BACKGROUND: Neglected tropical diseases (NTDs) and malaria pose a major health challenge, especially in low- and middle-income countries. METHODS: Initially, we performed a descriptive analysis of the Global Burden of Disease (GBD) 2021 database, categorizing data by subtypes. Next, linear regression models were employed to analyze temporal trends. We then utilized four predictive models to forecast the future burden. Additionally, we explored the relationship between estimated annual percentage change (EAPCs) and age-standardized rates (ASRs), as well as Human Development Index (HDI) scores for 2021. Furthermore, decomposition analysis was applied to assess the influence of aging, population dynamics, and epidemiological changes. Lastly, frontier analysis was conducted to examine the connection between disease burden and sociodemographic development. RESULTS: In 2021, NTDs and malaria contributed significantly to the global disease burden, with considerable disparities across genders, age groups, Socio-demographic Index (SDI) regions, GBD regions, and individual countries. From 1990 to 2021, both the number of cases and the associated ASRs have shown a recent downward trend. The EAPCs are positively correlated with ASRs and HDI scores. Projections indicate a continued decline in disease burden through 2046. Additionally, our decomposition analysis highlighted the positive impact of aging and epidemiological shifts on the reduction of the disease burden. Finally, frontier analysis revealed that countries and regions with higher SDI scores have greater potential for further reducing their health burden. CONCLUSION While the global burden of NTDs and malaria has improved overall, significant disparities remain across regions and countries. Our findings highlight the importance of implementing targeted intervention strategies and maintaining sustained investments to tackle the ongoing challenges.
Malaria/epidemiology* ; Humans ; Neglected Diseases/epidemiology* ; Global Burden of Disease/trends* ; Global Health/statistics & numerical data* ; Male ; Female ; Tropical Medicine ; Adult ; Cost of Illness ; Child, Preschool ; Middle Aged ; Adolescent ; Young Adult ; Infant

Objective:To analyze the changes of peripheral blood CD 4+ T lymphocyte subsets caused by nanosecond pulse ablation in C57BL/6J liver cancer mice and its effect on the immunity of liver cancer mice. Methods:According to the randomallocation, 32 female C57BL/6J mice weighing 18-20 g and aged 8-10 weeks were divided into the blank control group (Group A), the liver cancer control group (Group B), the radical liver lobectomy group (Group C), and the nanosecond pulse ablation treatment group (Group D), with 8 mice in each group. The in situ liver cancer models for mice in groups B, C, and D were established using Hepa 1-6 hepatoma cell line. On the 7th day after modeling, group C underwent liver lobectomy, and group D underwent nanosecond pulse ablation. After 7 days of treatment, the subtypes Th1, Th2, Th17 and Treg cell levels of CD 4+ T cells in the peripheral blood of the four groups of mice were detected by flow cytometry. Results:Flow cytometry was used to detect and analyze the proportions of CD 4+ T cell subsets Th1, Th2, Th17 and Treg in the peripheral blood of four groups of mice. Comparisons of each index among the groups showed statistically significant differences (all P<0.001). The proportion of Th1 cells detected by flow cytometry was (8.4±1.1) % in group A, (8.5±1.5)% in group D, (3.5±0.5)% in group B, and (2.4±0.5)% in group C. Both group A and Group D were higher than group B and group C, and the differences were statistically significant (all P<0.001). The proportion of Th2 cells detected by flow cytometry was (5.1±0.8)% in group A, (5.1±1.3)% in Group B, (5.4±0.9)% in group C, and (3.6±0.9)% in group D. The proportion of Th2 cells in groups A, B, and C was higher than that in group D, and the differences were statistically significant (all P<0.05). The proportion of Th17 cells detected by flow cytometry was (1.5±0.6)% in group A, (8.6±1.3)% in group B, (8.2±1.5)% in group C, and (1.7±0.3)% in group D. The proportion of Th17 cells in both group B and group C was higher than that in group A and group D, and the differences were statistically significant (all P<0.001). The proportion of Treg cells detected by flow cytometry was (7.0±0.9)% in group B, (6.8±0.9)% in group C, (3.8±0.8)% in group D, and (0.9±0.2)% in group A. The proportion of Treg in group B and group C was higher than that in group A and group D, and the difference was statistically significant (all P<0.001). Conclusion:Nanosecond pulse ablation for liver cancer in mice can regulate CD 4+ T cell subsets in peripheral blood, enhance the immune response of Th1 cells, inhibit the expression of Th2, Th17 and Treg cells, and improve the immunosuppressive state caused by liver cancer.

Objective:To analyze the changes of peripheral blood CD 4+ T lymphocyte subsets caused by nanosecond pulse ablation in C57BL/6J liver cancer mice and its effect on the immunity of liver cancer mice. Methods:According to the randomallocation, 32 female C57BL/6J mice weighing 18-20 g and aged 8-10 weeks were divided into the blank control group (Group A), the liver cancer control group (Group B), the radical liver lobectomy group (Group C), and the nanosecond pulse ablation treatment group (Group D), with 8 mice in each group. The in situ liver cancer models for mice in groups B, C, and D were established using Hepa 1-6 hepatoma cell line. On the 7th day after modeling, group C underwent liver lobectomy, and group D underwent nanosecond pulse ablation. After 7 days of treatment, the subtypes Th1, Th2, Th17 and Treg cell levels of CD 4+ T cells in the peripheral blood of the four groups of mice were detected by flow cytometry. Results:Flow cytometry was used to detect and analyze the proportions of CD 4+ T cell subsets Th1, Th2, Th17 and Treg in the peripheral blood of four groups of mice. Comparisons of each index among the groups showed statistically significant differences (all P<0.001). The proportion of Th1 cells detected by flow cytometry was (8.4±1.1) % in group A, (8.5±1.5)% in group D, (3.5±0.5)% in group B, and (2.4±0.5)% in group C. Both group A and Group D were higher than group B and group C, and the differences were statistically significant (all P<0.001). The proportion of Th2 cells detected by flow cytometry was (5.1±0.8)% in group A, (5.1±1.3)% in Group B, (5.4±0.9)% in group C, and (3.6±0.9)% in group D. The proportion of Th2 cells in groups A, B, and C was higher than that in group D, and the differences were statistically significant (all P<0.05). The proportion of Th17 cells detected by flow cytometry was (1.5±0.6)% in group A, (8.6±1.3)% in group B, (8.2±1.5)% in group C, and (1.7±0.3)% in group D. The proportion of Th17 cells in both group B and group C was higher than that in group A and group D, and the differences were statistically significant (all P<0.001). The proportion of Treg cells detected by flow cytometry was (7.0±0.9)% in group B, (6.8±0.9)% in group C, (3.8±0.8)% in group D, and (0.9±0.2)% in group A. The proportion of Treg in group B and group C was higher than that in group A and group D, and the difference was statistically significant (all P<0.001). Conclusion:Nanosecond pulse ablation for liver cancer in mice can regulate CD 4+ T cell subsets in peripheral blood, enhance the immune response of Th1 cells, inhibit the expression of Th2, Th17 and Treg cells, and improve the immunosuppressive state caused by liver cancer.