ObjectiveTo explore the vascular endothelial injury in male mice caused by exposure to polystyrene microplastics （PS-MPs） and the intervention effect of luteolin on vascular remodeling. Additionally， to investigate the mechanism through the oxidative system and metabolomics. MethodsThirty-two C57BL/6 mice （6-8 weeks old） were randomly divided into the saline group （saline group）， the 0.1 mg/kg PS-MPs exposure group （0.1PS-MPs group）， the 1 mg/kg PS-MPs exposure group （1PS-MPs group）， and the 1 mg/kg PS-MPs + luteolin treatment group （1PS-MPs + Lut group）， with 8 mice in each group. After 8 weeks of intervention， the body weight， blood pressure， aortic organ coefficient， and aortic histopathological changes of mice in each group were detected； the total cholesterol （TC）， triglyceride （TG）， and high-density lipoprotein cholesterol （HDL-C） lipid metabolism-related indicators in the aorta of mice were detected； the reactive oxygen species （ROS）， glutathione （GSH）， and malondialdehyde （MDA） oxidative stress-related indicators were detected； the endothelin （ET-1）， nitric oxide （NO）， vascular endothelial growth factor A （VEGF-A）， vascular cell adhesion molecule-1 （VCAM-1/CD106）， and intercellular adhesion molecule-1 （ICAM-1/CD54） endothelial function-related indicators and serum metabolomics were detected. ResultsCompared to the saline group， exposure to PS-MPs resulted in pathological thickening of the mouse aorta， increased aortic organ coefficient， and elevated blood pressure. Lipid metabolism-related indicators， including TC and TG， were elevated， while HDL-C was reduced， indicating lipid metabolism disorder in mice. Oxidative stress markers such as ROS and MDA increased， whereas GSH decreased， demonstrating oxidative damage. Vascular endothelial inflammation and injury markers， including ET-1， VEGF-A， VCAM-1， and ICAM-1， were upregulated， while the vasodilatory substance NO was downregulated， confirming endothelial injury. Furthermore， serum metabolomics results revealed that PS-MPs exposure induced endothelial damage by disrupting metabolic pathways such as the citrate cycle. Compared to the PS-MPs group， luteolin significantly reversed these effects， attenuating oxidative stress and lipid metabolism disorders， and effectively repairing endothelial injury. ConclusionPS-MPs induce vascular toxicity through oxidative stress and lipid metabolism. Luteolin effectively alleviates endothelial damage and vascular remodeling.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

AIM To compare the contents of caffeic acid,ferulic acid,narirutin,calycosin,glycyrrhizic acid and atractylenolide Ⅲ of modified Liujunzi Decoction(MLJZD)during small test,pilot test(500,1 500 L)and large production.METHODS The samples were taken after soaking for 60 min,boiling for 0,5,10,15,20,30 min in the first decoction,and boiling for 5,10,15,20 min in the second decoction,respectively,after which the HPLC fingerprints were established,the contents of active constituents were determined.RESULTS There were 6 common peaks in the HPLC fingerprints for small test and pilot test,while 5 common peaks were observable in the HPLC fingerprints for large production,along with the similarities of more than 0.980.During pilot tests at different time points,various active constituents demonstrated consistent content changing trends,whose total content was higher than those during small test and large production.CONCLUSION Process amplification exhibits a little influence on active constituent contents in MLJZD,which don't show increasing trends with the expansion of container and enhancement of dosage.

AIM To compare the contents of caffeic acid,ferulic acid,narirutin,calycosin,glycyrrhizic acid and atractylenolide Ⅲ of modified Liujunzi Decoction(MLJZD)during small test,pilot test(500,1 500 L)and large production.METHODS The samples were taken after soaking for 60 min,boiling for 0,5,10,15,20,30 min in the first decoction,and boiling for 5,10,15,20 min in the second decoction,respectively,after which the HPLC fingerprints were established,the contents of active constituents were determined.RESULTS There were 6 common peaks in the HPLC fingerprints for small test and pilot test,while 5 common peaks were observable in the HPLC fingerprints for large production,along with the similarities of more than 0.980.During pilot tests at different time points,various active constituents demonstrated consistent content changing trends,whose total content was higher than those during small test and large production.CONCLUSION Process amplification exhibits a little influence on active constituent contents in MLJZD,which don't show increasing trends with the expansion of container and enhancement of dosage.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

The 2024 National Education Work Conference pointed out that at the current juncture of the critical period for achieving the goals and tasks of the 14th Five-Year Plan,the implementation of the Education Powerhouse Construction Plan Outline should be taken as the main line of work,and building first-class disciplines is an crucial task for a higher education powerhouse.In 2022,forensic medicine was officially listed as a first-level discipline under the medical category,presenting an un-precedented historical opportunity for the development of forensic medicine.The forensic medicine dis-cipline of Southern Medical University comprehensively improves the quality of talent cultivation and facilitates the construction of first-class disciplines as its main direction.It aims to initiate and imple-ment a high-level faculty team building plan featuring"combining recruitment and cultivation,inter-disciplinary integration";make vigorous efforts to establish a first-level doctoral program,refine advan-tageous second-level disciplines and research directions;and establish an innovative research platform from a high starting point with deep integration.The discipline adheres to moral cultivation and the Five Domains of Education simultaneous development,to build a high-quality talent joint training model.Guided by the construction of the national legal system and industry needs,the discipline will enhance social service capabilities.The forensic medicine construction in our university will continue to contribute to the rule of law in China and educational power.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

