Chunjie Xu

Background: Visceral leishmaniasis (VL) remains a fatal neglected tropical disease with substantial global burden. The Group of Twenty (G20) encompasses both endemic and non-endemic nations, yet comprehensive multi-country assessments of VL trends and future projections are limited. This study aims to evaluate the 33-year epidemiological transition of VL across G20 countries and forecast its trajectory to 2043. Methodology/Principal findings: We extracted VL-related prevalence, incidence, mortality, and disability-adjusted life years (DALYs) data for G20 countries from the Global Burden of Disease 2023 database (1990–2023). We employed joinpoint regression to identify trend inflection points, decomposition analysis to quantify drivers of change (population growth, aging, and epidemiological changes), and autoregressive integrated moving average (ARIMA) models to project trends to 2043. From 1990 to 2023, G20 countries showed significant declines in age-standardized prevalence rate (EAPC = -9.06%), incidence rate (EAPC = -9.06%), mortality rate (EAPC = -7.23%), and DALYs rate (EAPC = -7.40%). Saudi Arabia, Turkey, and India experienced the steepest declines, while Brazil exhibited the smallest reduction and the highest burden in 2023 (age-standardized DALY rate: 30.54 per 100,000). Burden was consistently higher in males and concentrated in children under 5 years, with a slight increase observed among those aged ≥95 years. Decomposition analysis revealed that changes in epidemiological rates were the primary driver of mortality (contributing -82.05%) and DALYs (-52.62%) reductions, counteracting the positive effects of population growth and aging. ARIMA projections (2024–2043) suggest a stabilization in mortality, a gradual decline in DALYs, and a subtle increase in incidence and prevalence rates, with persistent gender disparities. Conclusions/Significance: While the VL burden in G20 nations has significantly decreased, substantial national disparities are evident. Our analysis specifically identifies Brazil as the priority target for intensified control. Sustained surveillance and international cooperation are crucial to prevent a projected mild resurgence in new infections.

The role of long-term exposure to a comprehensive panel of particulate matter (PM) size fractions and extreme weather events in the development of incident

Hepatitis B (HB) poses a significant disease burden in Henan due to its high morbidity and prevalence. Traditional surveillance systems often suffer from r

Hypertension, dyslipidemia, and liver diseases often coexist as multimorbidity, yet its assocaition with environmental drivers like nighttime light (NL) and air pollution remain underexplored. This study investigates the independent and joint effects of NL, air pollutants, and PM2.5 components on multimorbidity risk. Based on data from the China Health and Retirement Longitudinal Study (2015–2020), we analyzed 11,216 adults aged 45 years and older who did not have multiple chronic conditions at baseline. We adjusted the covariates, including age, gender, education level, marital status, smoking status, drinking status, and sleep state. We employed Cox models that incorporated various combinations of these covariates to estimate the hazard ratios (HR). The exposure variables included NL, sulfur dioxide (SO₂), carbon monoxide (CO), ozone (O₃), nitrogen dioxide (NO₂), and particulate matter (PM₁, PM2.5, PM₁₀), along with components of PM2.5 (black carbon [BC], organic matter [OM], nitrate [NO₃⁻], sulfate [SO42-], and ammonium [NH4+]). Dose-response relationships and synergistic effects were quantified using restricted cubic spline functions and interaction analyses. During a median follow-up period of five years, 1,504 participants (13.4%) developed multiple conditions. A significant dose-response relationship (P < 0.05) was observed between the risks of multiple diseases and NL, as well as several air pollutants, including PM1, PM2.5, PM10, NO₂, SO₂, CO and components of PM2.5 (BC, OM, NO₃⁻, SO₄²⁻, and NH₄⁺), with the exception of O₃. The relative excess risk in interaction (RERI) for NL and PM₁ was 0.24 (95% CI: 0.01–0.46), for PM2.5 it was 0.26 (95% CI: 0.03–0.48), for O₃ it was 0.35 (95% CI: 0.11–0.58), and for ammonium (NH₄⁺) it was 0.25 (95% CI: 0.03–0.47), indicating synergistic risk. The most pronounced interactions were observed between NL and BC (HR= 1.85, 95% CI: 1.57–2.18) as well as NO₂ (HR = 1.63, 95% CI: 1.39–1.93). Concurrent exposure to high levels of NL and moderate levels of PM₂.₅ increased the risk by 61% (HR = 1.61, 95% CI: 1.29–1.99), while high levels of NL combined with black carbon resulted in an 85% increase in risk (HR = 1.85, 95% CI: 1.57–2.18). NL and air pollutants independently and synergistically elevate multimorbidity risk, with PM2.5 components (e.g., BC, NO3-) and O₃ exhibiting pronounced interactions. Policy interventions targeting light pollution reduction and air quality improvement are urgently needed to mitigate environmental health risks.

