BACKGROUND:Autophagy,as a key regulatory mechanism of cell development,plays an important role in different stages of embryonic development.The mechanism of how autophagy regulates embryonic development through histone modifications is currently unclear.OBJECTIVE:To investigate the effect of autophagy on trimethylation of lysine 4 on histone H3(H3K4me3)modification in embryos and its effect on embryonic development.METHODS:Mouse fertilized eggs were divided into control and autophagy inhibitor-treated groups(chloroquine phosphate-treated group and 3-methyladenine-treated group),and cultured in vitro to different periods of time,and were then classified as early 2-cell embryos,middle 2-cell embryos,late 2-cell embryos,4-cell embryos,8-cell embryos,morula stage,and blastocyst stage.Levels of reactive oxygen species,autophagy marker proteins LC3B and P62,DNA loss marker γH2AX,and H3K4me3 were analyzed by immunofluorescence assay in late 2-cell embryos of each group.Changes in H3K4me3 modification in late 2-cell embryos of each group were detected by CUT&Tag.RESULTS AND CONCLUSION:(1)Autophagy inhibition caused embryo development arrest.(2)There was no significant difference in reactive oxygen species and γH2AX between the autophagy inhibitor-treated groups and control group.(3)H3K4me3 levels were significantly elevated in the autophagy inhibitor-treated group compared with the control group.(4)CUT&Tag results showed a significantly increased H3K4me3 peaks on the proximal promoter region of the genes after autophagy inhibition and an increase of H3K4me3-specific modification genes.These findings suggest that autophagy may affect embryonic development by regulating the level of H3K4me3 modification.

BACKGROUND:Autophagy,as a key regulatory mechanism of cell development,plays an important role in different stages of embryonic development.The mechanism of how autophagy regulates embryonic development through histone modifications is currently unclear.OBJECTIVE:To investigate the effect of autophagy on trimethylation of lysine 4 on histone H3(H3K4me3)modification in embryos and its effect on embryonic development.METHODS:Mouse fertilized eggs were divided into control and autophagy inhibitor-treated groups(chloroquine phosphate-treated group and 3-methyladenine-treated group),and cultured in vitro to different periods of time,and were then classified as early 2-cell embryos,middle 2-cell embryos,late 2-cell embryos,4-cell embryos,8-cell embryos,morula stage,and blastocyst stage.Levels of reactive oxygen species,autophagy marker proteins LC3B and P62,DNA loss marker γH2AX,and H3K4me3 were analyzed by immunofluorescence assay in late 2-cell embryos of each group.Changes in H3K4me3 modification in late 2-cell embryos of each group were detected by CUT&Tag.RESULTS AND CONCLUSION:(1)Autophagy inhibition caused embryo development arrest.(2)There was no significant difference in reactive oxygen species and γH2AX between the autophagy inhibitor-treated groups and control group.(3)H3K4me3 levels were significantly elevated in the autophagy inhibitor-treated group compared with the control group.(4)CUT&Tag results showed a significantly increased H3K4me3 peaks on the proximal promoter region of the genes after autophagy inhibition and an increase of H3K4me3-specific modification genes.These findings suggest that autophagy may affect embryonic development by regulating the level of H3K4me3 modification.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.

Objective To investigate short-term clinical efficacy of autologous leukocyte-poor platelet-rich plasma(LP-PRP)treatment of knee osteoarthritis(KO A).Methods 85 cases of patients with Keligren Lawrence grade Ⅰ-Ⅲ knee os-teoarthritis in Peking University First Hospital Taiyuan Hospital(Taiyuan Central Hospital)from 2022 to 2023 were collect-ed for autologous LP-PRP collection and quality assessment using a blood component separator,and all patients were treated with autologous LP-PRP.The degree and function of knee pain were assessed by visual analog scale(VAS)and knee arthri-tis index scale(WOMAC)at 1,3 and 6 months after injection.Knee MRI was performed after 6 months of treatment,and the MRI imaging changes before and after treatment were compared.Different influencing factors in the treatment results were grouped and analyzed,mainly including platelet concentration in LP-PRP and K-L grading of knee joint.According to the platelet concentration in LP-PRP,it was divided into three grades,which are low concentration[(＜800)×109/L],medium concentration[(800-1 000)×109/L],and high concentration[(＞1 000)× 109/L];According to the K-L grade of the knee joint,the severity of knee osteoarthritis was divided into three grades:Ⅰ、Ⅱ、Ⅲ.Results The VAS and WOMAC scores at 1,3 and 6 months after LP-PRP treatment were significantly lower than those before treatment,and the difference was sta-tistically significant(P＜0.05).There was a statistically significant difference in the therapeutic effect of different levels of platelet concentration,and when the platelet concentration was more than 1 000×109/L,the significant effect was the most obvious(P＜0.05).The therapeutic effect of different levels of platelet concentration was statistically significant(P＜0.05).MRI showed that the articular cartilage signal was significantly improved after treatment.Conclusion Autologous LP-PRP injection into knee cavity for the treatment of KO A has a good short-term clinical effect in relieving knee pain.

Objective:To investigate the risk factors of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients in plain-sand areas and loess hilly areas of Gansu province.Methods:A total of 1 599 T2DM patients who participated in chronic disease and risk factors monitoring and basic public health service management were selected by multi-stage stratified random sampling method in the sandy plain areas and loess hilly areas of Gansu province. Questionnaire survey, physical measurement and laboratory tests were performed. Multivariate binary logistic model was used to analyze the influencing factors.Results:The prevalence of DKD was 22.1% (174/787) among T2DM patients in the sandy plain areas and 19.1%(155/812) in the loess hilly area, respectively. Hypertension ( OR=3.022), hyperuricemia ( OR=2.114) and HbA1c≥7%( OR=2.231) were the risk factors for DKD in the plain-sand areas, and the risk of DKD increased with age. In the loess hilly areas, female sex ( OR=0.379) was the protective factor for DKD; while duration of disease≥10 years ( OR=2.476), hyperuricemia ( OR=1.907), HbA1c≥7% ( OR=1.927) were the risk factors for DKD; and the risk of DKD increased with the increase of age, and decreased with the increase of per capita monthly income. Conclusions:The prevalence of DKD and its influencing factors are different between sandy plain areas and loess hilly areas in Gansu province. The prevention and treatment of hypertension should be given more attention in sandy plain areas. In addition, the screening of DKD should be conducted among T2DM patients, particularly for those with old age, hyperuricemia and HbA1c≥7% in both areas of the province.

Osteosarcoma is a malignant tumor with extreme invasiveness and metastasis as well as dismal prognosis. It is critical to rapidly find a unique therapy strategy capable of significantly improving the prognosis of osteosarcoma. Tumor immunotherapy has the potential to reawaken the immune system, restart and sustain the tumor-immune cycle in the body, resulting in the death of tumor cells. CD8+ CTL, CD4+ T cells, NK cells and NKT cells all play critical roles in tumor immunity, while humoral immunity may not only inhibit tumor growth but also enhance it. Researchers have devised various strategies to boost the immune system in recent years based on tumor immune response studies. This paper highlights and examines osteosarcoma immunotherapy from two perspectives: (1) boosting the response of patient's own immune system to the tumor; (2) exogenously improving the patient's immunological function.