AIM: To investigate the diagnostic and prognostic value of differential expression of Cyclin D1 and p53 in eyelid tumors.METHODS: This retrospective study enrolled patients who underwent surgical resection for eyelid tumors at our hospital between March 2018 and March 2023. Participants were categorized into benign and malignant groups based on tumor characteristics. Clinical data were collected. Genetic data for eyelid tumors were obtained from the GEO database, and differential gene analysis, including volcano plot visualization and KEGG pathway enrichment analysis, was performed using the Sangerbox 3.0 platform. Immunohistochemistry was used to detect the expression levels of Cyclin D1, p53, and BAX in tissue samples. Correlations with clinical features were analyzed using Spearman analysis, and prognostic factors were identified via Logistic regression analysis.RESULTS: This study included 69 patients with eyelid tumors(78 eyes), categorized into a benign group(37 patients, 41 eyes)and a malignant group(32 patients, 37 eyes)based on tumor characteristics. There were significant differences between the two groups in histological subtype, TNM staging, vascular invasion, differentiation status, and local infiltration(all P<0.05). Among benign tumors: pigmented nevi in 11 eyes(27%), hemangiomas in 9 eyes(22%), squamous cell papillomas in 5 eyes(12%), epidermoid cysts in 5 eyes(12%), seborrheic keratoses in 4 eyes(10%), neurofibromas in 3 eyes(7%), and both calcifying epithelioma and xanthelasma in 2 eyes each(5%); among malignant tumors: basal cell carcinoma in 18 eyes(49%), meibomian gland carcinoma in 8 eyes(22%), squamous cell carcinoma in 5 eyes(14%), sebaceous gland carcinoma in 4 eyes(11%), lymphoma and malignant melanoma each in 1 eye(3%). At the follow-up cutoff date of March 2025, the 2-year survival rate in the benign group(95%)was significantly higher than that in the malignant group(78%; P<0.05). Bioinformatics analysis identified 4 103 differentially expressed genes, including Cyclin D1, p53, and BAX, which were predominantly involved in pathways such as the p53 signaling pathway and calcium-related signaling. Spearman analysis revealed that local invasion(rs=0.71, P<0.05)and TNM stage(rs=0.73, P<0.05)correlated with Cyclin D1 expression; local invasion(rs=0.76, P<0.05)and histological subtype(rs=0.65, P<0.05)correlated with p53 expression. Logistic regression results indicated that Cyclin D1, p53, TNM staging, and local invasion were prognostic risk factors. ROC curve analysis demonstrated that the combined detection of these four indicators had the highest predictive value for prognosis(AUC=0.83).CONCLUSION: High expression of cyclin D1 and p53 serves as molecular markers for distinguishing benign from malignant eyelid tumors and assessing prognosis. Combined detection of these markers with TNM staging and local invasion demonstrates high predictive value for prognosis.

Objective: To investigate factors influencing perioperative blood transfusion in patients with scarred uterus during pregnancy undergoing cesarean section, construct and validate a transfusion risk prediction model, and provide evidence for preoperative assessment and blood management. Methods: Clinical data of 405 patients undergoing cesarean section for scarred uterus during pregnancy at the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2024 were retrospectively collected. The dataset was randomly divided into a training set (n=284) and a validation set (n=121) at a 7∶3 ratio. Within the training set, Firth-penalized logistic regression was employed for multivariate analysis to identify independent factors influencing perioperative blood transfusion and construct a predictive model. Model performance was evaluated in the validation set. Results: Multivariate Firth regression analysis showed that severe placenta previa (OR=75.566, 95%CI: 8.603-9979.174) and placenta accreta (OR=4.591, 95%CI: 1.120-19.416) were independent risk factors for perioperative blood transfusion, while preoperative red blood cell count (OR=0.189, 95%CI: 0.083-0.405) and fibrinogen levels (OR=0.588, 95%CI: 0.395-0.855) were protective factors. The predictive model constructed based on these four variables demonstrated good discriminatory performance, with areas under the receiver operating characteristic curves of 0.803 (95%CI: 0.740-0.867) and 0.753 (95%CI: 0.644-0.862) in the training and validation sets, respectively. Conclusion: For patients with scarred uterus during pregnancy undergoing cesarean section, severe placenta previa and placenta accreta significantly increase the risk of transfusion, while higher preoperative red blood cell count and fibrinogen levels exert a protective effect. The predictive model established in this study facilitates the identification of patients requiring transfusion, thereby enabling preoperative blood preparation and optimized blood management.

