Objective To investigate the population density and seasonal fluctuations of Aedes albopictus in Guangzhou City, Guangdong Province, from 2021 to 2023, so as to provide insights into A. albopictus control and management of dengue fever. Methods The surveillance of A. albopictus density was performed in all surveillance sites assigned across all streets (townships) in Guangzhou City during the period from January to December from 2021 to 2023. The surveillance frequency was twice every half month from May to September, and once every month for the rest of a year. In each surveillance period, A. albopictus mosquito larvae were captured from indoor and outdoor small water containers in residential areas, parks, medical facilities, schools, other government sectors and social organizations, construction sites, special industries and others for mosquito species identification. Adult mosquitoes were captured using electric mosquito suction apparatus for species identification and gender classification. Adult mosquitoes and mosquito eggs were collected with mosquito and egg traps at the breeding and dwelling places of Aedes mosquitoes for identification. The mosquito oviposition index (MOI), Breteau index (BI), adult mosquito density index (ADI) and standard space index (SSI) were calculated. The A. albopictus density was classified into grades 0, 1, 2 and 3 in each surveillance site, with Grade 0 density defined eligible, and the eligible rate of A. albopictus density was calculated at all surveillance sites each year from 2021 to 2023. In addition, the changing trends in MOI, SSI, BI and ADI of A. albopictus were analyzed in Guangzhou City from 2021 to 2023. Results The eligible rates of A. albopictus density were 61.69%, 68.75% and 55.15% in surveillance sites of Guangzhou City from 2021 to 2023 (χ² = 297.712, P < 0.001), and appeared a tendency towards a reduction followed by a rise each year, which gradually reduced since January, maintained at a low level during the period between May and October, and gradually increased from November to December. The MOI, SSI, BI and ADI of A. albopictus all appeared a tendency towards a rise followed by a reduction in Guangzhou City during the period between January and December from 2021 to 2023. The BI of A. albopictus peaked in the first half of June in 2021 (4.03), the first half of July in 2022 (3.89) and the last half of August in 2023 (5.02), and the SSI of A. albopictus peaked in the last half of June in 2021 (0.93), the last half of May in 2022 (0.59), and the last half of June (0.94) and the first half of September in 2023 (1.12). In addition, the MOI of A. albopictus peaked in the first half of May in 2021 (8.64), the first half of June in 2022 (8.96), and the last half of May (10.21) and the last half of June in 2023 (10.89), and the ADI of A. albopictus peaked in the first half of June in 2021 (3.41), the last half of June in 2022 (4.06), and the first half of July in 2023 (3.61). Conclusions The density of A. albopictus is high in Guangzhou City during the period from May to October, and the risk of local outbreak caused by imported dengue fever is high. Persistent intensified surveillance of the density and seasonal fluctuation of A. albopictus is recommended and timely mosquito prevention and control is required according to the fluctuation in the A. albopictus density.

Objective To screen the influencing factors of hepatitis C cirrhosis patients progressing to hepatocellular carcinoma(HCC)using commonly used laboratory testing indicators,establish a prediction model using these indicators and validate them.Methods A total of 231 patients with hepatitis C cirrhosis and 179 patients with hepatitis C HCC hospitalized at the First Affiliated Hospital of Xi'an Jiaotong University between June 2020 and May 2023 were enrolled as the training set,and 105 patients with hepatitis C cirrhosis and 86 patients with hepatitis C HCC hospitalized between June 2023 and February 2024 were enrolled as the validation set.The routine laboratory test indexes of the study subjects in the two groups within the training set were compared,and logistic regression analysis was applied to screen the independent predictors of hepatocellular carcinoma occurrence.Receiver operating characteristic(ROC)curve was used to construct the curve model and validate the model.Results The age,male ratio,ALT,AST,AFP,WBC,NEU,MO,PLT,MPV,PDW,Fbg,NLR and PLR levels of the HCC group were higher than those of the cirrhosis group in the training set(H=-9.07～-2.19),while the levels of INR and LMR were lower than those of the cirrhosis group(H=-4.49,-2.65),and the differences were significant(all P＜0.05).The differences in TP,eGFR,LY and AST/ALT values between the two groups of patients were not significant(H=-1.46～-0.15,all P＞0.05).Multifactorial Logistic regression analysis showed that age(OR=1.048,95％CI:1.023～1.074),Male(OR=1.467,95％CI:1.413～1.765),AST(OR=1.010,95％CI:1.002～1.019),NEU(OR=1.186,95％CI:1.018～1.382)and Fbg(OR=2.245,95％CI:1.639～3.076)were independent risk factors for hepatocellular carcinoma patients(all P＜0.05),and these five independent risk factors were used to construct the HCC column-line graph prediction model,with the AUC for the training set and the validation set AUC(95％Cl)were 0.813(0.771～0.854)and 0.712(0.639～0.784),respectively,and the Hosmer-Lemeshow test showed a good fit of the model with P=0.650 for the training set and P=0.310 for the validation set.Conclusion The prediction model of HCC based on age,gender,AST,NEU and Fbg can have good predictive efficacy and clinical application value.

