Complement C3 plays a critical role in periodontitis. However, its source, role and underlying mechanisms remain unclear. In our study, by analyzing single-cell sequencing data from mouse model of periodontitis, we identified that C3 is primarily derived from periodontal fibroblasts. Subsequently, we demonstrated that C3a has a detrimental effect in ligature-induced periodontitis. C3ar^-/- mice exhibited significantly less destruction of periodontal support tissues compared to wild-type mice, characterized by mild gingival tissue damage and reduced alveolar bone loss. This reduction was associated with decreased production of pro-inflammatory mediators and reduced osteoclast infiltration in the periodontal tissues. Mechanistic studies suggested that C3a could promote macrophage polarization and osteoclast differentiation. Finally, by analyzing single-cell sequencing data from the periodontal tissues of patients with periodontitis, we found that the results observed in mice were consistent with human data. Therefore, our findings clearly demonstrate the destructive role of fibroblast-derived C3 in ligature-induced periodontitis, driven by macrophage M1 polarization and osteoclast differentiation. These data strongly support the feasibility of C3a-targeted interventions for the treatment of human periodontitis.
Animals ; Osteoclasts/cytology* ; Periodontitis/metabolism* ; Cell Differentiation ; Mice ; Fibroblasts/metabolism* ; Macrophages ; Disease Models, Animal ; Complement C3/metabolism* ; Humans ; Disease Progression ; Mice, Inbred C57BL ; Male ; Mice, Knockout

This study aimed to investigate the regulatory effect and mechanism of thymopentin on the growth of subcutaneous hepatocellular carcinoma in mice. A subcutaneous tumor model of Hepa1-6 liver cancer in immunocompetent mice was constructed, with three randomly divided groups based on tumor volume: control group, low-dose thymopentin (TP5) group (10 mg/kg), and high-dose TP5 group (20 mg/kg), with 6 mice in each group. Drugs were administered, and the intervention effect of thymopentin on tumor growth was evaluated. Hepa1-6 cells were then cultured in vitro and treated with blank medium and TP5 of different concentrations (10, 100, 1000 ng/mL) for 72 hours. Cell viability was detected by sulforhodamine B (SRB) colorimetry. A subcutaneous tumor model of liver cancer LM3 in immunocompromised mice was constructed, with three randomly divided groups based on tumor volume: control group, TP5 group (20 mg/kg), and positive drug Sorafinib group (30 mg/kg). The intervention effect of thymopentin on the growth of subcutaneous tumors in immunocompromised mice was evaluated. Flow cytometry was used to analyze the changes in the proportion of T cells and myeloid-derived suppressor cells (MDSCs) in the tumor microenvironment 11 days after TP5 administration in the Hepa1-6 model. MDSCs were cultured in vitro and treated with TP5. The effect of TP5 on MDSCs was evaluated by detecting the levels of ROS, IL-6, and NO, which are effector molecules of MDSCs. The mouse subcutaneous liver cancer model was established again using C57BL/6N mice. After 10 days, they were randomly divided into four groups based on tumor volume: control group, low-dose TP5 group (10 mg/kg), high-dose TP5 group (20 mg/kg), and arginine-deficient TP5 group (15 mg/kg). Drugs were administered continuously for 11 days, and the intervention effect of arginine-deficient TP5 on tumor growth was evaluated based on tumor weight. Annexin-V staining was used to detect the impact of TP5 on T cell survival. The results showed that both low and high doses of TP5 inhibited the growth of subcutaneous liver cancer in immunocompetent mice (P < 0.05), yet TP5 had no direct inhibitory effect on the proliferation of tumor cells cultured in vitro. Besides, a high dose of TP5 could not inhibit the growth of subcutaneous liver cancer in immunocompromised mice. Furthermore, TP5 promoted the infiltration of CD4 and CD8 T cells but decreased MDSCs in the subcutaneous tumor microenvironment of immunocompetent mice. TP5 did not affect the levels of ROS, IL-6, and NO in MDSCs. Lastly, arginine-deficient TP5 could not inhibit the growth of subcutaneous liver cancer in immunocompetent mice. Accordingly, TP5 but not arginine-deficient TP5 promoted the increase in the proportion of viable CD4 and CD8 T cells cultured in vitro. These results suggest that TP5 may inhibit the growth of liver cancer by increasing T cell number in the liver cancer microenvironment.
thymopentin ; hepatocellular carcinoma ; tumor microenvironment ; arginine ; T cells

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.