ObjectiveTo study the pharmacological substances and mechanisms through which sesquiterpene ZH-13 from Aquilariae Lignum Resinatum improves neuroinflammation. MethodsBV-2 microglial cells were stimulated with lipopolysaccharide （LPS） to induce neuroinflammation. The cells were divided into the normal group， the model group， and the ZH-13 low- and high-dose treatment groups （10， 20 μmol·L^-1）. The model group was treated with 1 μmol·L^-1 LPS. Cell viability was assessed using the cell proliferation and activity assay （CCK-8 kit）. Nitric oxide （NO） release in the cell supernatant was measured using a nitric oxide kit （Griess method）. The mRNA expression levels of interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， inducible nitric oxide synthase （iNOS）， and interleukin-6 （IL-6） were detected by real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. The phosphorylation of mitogen-activated protein kinase （MAPK） pathway proteins was assessed by Western blot. ResultsCompared with the model group， ZH-13 dose-dependently reduced NO release from BV-2 cells under LPS stimulation （P<0.05， P<0.01）. In the 20 μmol·L^-1 ZH-13 treatment group， the mRNA expression levels of IL-1β， TNF-α， iNOS， and IL-6 were significantly reduced compared to the model group （P<0.05， P<0.01）. In both the low- and high-dose ZH-13 groups， the expression of the inflammatory factor TNF-α and the phosphorylation of c-Jun N-terminal kinase （JNK） in the upstream MAPK pathway were significantly reduced （P<0.05）. After stimulation with the JNK agonist anisomycin （Ani）， both low- and high-dose ZH-13 treatment groups showed reduced phosphorylation of JNK proteins compared to the Ani-treated group （P<0.01）. ConclusionThe sesquiterpene compound ZH-13 from Aquilariae Lignum Resinatum significantly ameliorates LPS-induced neuroinflammatory responses in BV-2 cells by inhibiting excessive JNK phosphorylation and reducing TNF-α expression. These findings elucidate the pharmacological substances and mechanisms underlying the sedative and calming effects of Aquilariae Lignum Resinatum.

Extended reality(XR)technology includes virtual reality(VR),augmented reality(AR)and mixed reality(MR)Combining virtual environments with physical world,the extended reality(XR)technology has great potential in rehabilitation of patients with stroke.This article reviews the intervention effects of XR technology on the functions of limb,swallowing,speech and cognition and psychological outcomes in patients with stroke.Based on this review,issues in application of XR are identified and targeted solutions are proposed,thereby offering a guidance for application of XR technology in stroke rehabilitation in China.

Objective:To investigate mental health literacy and advance care planning(ACP)condition,their influencing fac-tors,and their correlation in elderly patients with coronary heart disease(CHD).Methods:General data of 500 elderly CHD patients admitted in the Second Affiliated Hospital of Chinese PLA Air Force Military Medical University between January 2020 and December 2021 were collected.Mental health literacy and ACP condition were assessed.Multivariate linear regres-sion was used to analyze their influencing factors,and Pearson method was used to analyze their association.Results:Total score of Multicomponent Mental Health Literacy(MHL)was(10.78±2.57)points,and total score of Advance Care Plan-ning Readiness Scale(ACPRS)was(71.41±4.84)points in the 500 elderly CHD patients.Multivariate linear regression a-nalysis indicated that level of disease uncertainty had negative impact on MHL score,presence of spouse and trust in medical care had positive impact on MHL score(P＜0.05 or＜0.01);number of complications had negative impact on ACPR score,while presence of spouse and family mean monthly income had positive impact on ACPRS score(P＜0.05 or＜0.01).Pearson correlation analysis indicated that MHL score was positively correlated with ACPRS score(r=0.476,P＜0.001).Conclusion:Both mental health literacy and ACP status need to be improved in elderly CHD patients.They are posi-tively correlated with each other.Presence of spouse,number of complications and trust in medical care are the important influencing factors.Therefore,medical staff can take targeted measures to improve ACP readiness and mental health quality.