Objective:To evaluate the clinical efficacy of allogeneic hematopoietic stem cell transplantation（allo-HSCT）in children with severe aplastic anemia（SAA）.Methods:Twenty-seven cases with SAA who had been treated with allo-HSCT from January 2020 to December 2022 were retrospectively analyzed and reviewed.Results:（1）A total of 27 SAA patients were enrolled，including 18 males and 9 females，with a median age of 8 (2-15) years.There were 20 cases of SAA-Ⅰ type,7 cases of SAA-Ⅱ type.Based upon donor sources，three cases of matched sibling donors hematopoietic stem cell transplantation,and 24 cases of haploidentical hematopoietic stem cell transplantation were adopted.（2）Hematopoietic reconstruction was achieved in all 27 cases.The median implantation time of neutrophils and platelets was 10（9-20）days and 12（7-26）days respectively.The cumulative incidence of acute graft-versus-host disease（GVHD）was 66.67%（18/27）.The incidence of grade Ⅰ-Ⅱ was 55.56%（15/27）and that of grade Ⅲ-Ⅳ was 11.11%（3/27）.The incidence of chronic GVHD was 7.41%（2/27）.Transplant-associated thrombotic microangiopathy (TA-TMA) occurred in 7.41%（2/27）patients,cytomegalovirus viremia in 62.96%（17/27）patients,epstein-barr virus infection in 33.33%（9/27）patients,and 14.81%（4/27）patients progressed to post-transplant lymphoproliferative disorder (PTLD).（3）The median follow-up time was 12 (2-28) months.The overall survival rate was 96.29%.Twenty-six patients survived,and one patient died due to multiple complications of severe acute GVHD,TA-TMA,cytomegalovirus infection,PTLD and secondary epilepsy.Conclusion:Allo-HSCT is an effective therapy for SAA in children.The effective rate of this research is 96.29%.Acute GVHD is still the key to therapy.The incidence rate of acute GVHD is 66.67% in this study.The blood incompatibility of donor and recipient may affect the incidence of GVHD.The intensity of GVHD prevention should be reduced after HLA-matched sibling donor-hematopoietic stem cell transplantation so as to avoid the complications of virus recurrence and PTLD.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

AIM:To investigate the mechanism through which esculetin induces ferroptosis of mouse breast cancer 4T1 cells.METHODS:Molecular docking of esculetin with p53,solute carrier family 7 member 11(SLC7A11)and glutathione peroxidase 4(GPX4)proteins was performed,and Kaplan-Meier curves and time-dependent receiver oper-ating characteristic curves were drawn.The 4T1 cells were divided into 6 groups,namely the control(CON),1/2 IC50,IC50,2 IC50,erastin,and capecitabine groups.The appropriate drug concentration for treating 4T1 cells was screened by CCK-8 assay.The invasion and migration abilities of 4T1 cells following esculetin treatment at the selected drug concentra-tion were analyzed by scratch test and Transwell assay.Mitochondrial morphological change were examined by electron mi-croscopy.The levels of ferroptotic cell death were then quantified by Fe2+,reactive oxygen species(ROS),malondialde-hyde(MDA),glutathione(GSH),and GPX4 assays.Western blot was performed to evaluate the protein levels of p53,SLC7A11,GPX4 and acyl-CoA synthetase long-chain family member 4(ACSL4).RESULTS:Compared with CON group,the esculetin 1/2 IC50,IC50 and 2 IC50 groups showed smaller size,increased membrane density,and decreased ridge of mitochodria,as well as decreased levels of GSH and GPX4,reduced cell invasion and migration abilities,and de-creased levels of SLC7A11 and GPX4 proteins(P＜0.05).Furthermore,these groups exhibited increased levels of Fe2+,ROS,and MDA,as well as elevated p53 and ACSL4 protein abundance(P＜0.05).CONCLUSION:Esculetin pro-motes ferroptosis of 4T1 cells through a mechanism involving the p53/SLC7A11/GPX4 regulatory axis.

OBJECTIVE To study the efficacy and mechanism of Shugan Jianpi Jiedu decoction in the treatment of the precancerous lesions of breast cancer through animal experiment. METHODS SD rats were taken and divided into 6 groups(10 rats in each group), namely blank group, breast precancerous lesion model group, tamoxifen group, Shugan Jianpi Jiedu decoction groups with low dose, middle dose, and high dose. DMBA modeling method was used to carry out modeling for breast precancerous lesion. HE staining was used to observe the pathological changes of breast tissue. CD4+, CD8+ were detected by flow cytometry. ELISA was used to detect IL-2, IL-4, IL-6, IL-10, IL-12, E2, P. The protein expression of ER, PI3K, p-Akt and mTOR was detected by Western blotting. RESULTS HE staining showed changes in rat mammary tissue, indicating successful modeling. Compared with the blank group, the content of CD4+ decreased and the content of CD8+ increased in the model group(P<0.01); compared with model group, the content of CD4+ increased and the content of CD8+ decreased in low, middle, high dose groups of Shugan Jianpi Jiedu decoction and tamoxifen group(P<0.01). The levels of IL-2, IL-4 and IL-10 in the model group were significantly lower than those in the blank group(P<0.01), while IL-12 and IL-6 were significantly increased(P<0.01). Compared with the model group, the concentrations of IL-2, IL-4 and IL-10 in the low, middle and high dose groups of Shugan Jianpi Jiedu decoction and the tamoxifen group were significantly increased(P<0.01), while IL-12 and IL-6 decreased significantly(P<0.05 or P<0.01). Compared with the blank group, the contents of E2 and P in the model group increased significantly(P<0.05 or P<0.01), the contents of E2 and P in the low, middle and high dose groups of Shugan Jianpi Jiedu decoction and the tamoxifen group were significantly lower than those in the model group(P<0.01). The Western blotting results showed that compared with the blank group, the expression of ER, PI3K, p-Akt and mTOR in the model group was significantly increased(P<0.01). Compared with the model group, the expression of ER, PI3K, p-Akt and mTOR in the low, medium and high dose groups of Shugan Jianpi Jiedu decoction and the tamoxifen group were significantly decreased(P<0.01). CONCLUSION Shugan Jianpi Jiedu decoction may inhibit the expression of ER, thus inhibiting the expression of PI3K/Akt/mTOR signaling pathway. Meanwhile, it can affect the immune response and reverse the precancerous lesions of breast cancer.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.