Aim To study the effect of anti-PD-L1 monoclonal antibody on high-fat diet-induced athero-sclerosis in ApoE-/-mice.Methods Twenty-four ApoE-/-mice were randomly divided into the normal group,high-fat group,and high-fat+anti-PD-L1 mAb group.After 70 days,the blood samples were harves-ted.Blood vessels(aortic root to abdominal aorta)and liver from each groups were stained with Oil Red O.Hematoxylin-eosin staining(HE)was employed to vis-ualize structural changes in liver.Enzyme-linked im-munosorbent assay(ELISA)was applied to detect the serum levels of total cholesterol(CHO),triglyceride(TG),high-density lipoprotein(HDL-c),low-density lipoprotein(LDL-c)and inflammatory factors(IFN-γ,TNF-α,IL-1 β).Flow cytometry was used to detect the proportion of lymphocytes(CD4 and CD8).RT-PCR was utilized to assess the expressions of IFN-γ,TNF-α,IL-1 β,CD4 and CD8 in liver.Results Compared with the high-fat group,the treatment with anti-PD-L1 monoclonal antibody promoted vascular wall and liver lipid accumulation,and also up-regulated serum and liver content of cholesterol(CHO),triglyceride(TG)and high-density lipoprotein(HDL-c).Treatment with anti-PD-L1 monoclonal antibody up-regulated the con-tent of alanine aminotransferase(GPT)and aspartate aminotransferase(GOT)in serum and liver,but not al-kaline phosphatase(AKP).ELISA test indicated that treatment with anti-PD-L1 monoclonal antibody stimu-lated the serum level of IFN-γ,TNF-α and IL-1 β.Fur-thermore,the mRNA level of IFN-γ,TNF-α and IL-1 βin liver was also up-regulated after treatment with anti-PD-L1 monoclonal antibody.With flow cytometry,we observed that treatment with anti-PD-L1 monoclonal antibody promoted hepatic CD8+T and CD8+IFN-γ+T cell activation,but had no effect on CD4+IFN-γ+T cell activation under high-fat feeding conditions.Con-clusions Anti-PD-L1 monoclonal antibody adminis-tered under high-fat feeding conditions can damage liv-er function and aggravate atherosclerosis by activating liver CD8+IFN-γ+T cells.

AIM To study the chemical constituents from the water fraction of rhizoma of Smilax trinervula Miq.and their biological activities.METHODS Polyamide,silica gel,Sephadex LH-20,ODS and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT mothod,and the inhibitory activities on α-glucosidase were determined by PNPG method.RESULTS Eleven compounds were isolated and identified as tyrosine(1),uridine(2),2-(2',3',4'-trihydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(3),2-(1',2',3',4'-tetrahydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(4),2-(1',2',3',4'-tetrahydroxybutyl)-5-(2",3",4"-trihydroxybutyl)-pyrazine(5),uracil(6),2-(1',2',3',4'-tetrahydroxybutyl)-5-(1",2",3",4"-tetrahydroxybutyl)-pyrazine(7),dioscin(8),shikimic acid(9),pyrazine(10),3,4-dihydroxyphenyethyl alcohol 8-O-β-D-glycopyranoside(11).The IC50 values of compounds 8 to human breast cancer cell MCF-7 was(2.36±0.26)μg/mL,and the IC50 values of compounds 3-5 and 7 to α-glucosidase were(1.54±0.15)-(10.53±0.38)μg/mL.CONCLUSION Compounds 1-7,10 are isolated from Smilax genus for the first time,and compound 9,11 are first isolated from this plant.Compound 8 has anti-tumor activity,and compounds 3-5,7 have α-glucosidase inhibitory activities.