Objective:This study aims to explore the rehabilitation effect of continuous rehabilitation management based on Internet thinking on patients with coronary heart disease(CHD)after percutaneous coronary intervention(PCI).Methods:This randomized controlled study enrolled 100 CHD patients admitted in Second Affiliated Hospi-tal of Chinese PLA Air Force Military Medical University between October 2020 and December 2021.They were di-vided into control group(n=50)and intervention group(n=50).Patients in control group received routine reha-bilitation nursing mode,compared to those in intervention group applying"Internet+"continuous rehabilitation nursing intervention program,both groups were intervened for 3 months.Cardiac function,cardiopulmonary exer-cise test indexes,depression,medication compliance,quality of life and incidence of adverse cardiovascular events within 1-year follow-up were compared between two groups.Results:Compared with patients in control group after 3 months,those in intervention group had significant higher oxygen uptake at anaerobic threshold(VO2@AT)[(11.75±0.39)ml·kg-1·min-1 vs.(10.17±0.76)ml·kg-1·min-1],peak oxygen uptake(Peak VO2)[(17.87±0.72)ml·kg-1·min-1 vs.(16.66±0.24)ml·kg-1·min-1],left ventricular ejection fraction(LVEF)[(51.15±2.42)％vs.(44.09±1.94)％],scores of Morisky Medication Adherence Scale(MMAS-8)[(5.29±0.30)points vs.(4.11±0.27)points]and Seattle Angina Questionnaire(SAQ)[(85.50±4.37)points vs.(73.27±2.53)points],and significant lower left ventricular end-diastolic diameter(LVEDd)[(40.51±0.41)mm vs.(46.64±0.99)mm],score of Patient Health Questionnaire-9(PHQ-9)[(7.67±0.85)points vs.(9.66±1.43)points]and total incidence of adverse cardiovascular events within 1-year follow-up(4.00％vs.16.00％)(P＜0.05 or＜0.01).Conclusion:Internet continuous rehabilitation intervention could improve car-diopulmonary exercise capacity and cardiac function,help to improve their quality of life and relieve depression,and reduce the risk of adverse cardiovascular events in CHD patients after PCI.

Objective:To investigate the predictive value of microRNA-1(miR-1),brain natriuretic peptide(BNP)and ischemia-modified albumin(IMA)for unstable angina pectoris(UAP).Methods:We enrolled 237 UAP patients admitted to Xining Second People's Hospital between June 2018 and December 2020 as UAP group.Another 86 healthy subjects undergoing physical examination simultaneously were enrolled as control group.MiR-1 expression,BNP and IMA levels were measured.General data between UAP group and control group,serum miR-1 expression,BNP and IMA levels among different Braunwald class and prognosis were compared.Receiver operat-ing characteristic(ROC)curve was employed to analyze predictive value of miR-1,BNP,IMA and their combina-tion for prognosis in UAP patients.Results:Compared with participants in the control group,those in UAP group had significant higher serum miR-1 expression[(1.80±0.59)vs.(0.93±0.11)],BNP[(107.34±37.46)pg/ml vs.(52.31±10.64)pg/ml]and IMA[(79.76±19.29)g/L vs.(53.16±6.43)g/L](P＜0.001 all).As Braun-wald class increased(class Ⅰ～Ⅲ),serum miR-1 expression,BNP and IMA levels elevated(P＜0.001 all).Com-pared with patients in favorable outcome group,those in unfavorable outcome group had significant higher serum miR-1 expression[(2.31±0.54)vs.(1.53±0.41)],BNP[(147.03±29.63)pg/ml vs.(85.95±19.46)pg/ml]and IMA[(97.24±15.35)g/L vs.(70.35±13.88)g/L](P＜0.001 all).ROC curve indicated that AUC of com-bined detection for predicting unfavorable outcome in UAP patients was 0.925(95％CI 0.884～0.955),which was significantly higher than miR-1(AUC=0.880,95％CI 0.831～0.918),BNP(AUC=0.863,95％CI 0.813～0.904)and IMA(AUC=0.900,95％CI 0.854～0.935)alone(Z=2.884,3.130,2.090,P＜0.05 or＜0.01).Conclusion:MiR-1 expression,BNP and IMA levels significantly increase in UAP patients,and they are associated with the severity of disease.Combined detection has good predictive value for unfavorable outcome in UAP pa-tients.

