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.

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.

Objective:To investigate the therapeutic effect of methotrexate loaded vesicles on experimental periodontitis in mice.Methods:Extracellular vesicles (EVs) were isolated from human umbilical cord mesenchymal stem cells (hUC-MSC). Methotrexate loaded vesicles (MTX-EVs) were constructed, whose morphology and size were analyzed by using scanning electron microscopy and particle size analyzer. Western blotting was used to identify their surface specific proteins. C57BL/6J male mice of 4-5 weeks (provided by Experimental Animal Center of The Fourth Military Medical University) were selected, among which 8 were randomly selected by blind grasp method without treatment and fed normally as normal group, and others were induced to periodontitis models by local injection of lipopolysaccharide (LPS) into the periodontium. The LPS was injected once every day with a concentration of 2 g/L and a volume of 5 μl, lasting for two weeks. The mice with successfully induced periodontitis were randomly divided into 4 groups by blind grasping method, with 8 mice in each group. The LPS group was with no treatment, and the other three groups were treated with periodontal local injection of MTX, EVs or MTX-EVs, respectively. Two weeks later, enzyme-linked immunosorbent assay (ELISA) was used to detect the expressions of inflammatory cytokine interleukin (IL)-1β, IL-6 and tumor necrosis factor-α (TNF-α) in gingival tissue. The amount of alveolar bone resorption of four groups was detected by using micro-CT scanning and HE staining. The expression proportion of the inflammatory factor in gingival tissue was analyzed by using flow cytometry.Results:The scanning electron microscopy results showed that EVs and MTX-EVs were circular or elliptical in shape. Dynamic light scattering (DLS) particle size analysis showed that the particle size of EVs was around 200 nm, while that of MTX-EVs was around 300 nm. The ELISA results showed IL-1β levels in the normal group, LPS group, LPS+MTX group, LPS+EVs group and LPS+MTX-EVs group were (28.86±2.76), (51.50±2.04), (35.26±2.40), (45.49±2.04) and (35.77±3.49) ng/L. That is, the IL-1β concentrations in the LPS+MTX group, LPS+EVs group and LPS+MTX-EVs group were significantly lower than that in the LPS group ( P<0.05); the mass concentration of IL-1β in the LPS +MTX-EVs group was significantly lower than that in the LPS+EVs group ( P<0.05). The concentrations of IL-6 in the normal group, LPS group, LPS+MTX group, LPS+EVs group and LPS+MTX-EVs group were (125.44±4.12), (221.64±10.59), (178.16±16.90), (181.09±18.22) and (170.15±9.04) ng/L, among which the concentration of IL-6 in the last three groups were significantly lower than that in the LPS group ( P<0.05). The mass concentration of IL-6 in the LPS+MTX-EVs group was significantly lower than those in the LPS+MTX group and LPS+EVs group ( P<0.05). The concentrations of TNF-α in the normal group, LPS group, LPS+MTX group, LPS+EVs group and LPS+MTX-EVs group were (320.27±38.68), (479.62±40.94), (342.18±25.89), (415.88±12.01) and (325.75±30.83) ng/L, among which the concentrations of last three groups were significantly lower than the LPS group ( P<0.05); the mass concentration of TNF-α in the LPS+MTX-EVs group was significantly lower than those in the LPS+EVs group and LPS+MTX group ( P<0.05). The micro-CT results showed that the distance of cement-enamel junction-alveolar bone crest (CEJ-ABC) of the first molar and root (M1R1) in the normal group, LPS group, LPS+MTX group, LPS+EVs group and LPS+MTX-EVs group of mice were (0.11±0.03), (0.28±0.02), (0.23±0.03), (0.20±0.04), and (0.18±0.03) mm, respectively. Compared with the LPS group, the CEJ-ABC of the M1R1 in the LPS+MTX group, LPS+EVs group and LPS+MTX-EVs group were inhibited to varied degrees with statistically significant differences ( P<0.05). Among them, LPS+MTX-EVs group had the best bone resorption inhibitioin effect compared to LPS+MTX group and LPS+EVs group, and the differences were statistically significant ( P<0.05). The flow cytometry results indicated that the proportion of interferon-γ (IFN-γ) positive cells was (11.77±1.02)% in the LPS group, (6.87±0.65)% in the LPS+EVs group, and (4.15±0.92)% in the LPS+MTX-EVs group, respectively. The proportions of IFN-γ positive cells in the LPS+EVs group and LPS+MTX-EVs group were significantly lower than that in the LPS group ( P<0.05), while the ratio of IFN-γ positive cells in the LPS+MTX-EVs group was found significantly lower than that in the LPS+EVs group ( P<0.05). Conclusions:MTX-EVs can effectively alleviate the periodontal local inflammatory environment and reduce bone resorption of alveolar bone in periodontitis model mice.

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.

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.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.