Diabetes or high blood sugar (D/HBS) is a major global public health challenge, with a particularly high burden among middle-aged and older adults in China. While traditional risk factors (e.g., obesity, sedentary behavior) are well-studied, the impacts of environmental factors such as nighttime light (NL), air pollution, and the normalized difference vegetation index (NDVI) on D/HBS remain underexplored. Using data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2015), we included 11,865 participants aged ≥ 45 years without baseline D/HBS. Cox proportional hazards models were employed to evaluate the independent effects of NL, air pollutants (PM₁, PM_2.5, NO₂, etc.), and NDVI on D/HBS risk, adjusting for confounders. Interaction effects, joint effects, and mediation effects were further analyzed. The median follow-up duration was 4.0 years. Among the 11,865 baseline participants, 371 developed incident D/HBS. NL was significantly associated with increased D/HBS risk (per IQR increase: HR = 1.15, 95% CI: 1.06-1.26). High exposure to PM_2.5 (Q4: HR = 1.46, 95% CI: 1.06-2.01) and NO₂ (Q4: HR = 1.44, 95% CI: 1.07-1.92) elevated risk, while higher NDVI (Q3: HR = 0.52, 95% CI: 0.37-0.72) showed a protective effect. Synergistic effects were observed between NL and PM_2.5 (RERI = 0.61, 95% CI: 0.13-1.09) or NO₃^- (RERI = 0.59, 95% CI: 0.11-1.08). Mediation analyses indicated that air pollutants, specifically NH₄⁺ (proportion = - 68.3%) and NO₃^- (proportion = - 64.1%), partially attenuated the protective role of NDVI. NL and air pollution are independent risk factors for D/HBS, with synergistic effects exacerbating disease risk. NDVI confers protection by reducing pollutant exposure. Comprehensive strategies targeting light pollution control, air quality improvement, and optimized green space planning are imperative. Future studies should integrate individualized exposure assessments and elucidate causal environmental-metabolic pathways.

Cardiovascular-kidney-metabolic (CKM) syndrome, characterized by interconnected cardiovascular, renal, and metabolic dysfunctions, poses a growing global health burden. While both light at night (LAN) and air pollutants have independently been linked to adverse health outcomes, their synergistic and joint effects on CKM syndrome risk remain poorly understood. This study aimed to assess the independent, interactive, and joint associations of LAN, air pollutants, and PM2.5 components with CKM syndrome. Data from 4,361 participants aged ≥ 45 years in the China Health and Retirement Longitudinal Study (CHARLS, 2011–2015) were analyzed. Cox proportional hazards regression models were employed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for CKM syndrome risk. Multiplicative and additive interactions between LAN and air pollutants were assessed using likelihood ratio tests and relative excess risk due to interaction (RERI). Joint effects were evaluated by categorizing exposures into tertiles. Over a median follow-up of 4.2 years, 792 incident CKM syndrome cases were identified. Adjusted models indicated that higher LAN exposure (highest vs. lowest quartile: HR = 1.46, 95% CI: 1.18–1.80) and increased levels of NO₂ (HR = 1.44, 95% CI: 1.18–1.75), PM2.5 (HR = 1.49, 95% CI: 1.19–1.87), PM10 (HR = 1.75, 95% CI: 1.40–2.18), NO₃⁻ (HR = 1.42, 95% CI: 1.15–1.75), and NH₄⁺ (HR = 1.42, 95% CI: 1.15–1.75) were independently associated with elevated CKM risk. Significant multiplicative interactions were observed between LAN and all pollutants except O₃, NO₃⁻, and NH₄⁺ (P for interaction < 0.05). In the additive interaction analysis, the RERI values ranged from 0.158 to 0.792, indicating a significant synergistic effect between LAN and air pollutants, which increases the risk of CKM syndrome. Joint exposure analysis showed that the combination of high LAN and high PM₁₀ increased CKM risk by 56.3% (HR = 1.563, 95% CI: 1.092–2.238), while moderate co-exposure to LAN and PM2.5 elevated risk by 33.4% (HR = 1.334, 95% CI: 0.872–2.041). This study provided evidence that LAN, air pollutants, and PM2.5 components were positively associated with CKM syndrome, and significant synergistic and joint effects existed, increasing the risk of CKM syndrome in older adults. These results highlighted the urgency of comprehensive environmental intervention measures and emphasized the necessity of incorporating multi-factor joint exposure assessment in future CKM syndrome research.