Objective:To discern the association between autism-like behaviors and resilience within the ado-lescent demographic.Methods:A total of 7 063 middle school students were selected to assess ASD-like behaviors and resilience in adolescents using the Autism Spectrum Screening Questionnaire(ASSQ)as well as the Resilience Scale for Chinese Adolescent(RSCA).Subgroups bounded by P5 and P95 of the total ASSQ score,a comparative analysis of the resilience scores between these groups was executed.A correlation evaluation and linear regression a-nalysis was carried out between ASSQ and RSCA scores from all participants.Results:The RSCA scores within the high ASSQ scoring group,were inferior to those in the low scoring group.ASSQ scores were negatively correlated with RSCA scores for the full sample(Ps＜0.01);Social interaction scores on the ASSQ were negatively correlated with the five-factor RSCA scores(β=-0.23,-0.27,-0.11,-0.23,-0.37,Ps＜0.05).Conclusion:There was a negative association between autism spectrum disorder-like behaviors and resilience in adolescents,with more severe social interaction symptoms being associated with poorer resilience.

Aim To study the correlation between es-trogen metabolism function of intestinal flora and liver fibrosis disease phenotype and differential intestinal bacteria by fecal microbiota transplantation(FMT).Methods C57BL/6J male mice were divided into normal group(Control-M),liver fibrosis Model group(Model),FMT-1 group(normal mice fecal microbiota transplantation from liver fibrosis mice),and FMT-2 group(liver fibrosis mice fecal microbiota transplanta-tion from female mice).The model group was induced by high fat and high glucose combined with low dose of CCl4 for 16 weeks.In the FMT group,the bacteria were destroyed by mixed antibacterial solution and then the corresponding fecal microbiota solution was given.The model group was established in the FMT-2 group and the model group at the same time.Liver function(ALT,AST)was detected by biochemical methods;liver inflammation(IL-1α,IL-6)was detected by ELISA;liver pathology was detected by HE and Mas-son methods;the expressions of α-SMA,collagen Ⅰ,estrogen receptor ERα,ERβ and GPER were detected by Western blot;estrogen metabolic enzymes β-glucu-ronidase and β-glucosidase in intestinal flora were de-tected by double antibody sandwich assay;gut microbi-ota was detected by 16S rDNA method;the correlation between estrogen metabolic enzymes,estrogen receptors and disease phenotypes and disease-related differential bacteria was analyzed by Pearson correlation analysis.Results Liver function,inflammation and fibrosis in-dices were significantly higher in the model group than those in the control-M group and significantly lower in the FMT-2 group than in the model group;estrogen metabolic enzymes of the intestinal flora significantly increased in the model group compared to the control-M group and significantly decreased in the FMT-2 group compared to the model group;the model group showed a significant increase in ERβ and GPER and a significant decrease in ERα compared to the control-M group,while the FMT-2 group showed a significant de-crease in ERβ and GPER and a significant increase in ERα compared to the model group;the FMT-2 group increased the enterobacterial abundance and diversity reduced by modelling;estrogen metabolic enzymes,es-trogen receptor ERβ and GPER were all positively cor-related with the disease phenotype,while the opposite was true for ERα;estrogen metabolic enzymes were positively correlated with Allobaculum,Ruminococcus and Alistipes,and negatively correlated with Akkerman-sia,Lactobacillus and Prevotella.Conclusions Fecal microbiota transplantation in female mice can alleviate liver fibrosis in male mice,which is related to the im-provement of estrogen metabolism of intestinal flora.