ObjectiveTo investigate the relationship between mitochondrial DNA copy number (mtDNAcn) and cognitive dysfunction, and its mediating role between type 2 diabetes mellitus (T2DM) and cognitive dysfunction. MethodsA case-control study was conducted from May 2019 to April 2021 at the Shanghai Yangpu District Central Hospital, China. A total of 193 subjects were recruited and divided into two groups based on the Montreal Cognitive Assessment (MoCA): normal control (NC) group (n=95) and cognitive impairment group (n=98). The prevalence of T2DM was determined on the basis of medical history, while mtDNAcn in peripheral blood samples was quantified using realtime fluorescent quantitative polymerase chain reaction. ResultsUnivariate analyses revealed that the mean mtDNAcn in the cognitive impairment group was 0.76±0.37, significantly lower than that in the NC group (1.06±0.45) (P<0.05). Logistic regression analyses showed that higher mtDNAcn was associated with a reduced risk of cognitive impairment (OR=0.315, 95%CI: 0.125‒0.795). Additionaly, a statistically significant positive correlation was observed between mtDNAcn and the total MoCA score (r=0.381, P<0.01). Morever, T2DM history (OR=2.741, 95%CI: 1.002‒7.497) and elevated glycosylated hemoglobin (HbA1c) levels (OR=1.796, 95%CI: 1.190‒2.711) were identified as risk factors for cognitive impairment. Mediation analyses indicated that mtDNAcn served as a mediator between T2DM/HbA1c and the risk of cognitive impairment, with proportions of mediating effect of 9.04% and 9.18%, respectively. ConclusionPatients with mild and moderate cognitive impairment have significantly lower mtDNAcn than those with normal cognitive function. Reduced mtDNAcn is an influencing factor for cognitive dysfunction and may play a mediating role in the association between T2DM and mild to moderate cognitive impairment.

Objective: To investigate the abnormal fluctuation of coagulation function indicators in pediatric Burkitt lymphoma patients, and to analyze its correlation with disease progression and prognosis. Methods: The data of 172 children with Burkitt lymphoma in Children's Medical Center, Shanghai Jiao Tong University School of Medicine from January 2020 to December 2023 were retrospectively analyzed, and 120 healthy children were used as control group. Plasma prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen (Fib), International standardized ratio (INR), D-dimer (D-D), fibrinogen degradation products (FDP), and antithrombin (AT) were measured. Appropriate statistical methods were used to compare the data between two groups, and the Cox regression model was employed to analyze the influencing factors. A P-value <0.05 was considered statistically significant. Results: Levels of D-D, FDP, INR, and PT were significantly higher in children with Burkitt lymphoma than in the healthy controls [median (P25, P75) for the case group: 0.35 (0.13, 1.22), 3.10 (1.30, 10.20), 1.16 (1.06, 1.24), 12.60 (11.43, 13.50); median (P25, P75) for the healthy control group: 0.10 (0.07, 0.15), 0.60 (0.20, 1.08), 1.06 (1.02, 1.13), 11.50 (11.00, 12.30)](P<0.05). Levels of D-D, FDP, INR, PT, and TT were significantly elevated in children with recurrence compared to those without recurrence [median (P25, P75) for the recurrent group: 0.44 (0.16, 1.42), 3.85 (1.50, 12.25), 1.17 (1.08, 1.24), 12.70 (11.73, 13.50), 16.20 (14.80, 17.80); median (P25, P75) for the non-recurrent group: 0.21 (0.11, 0.69), 2.00 (1.00, 6.85), 1.11 (1.03, 1.24), 11.90 (11.10, 13.43), 15.20 (14.50, 16.40)](P<0.05). Levels of D-D, FDP in children with metastasis were significantly higher than those without metastasis [median (P25, P75) for the metastatic group: 0.51 (0.17, 1.84), 4.38 (1.70, 13.45); median (P25, P75) for the non-metastatic group: 0.20 (0.11, 0.39), 1.50 (1.00, 3.10)] (P<0.05). Levels of D-D and FDP were significantly higher in children with advanced stage than in those with early stage [median (P25, P75) for the high-stage group: 0.33 (0.14, 1.20), 3.10 (1.40, 10.23); median (P25, P75) for the low-stage group: 0.12 (0.08, 0.24), 0.90 (0.50, 2.50)] (P<0.05). Levels of D-D and FDP in high-risk children were significantly higher than those of low-risk [median (P25, P75) for the high-risk group: 0.28 (0.13, 1.01), 2.90 (1.15, 9.65); median (P25, P75) for the low-risk group: 0.12 (0.08, 0.17), 0.80 (0.43, 1.98)] (P<0.05). Levels of D-D, FDP, INR, and PT were significantly higher in children with poor prognosis than in those with favorable prognosis [median (P25, P75) for the poor prognosis group: 1.76 (0.80, 2.72), 13.45 (7.20, 25.30), 1.19 (1.12, 1.32), 12.85 (12.10, 14.35); median (P25, P75) for the favorable prognosis group: 0.23 (0.12, 0.52), 2.00 (1.00, 4.80), 1.14 (1.05, 1.23), 12.30 (11.40, 13.40)] (P<0.05). INR levels significantly increased with accumulating chemotherapy cycles [median (P25, P75) for one session: 1.09 (1.02, 1.20); two sessions: 1.31 (1.23, 1.38); three sessions: 1.79 (1.52, 2.41)] (P<0.05). Age, APTT, D-D, FDP, INR, PT, recurrence and metastasis had a significant effect on the survival of children with Burkitt lymphoma (P<0.05). Conclusion: Patients with Burkitt lymphoma exhibit coagulation disorders, which are influenced by recurrence, metastasis, clinical stage, risk stratification, and prognosis. In clinical practice, it is crucial to prioritize the monitoring of coagulation indicators to facilitate timely detection of coagulation dysfunction.