Objective : To observe the brain tissue injury during hypoxia-ischemia, as well as the pathological changes and the expression of ferroptosis-related factors after the use of Shenfu injection(SFI), and to explore the protective effect of SFI on hypoxic-ischemic brain injury(HIBD) by inhibiting ferroptosis. Methods : An animal model of HIBD in SD rats was constructed and intervened with SFI. Pathologic changes in brain tissue were observed by HE staining methods. Nissen staining was used to observe neuron survival. Glutathione Peroxidase 4(GPX4) and Divalent Metal Transporter 1(DMT1) expression were detected in brain tissue by Western blot, immunohistochemistry and immunofluorescence. Reduced Glutathione(GSH), Lactate Dehydrogenase(LDH), Malondialdehyde(MDA), Superoxide Dismutase(SOD) and tissue iron content were determined with the kits. BV-2 microglial cell line(BV2) cells were culturedin vitroand divided into control group(Ctrl group), oxygen-glucose deprivation group(OGD group), iron ferroptosis-inducing group(Erastin group), iron ferroptosis-inhibiting group(Fer-1 group), Shenfu injection group(SFI group), and Erastin+Shenfu injection group(Erastin+SFI group). 2′,7′-Dichlorodihydrofluorescein diacetate(DCFH-DA) reactive oxygen species(ROS) fluorescent probe was used to detect the ROS release level; Immunofluorescence was used to observe intracellular GPX4, DMT1 expression. Results : Compared with the Sham group, rats in the HIBD group showed significant neuronal cell damage in brain tissue, decreased GPX4 expression(P<0.01), increased DMT1 expression(P<0.01), decreased GSH and SOD levels(P<0.01), and increased LDH, MDA and tissue iron levels(P<0.05,P<0.05,P<0.01). In contrast, after the intervention of SFI, GPX4 expression was elevated(P<0.01), DMT1 expression decreased(P<0.01), GSH and SOD levels were elevated(P<0.01), and LDH, MDA, and tissue iron levels decreased(P<0.05,P<0.05,P<0.01). The cells experiments showed that compared with the Ctrl group, the OGD group had a significantly higher ROS content and a decrease in the expression of GPX4 fluorescence intensity, and an increase in the fluorescence intensity of DMT1(P<0.01), compared with the OGD group, the ROS content was reduced in the SFI group, while the expression of GPX4 was elevated and the expression of DMT1 was reduced(P<0.01). Conclusion Hippocampal and cortical regions are severely damaged after HIBD in neonatal rats, and their brain tissues show decreased expression of GPX4 and increased expression of DMT1. The above suggests that ferroptosis is involved in HIBD brain injury in neonatal rats. In contrast, Shenfu injection has a protective effect on HIBD experimental animal model and BV2 cell injury model by reducing iron aggregation and ROS production.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

BACKGROUND:Knee osteoarthritis(KOA)is a common chronic inflammatory disease that causes damage to joint cartilage and surrounding tissues.Immune cells play an important role in the immune-inflammatory response in knee osteoarthritis,but the specific mechanisms involved are still not fully understood. OBJECTIVE:To evaluate the potential causal relationship between 731 immune cell phenotypes and the risk of knee osteoarthritis using Mendelian randomization. METHODS:Summary statistics of genome-wide association studies(GWAS)for 731 immune cell phenotypes(from GCST0001391 to GCST0002121)obtained from the GWAS catalog and GWAS data for knee osteoarthritis from the IEUGWAS database(ebi-a-GCST007090)were used.Inverse variance-weighted method,MR-Egger regression,weighted median method,weighted mode method,and simple mode method were employed to investigate the causal relationship between immune cells and knee osteoarthritis.Sensitivity analyses were conducted to assess the reliability of the Mendelian randomization results.Reverse Mendelian randomization analysis was also performed using the same methods. RESULTS AND CONCLUSION:The forward MR analysis indicated significant causal relationships(FDR<0.20)between knee osteoarthritis and four immune cell phenotypes,namely CD27 on CD24+CD27+in B cells(OR=1.026,P=0.000 26,Pfdr=0.18),CD33 on CD33dim HLA DR-in myeloid cells(OR=1.014,P=0.000 50,Pfdr=0.18),and CD45RA+CD28-CD8br%CD8br in Treg cells(OR=1.001,P=0.000 78,Pfdr=0.18),and PDL-1 on monocytes in mononuclear cells(OR=0.952,P=0.000 98,Pfdr=0.18).These immune cell phenotypes showed direct positive or negative causal associations with the risk of knee osteoarthritis.Reverse Mendelian randomization analysis revealed no significant causal relationships(FDR<0.20)between knee osteoarthritis as exposure and any of the 731 immune cell phenotypes.The results of sensitivity analysis show that the P-values of the Cochran's Q test and the MR-Egger regression method for bidirectional Mendelian randomization were both greater than 0.05,indicating that there is no significant heterogeneity and pleiotropy in the causal effect analysis between immune cell phenotypes and knee osteoarthritis.To conclude,there may be four potential causal relationships between immune cell phenotypes,such as CD27 on CD24+CD27+cells,CD33 on CD33dim HLA DR-cells,CD45RA+CD28-CD8br%CD8br cells,and PDL-1 on monocytes,and knee osteoarthritis.These findings provide valuable clues for studying the biological mechanisms of knee osteoarthritis and exploring early prevention and treatment strategies.They also offer new directions for the development of intervention drugs.