Objective To analyze the global literature related to functional cure of hepatitis B from 2019 to 2023 by using bibliometric analysis methods,so as to help researchers understand the research hotspots and trends in this field.Methods The literature related to the topic of functional cure of hepatitis B included in the Science Citation Index Expanded(SCI-Expanded)of the Web of Science Core Collection from 2019 to 2023 was searched.By using VOSviewer and CiteSpace visual analysis tools,analyses were conducted from the perspectives of publication trends,international research cooperation networks,and keyword emergence,and were elaborated with the specific contents of the related literature to elucidate research hotspots and trends.Results A total of 600 eligible papers in this field were included.Keyword co-occurrence and thematic clustering suggested that the main research directions of functional cure were:serum biomarkers for prediction and monitoring of functional cure,functional cure and immunity,nucleoside analog discontinuation,interferon therapy,and long-term prognosis of functional cure.The research contents of the ESI highly cited original research papers were similar to the clustering of the above,but showed more attention on the novel agents for functional cure.The content of the keyword emergence map showed that hotspots of interest changed from virologic mechanisms and serum markers,to nucleoside analog discontinuation and interferon therapy,and finally to immunologic mechanisms and new drug.Conclusion The research hotspots and trends of functional cure of hepatitis B were focused on virological mechanism,serum markers,immunological mechanism,nucleoside analog discontinuation,interferon therapy,and long-term prognosis after cure.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective To compare the therapeutic efficacy of a self-locking zero-notch interbody fusion device for long-segment cervical spondylosis in elderly patients with traditional titanium plate combined with interbody fusion device.Methods From Jan 2019 to Jan 2021,elderly patients(>60 years)with 3-4 segments(C3-C7)radiculopathy,myelopathy,or mixed-type cervical spondylosis underwent anterior cervical discectomy and fusion(ACDF)using a zero-notch interbody fusion device(Group A,n=24)and ACDF using a titanium plate combined with an interbody fusion device(Group B,n=18).We recorded the surgery duration,blood loss,incision length and hospital stay,measure preoperative and postoperative intervertebral height,functional segment height and cervical lordosis,and also observe treatment outcomes and postoperative complications between the two groups.Results There were no statistically significant differences between the two groups in terms of gender,age,Japanese Orthopaedic Association(JOA)score,visual analogue scale(VAS)of upper limb,Neck Disability Index(NDI),preoperative intervertebral height,functional segment height and cervical lordosis.Blood loss,surgery time and hospital stay were similar in both groups,but Group A had shorter incision length(P<0.01)compared with Group B.There were no significant differences between the two groups in JOA scores,upper limb VAS and postoperative NDI,and even in postoperative intervertebral height,functional segment height and cervical lordosis recovery.Conclusion The zero-notch interbody fusion device is effective for treating long-segment cervical spondylosis.Compared with the traditional titanium plate combined with an interbody fusion device,it can avoid postoperative dysphagia with smaller incision and shorter surgery time,which makes it more suitable for elderly patients.

Objective:To investigate the predictive value of heart rate variability(HRV)and heart rate turbulence(HRT)related parameters for major adverse cardiovascular events(MACE)in patients with coronary heart disease(CHD).Methods:A total of 330 CHD patients admitted to Zaozhuang Hospital of Traditional Chinese Medicine between May 2020 and October 2022 were enrolled.According to the occurrence of MACE,they were divided into MACE group(n=30)and no MACE group(n=300).HRV and HRT parameters were compared between two groups.Receiver operating characteristic(ROC)curve was employed to analyze the predictive value of HRV and HRT parameters for MACE in CHD patients.Results:Compared with patients in no MACE group,those in MACE group had significant higher turbulence onset(TO)[(1.80±0.29)％ vs.(1.31±0.26)％],and significant lower turbulence slope(TS)[(2.46±0.72)ms/RRI vs.(3.08±0.56)ms/RRI],standard deviation of normal to normal RR intervals(SDNN)[(68.61±4.96)ms vs.(80.87±7.83)ms],root mean square of successive differences(rMSSD)[(16.85±4.96)ms vs.(19.85±4.76)ms]and percentage of NN intervals differing by more than 50 ms(PNN50)[(3.32±0.92)％ vs(4.36±1.12)％](P＜0.01 all).ROC curve indicated that TO(AUC=0.854,95％CI 0.811～0.890),TS(AUC=0.649,95％CI 0.595～0.700),SDNN(AUC=0.850,95％CI 0.807～0.887),rMSSD(AUC=0.656,95％CI 0.602～0.707)and PNN50(AUC=0.708,95％CI 0.656～0.757)had cer-tain predictive value for MACE in CHD patients,among which TO and SDNN had the highest predive performance.Conclusion:HRV and HRT parameters have certain predictive value for MACE in CHD patients,and the predictive performance of TO and SDNN are the highest,which could be used as sensitive indicators for MACE in CHD pa-tients.