Tuberculosis (TB) is a bacterial infection caused by the pathogen Mycobacterium tuberculosis [1]. Despite significant global health advancements, TB remains the 13th leading cause of death and the second leading infectious killer after COVID-19, surpassing even HIV/AIDS. The consequences of TB are devastating for individuals, communities, and economies. Between 2015–2021, global efforts resulted in approximately […]

Introduction: Human brucellosis (HB) has re‐emerged as a critical public health threat in China, necessitating robust forecasting tools for early intervention. This study evaluates the seasonal autoregressive fractionally integrated moving average (SARFIMA) model's performance in predicting HB epidemics, comparing it with the widely used seasonal autoregressive integrated moving average (SARIMA).Methods: Monthly HB morbidity data from January 2012 to May 2023 in Henan were collected retrospectively and divided into training (January 2012 to December 2021) and testing (January 2022 to May 2023) segments to evaluate the predictive ability of SARFIMA, comparing it with the seasonal autoregressive integrated moving average (SARIMA). Sensitivity and secondary analyses were also conducted using HB incidence data in different periods in Henan and mainland China to confirm the predictive robustness.Results: HB incidence exhibited marked seasonality (peaks: May–June; troughs: December–January) and surged post‐2018 (annual increase: 34.9%). The analysis identified distinct SARIMA and SARFIMA configurations for different prediction horizons in Henan. 17‐step forecasts required autoregressive components with seasonal differencing, while 5‐step predictions benefited from moving average terms. The SARFIMA models consistently exhibited fractional differencing parameters (0.329–0.487), indicating persistent temporal dependencies in the data structure. Although the SARFIMA produced smaller forecast errors than the best SARIMA in both horizons, the forecast errors were still large, and the prediction intervals of the SARFIMA were wider than those of the SARIMA. Further cross‐validation and secondary analysis also showed that SARFIMA outperformed SARIMA in assessing HB epidemics.Conclusions: SARFIMA marginally improves HB forecasting accuracy over SARIMA by addressing long‐range dependence, but prediction reliability remains limited. Hybrid models integrating environmental/livestock data are recommended. Escalating HB incidence underscores urgent needs for livestock vaccination, public education on unpasteurized dairy risks, and real‐time surveillance to mitigate zoonotic transmission in high‐risk regions.

Azvudine (FNC) is a novel cytidine analogue that is widely used in the treatment of infectious diseases such as AIDS and COVID-19. Previous studies have demonstrated its anticancer activity in various cancer cell lines, including non-Hodgkin’s lymphomas and lung adenocarcinoma cell lines. However, its effects on hepatocellular carcinoma (HCC) and the underlying mechanisms remain unclear. This study aimed to investigate the anti-epithelial–mesenchymal transition (anti-EMT) activity of FNC and evaluate its potential application in HCC treatment. We found that FNC significantly inhibits the migration of the liver cancer cell line Huh7 by downregulating key EMT markers, such as matrix metalloproteinases (MMPs) and N-cadherin, at both the transcriptional and protein expression levels. Notably, we found that FNC inhibits HEY proteins, particularly HEY1, a transcriptional regulator of the Notch signalling pathway that is overexpressed in approximately 50% of HCC patients. To identify the primary target of FNC, microscale thermophoresis (MST) and molecular dynamics (MD) simulations were performed, revealing that FNC directly binds to Jagged1. This study provides valuable insights into the therapeutic potential of FNC in HCC treatment and elucidates its underlying mechanisms.

Azvudine (FNC) is a novel cytidine analogue widely used in the treatment of AIDS and COVID-19 infectious disease. Previous studies have demonstrated its anticancer activity in various cancer cell lines, including non-Hodgkin’s lymphomas and lung adenocarcinoma cell lines. However, its effects on hepatocellular carcinoma (HCC) and the underlying mechanisms remain unclear. This study aimed to investigate the anti-epithelial-mesenchymal transition (anti-EMT) activity of FNC and evaluate its potential application in HCC treatment. We found that FNC significantly inhibits the migration of the liver cancer cell line Huh7 by downregulating key EMT markers, such as matrix metalloproteinases (MMPs) and E-cadherin, at both transcriptional and protein expression levels. Notably, we found that FNC inhibits HEY proteins, particularly HEY1, a transcriptional regulator of the Notch signalling pathway that is overexpressed in approximately 50% of HCC patients. To identify the primary target of FNC, microscale thermophoresis (MST) and molecular dynamics (MD) simulations were performed, revealing that FNC directly binds to Jagged1. This study provides valuable insights into the therapeutic potential of FNC in HCC treatment and elucidates its underlying mechanisms.