Objective: To explore the causal link of cumulative ecological risk and future orientation with health risk behaviors among higher vocational college students, so as to provide reference for reducing and preventing health risk behaviors among higher vocational college students. Methods: A longitudinal follow up study was conducted on 612 students using convenience sampling from 2 vocational colleges in Hunan Province. The Cumulative Ecological Risk Scale, Future Orientation Scale, and Health Risk Behavior Scale were used during three follow up visits (T1: September 2022, T2: June 2023, T3: March 2024), and a cross lagged panel model was constructed to examine the longitudinal causal relationship of cumulative ecological risk, future orientation and health risk behaviors. Analysis of longitudinal intermediary effect between variables by Bootstrap. Results: The cumulative ecological risk scores of T1, T2 and T3 among higher vocational college students were (2.94±1.44,2.99±1.63,3.02±1.54), future orientation scores (40.49±4.71,41.51±5.72,41.06±4.35) and health risk behavior scores (3.73±2.01,3.49±2.00,3.23±2.00). The results of repeated measures ANOVA showed that the future orientation score of T2 was higher than that of T1, and the main effect of measurement time was statistically significant ( F=5.09，P＜0.01,η 2=0.02). The health risk behavior score of T1 was higher than that of T2, and the health risk behavior score of T2 was higher than that of T3, and the main effect of measurement time was statistically significant ( F=10.12，P＜0.01,η 2=0.03).The cross lagged model showed good adaptability, with χ 2/df =7.20 ( P <0.01), relative fitting indicators GFI=0.98, CFI=0.99, TLI=0.96, IFI=0.99, NFI =0.99, and absolute fitting indicator RMSEA =0.06. Among them, the T1, T2 cumulative ecological risk showed negatively predictive effects on T2, T3 future orientation ( β =-0.24, -0.47 ), and T1, T2 cumulative ecological risk positively predicted T2, T3 health risk behavior ( β =0.20, 0.24), while T1, T2 future orientation negatively predicted T2, T3 health risk behavior ( β =-0.25, -0.18) ( P ＜0.01). Bootstrap test analysis found that T2 future orientation had a longitudinal mediating effect ( β=0.04, P ＜0.01) on the T1 cumulative ecological risk and T3 health risk behavior. Conclusions The accumulation of ecological risk among higher vocational college students can positively predict health risk behaviors, while future orientation can negatively predict healthrisk behaviors. Moreover, future orientation plays a longitudinal mediating role between accumulated ecological risks and health risk behaviors.

OBJECTIVE To establish a clinical comprehensive evaluation framework for direct oral anticoagulants （DOACs） in the prevention of cancer-associated venous thromboembolism （CAVTE）， providing a methodological reference for the rational prevention and treatment of CAVTE as well as for the formulation and adjustment of macro-management strategies for anticoagulant drugs. METHODS Through literature retrieval， evaluation indicators were collected and organized to establish a preliminary indicator pool. The selection of evaluation indicators was carried out through two rounds of Delphi surveys using average score of indicator importance≥3.5 and a coefficient of variation （CV） ＜0.25 as the screening criteria. Analytic hierarchy process （AHP） was employed to finalize the indicator weights. RESULTS The authority levels （C）r of the two rounds of expert consultations were 0.877 and 0.943， with CV of 0.24 and 0.18， respectively. The Kendall concordance coefficients were 0.331 and 0.535 （P＜0.05）. After expert validation， six primary indicators and forty-six secondary indicators were finalized for inclusion in the evaluation framework. The primary indicators and their weightings， ranked in descending order， were as follows：“ effectiveness” （38.86%）， “safety” （38.86%），“ cost-effectiveness” （10.67%），“ accessibility” （5.51%），“ suitability” （3.48%）， and “innovation” （2.64%）. The secondary indicators exhibited a weight range from 0.02% to 20.25%， with the top five secondary indicators being：“ incidence of intracranial hemorrhage” （20.25%）， “reduction in all-cause mortality” （15.29%）， “decrease in the incidence of pulmonary embolism” （8.82%）， “reduction in the incidence of deep vein thrombosis” （7.25%）， and “drug contraindications” （4.74%）. CONCLUSIONS This study has established an authoritative， scientific， and reliable comprehensive clinical evaluation framework for the use of DOACs in the prevention of CAVTE.