

Objective To explore the relationship between serum S100 calcium-binding protein(S100)A4,S100A12 and the infection type and prognosis of neonatal infectious pneumonia(NIP).Methods A total of 300 children with NIP admitted to the Neijiang Second People's Hospital from January 2021 to March 2024 were selected and divided into the bacterial infection group(214 cases)and the non-bacterial infection group(86 cases)according to the types of pathogenic bacteria.Another 150 healthy newborns in the same hospital during the same period were selected as the control group.The levels of serum S100A4 and S100A12 were de-tected by enzyme-linked immunosorbent assay.Pearson correlation analysis was conducted to examine the cor-relations between serum S100A4,S100A12 and procalcitonin(PCT),white blood cell count(WBC),albumin(Alb),and platelet count(PLT).The receiver operating characteristic(ROC)curve was used to evaluate the differential value of serum S100A4,S100A12,PCT,WBC,Alb,and PLT alone and in combination for NIP bac-terial infection.According to the prognosis,children with NIP were divided into the poor prognosis group(63 cases)and the good prognosis group(237 cases).Multivariate Logistic regression model was used to analyze the influencing factors of poor prognosis in children with NIP,and ROC curve was used to analyze the value of each factor in predicting poor prognosis in children with NIP.Results The levels of serum S100A4,S100A12,PCT,WBC,and PLT in the bacterial infection group were higher than those in the non-bacterial infection group and the control group,while Alb was lower than that in the non-bacterial infection group and the control group,the differences were statistically significant(P<0.05).Pearson correlation analysis showed that serum S100A4 and S100A12 in children with NIP were positively correlated with PCT,WBC and PLT(P<0.05),and negatively correlated with Alb(P<0.05).The results of ROC curve analysis showed that the area under the curve(AUC)of serum S100A4 and S100A12 in differentiating NIP infection types was slightly lower than that of PCT,WBC,Alb,and PLT in differentiating NIP infection types.The results of multivariate Logistic re-gression analysis showed that elevated S100A4,elevated S100A12,elevated PCT,bacterial infection,and lung consolidation were independent risk factors for poor prognosis in children with NIP(P<0.05).The AUC of bacterial infection,lung consolidation,PCT,S100A4,and S100A12 for predicting the poor prognosis of chil-dren with NIP was 0.903.It was greater than the AUC predicted separately by bacterial infection,lung consol-idation,PCT,S100A4,and S100A12 levels(Z=9.989,9.460,5.514,4.084,4.376,P<0.001).Conclusion The combination of serum S100A4 and S100A12 with traditional markers has certain discrimina-tory value for the infection types of NIP,and the levels of serum S100A4 and S100A12 are related to the prog-nosis of NIP.

With the widespread application of information technology in the field of Traditional Chinese Medicine(TCM),the data in the TCM domain is becoming increasingly rich.The emergence of data-driven research in TCM has utilized knowledge graphs for the management,analysis,and presentation of TCM data,becoming a crucial method for the inheritance and innovation of Traditional Chinese Medicine.Therefore,reasoning based on TCM knowledge graphs has become a hot topic in contemporary TCM research.In order to better utilize knowledge graph reasoning technology to promote innovation and development in TCM,this article,after providing an overview of TCM knowledge graph reasoning,focuses on the development of knowledge graph reasoning in TCM and its applications from three perspectives:logic rule-based,distributed representation,and neural network-based methods.Finally,the article summarizes the advantages and disadvantages of knowledge reasoning methods and provides prospects for research and applications in TCM knowledge graph reasoning,including studies on interpretability,temporal knowledge graphs,and the fusion of multimodal information.

Objective:This multicenter retrospective study aimed to analyze the clinicopathological features of duodenal adenocarcinoma (DA) and identify prognostic factors for postoperative survival.Methods:Demographic characteristics, clinicopathological features, treatment outcomes and survival of DA patients undergoing surgical treatment at 18 Chinese medical centers from January 2012 to December 2023 were retrospectively analyzed.Results:Among the 2 056 DA patients included, 46.8% (963) had extra-ampullary DA (EA-DA), and 53.2% (1 093) had peri-ampullary DA (PA-DA). The 1-, 3-, and 5-year overall survival (OS) rates for patients who underwent radical surgery were 93.2%, 71.0%, and 57.2%, respectively. The median overall survival was 76 months, and the median progression-free survival (PFS) was 65 months. No differences in survival were observed between the laparotomy group and minimally invasive surgery (MIS) group either before or after propensity score matching (OS: 76 vs. 75 months before PSM, P=0.986; OS: 75 vs. 75 months after PSM, P=0.602). Furthermore, there were no significant differences between-group in operation time and postoperative complications ( P＞0.05). The MIS group experienced less intraoperative blood loss and shorter hospital stays. The multivariate Cox regression analysis revealed that advanced age ( HR=1.43,95% CI:1.18-1.73), elevated carbohydrate antigen 19-9 levels ( HR=1.24,95% CI:1.02-1.51), perineural invasion ( HR=1.44,95% CI:1.14-1.81), vascular invasion ( HR=1.35,95% CI:1.07-1.71), advanced T stage (T3-4 vs. T1-2: HR=1.86,95% CI:1.49-2.31), regional lymph node metastasis ( HR=1.93,95% CI:1.58-2.36), preoperative biliary drainage ( HR=1.26,95% CI:1.04-1.53), intraoperative blood loss ( HR=1.34,95% CI:1.11-1.62), clinically significant postoperative pancreatic fistulas ( HR=1.53,95% CI:1.12-2.09), and postoperative hemorrhage ( HR=1.62,95% CI:1.14-2.29) were independent risk factors for poor prognosis after surgery (all P＜0.05). Conclusions:Radical surgery is associated with favorable overall survival among DA patients, and no difference in survival is observed between EA-DA and PA-DA patients. MIS is a reliable alternative for DA treatment.