Objective:To establish and validate a multimodal model based on radiomics and deep learning for predicting acute pancreatitis (AP) complicated with acute respiratory distress syndrome (ARDS).Methods:Patients diagnosed with AP from The First Affiliated Hospital of Soochow University, Donghai County People's Hospital and Jintan Affiliated Hospital of Jiangsu University between January 2017 and December 2023 were enrolled. Based on the diagnosis of ARDS within 1 week after admission, the patients were classified into the ARDS group and the non-ARDS group. Patients in the First Affiliated Hospital of Soochow University ( n=406) was used as the training set (non-ARDS group n=212 vs ARDS group n=194), while Donghai and Jintan hospitals served as the test set ( n=175; non-ARDS group n=104 vs ARDS group n=71). Clinical data, laboratory tests and the occurrence of systemic inflammatory response syndrome (SIRS) within 24 hours after admission were collected. Scoring systems such as bedside index for severity in acute pancreatitis (BISAP), Ranson score and modified CT severity index (MCTSI) were calculated. Radiomics features were extracted from three-dimensional CT images to develop a radiomics model based on XGBoost algorithm. At the same time, a deep learning model was constructed using deep convolutional networks to extract deep features. Finally, clinical features and the predictions from the aforementioned models were integrated to establish a multimodal model based on XGBoost algorithm. To enhance model visualization, variable importance ranking and local interpretable visualization were used. The receiver operating characteristic (ROC) curves of the three models and the three scores including BISAP, Ranson and MCTSI were plotted and the area under the curves (AUCs) were calculated to evaluate the prediction performance for ARDS in AP patients, as well as sensitivity and specificity. Results:In the multimodal model for predicting ARDS in AP patients, predictions of the deep learning model and the radiomics model were the most important variables, followed by SIRS, C-reactive protein, procalcitonin, albumin, glucose, creatinine, neutrophil, and Ca 2+. In the training set, the multimodal model achieved an AUC of 0.933 for predicting ARDS in AP patients, higher than the radiomics model (0.727), the deep learning model (0.877), MCTSI (0.870), Ranson (0.620) and BISAP (0.898). In the test set, the model's AUC was 0.916 for predicting ARDS in AP patients, higher than the radiomics model (0.660), the deep learning model (0.864), MCTSI (0.851), Ranson (0.609), and BISAP (0.860). Conclusions:Based on clinical structured data, radiomics and deep learning features, the multimodal model could predict the risk of ARDS in AP patients at an early stage, whose performance is better than the single-modal models and the traditional scoring systems.

Objective:To analyse the impact of diagnosis-related groups (DRG) payment reform on the length of stay and hospitalisation expenses of patients in pilot medical institutions of Beijing, for references for the formulation and optimisation of DRG payment related policies.Methods:The home page data of inpatient medical records from 56 medical institutions that implemented DRG payment in Beijing from April to October 2021 (before DRG payment reform) and April to October 2022 (after DRG payment reform). Patients participating in the basic medical insurance for urban employees in Beijing were selected as the reform group, and others served as the control group. The difference-in-differences model (DID) were used to analyse the related indicators, to evaluate the effectiveness of the reform.Results:This study comprised a total of 3 294 003 inpatients. Of them, 1 714 134 cases were in the control group (911 100 cases before the reform and 803 034 cases after) and 1 579 869 cases were in the study group (802 899 cases before the reform and 776 970 cases after). The gender, age composition and treatment methods of patients changed little before and after the reform. But the proportion of patients with severe comorbidities or complications rose from 11.11% before the reform to 13.19% after the reform. Through the analysis of the DID model, the DRG payment reform could reduce the length of stay ( P=0.001) and hospitalization expenses of patients ( P<0.001), and played a certain optimising role in the cost structure. Among them, the proportion of medical service expenses did not change significantly ( P=0.977), the proportion of inspection and testing expenses, as well as drug expenses decreased slightly ( P=0.001, P=0.004), and the proportion in consumable expenditures increased slightly ( P=0.001). Conclusions:DRG payment reform played a positive role in shortening the length of stay and hospitalization expenses. It was suggested that medical institutions in Beijing should further optimize the structure of patient hospitalization expenses, with a focus on exploring effective ways to increase the medical service revenue and reasonably control the consumables costs.

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.