Background: The World Health Organization declared mpox an international public health emergency. Since January 1, 2022, China has been ranked among the top 10 countries most affected by the mpox outbreak globally. However, there is a lack of spatial epidemiological studies on mpox, which are crucial for accurately mapping the spatial distribution and clustering of the disease. Objective: This study aims to provide geographically accurate visual evidence to determine priority areas for mpox prevention and control. Methods: Locally confirmed mpox cases were collected between June and November 2023 from 31 provinces of mainland China excluding Taiwan, Macao, and Hong Kong. Spatiotemporal epidemiological analyses, including spatial autocorrelation and regression analyses, were conducted to identify the spatiotemporal characteristics and clustering patterns of mpox attack rate and its spatial relationship with sociodemographic and socioeconomic factors. Results: From June to November 2023, a total of 1610 locally confirmed mpox cases were reported in 30 provinces in mainland China, resulting in an attack rate of 11.40 per 10 million people. Global spatial autocorrelation analysis showed that in July (Moran I=0.0938; P=.08), August (Moran I=0.1276; P=.08), and September (Moran I=0.0934; P=.07), the attack rates of mpox exhibited a clustered pattern and positive spatial autocorrelation. The Getis-Ord Gi* statistics identified hot spots of mpox attack rates in Beijing, Tianjin, Shanghai, Jiangsu, and Hainan. Beijing and Tianjin were consistent hot spots from June to October. No cold spots with low mpox attack rates were detected by the Getis-Ord Gi* statistics. Local Moran I statistics identified a high-high (HH) clustering of mpox attack rates in Guangdong, Beijing, and Tianjin. Guangdong province consistently exhibited HH clustering from June to November, while Beijing and Tianjin were identified as HH clusters from July to September. Low-low clusters were mainly located in Inner Mongolia, Xinjiang, Xizang, Qinghai, and Gansu. Ordinary least squares regression models showed that the cumulative mpox attack rates were significantly and positively associated with the proportion of the urban population (t0.05/2,1=2.4041 P=.02), per capita gross domestic product (t0.05/2,1=2.6955; P=.01), per capita disposable income (t0.05/2,1=2.8303; P=.008), per capita consumption expenditure (PCCE; t0.05/2,1=2.7452; P=.01), and PCCE for health care (t0.05/2,1=2.5924; P=.01). The geographically weighted regression models indicated a positive association and spatial heterogeneity between cumulative mpox attack rates and the proportion of the urban population, per capita gross domestic product, per capita disposable income, and PCCE, with high R2 values in north and northeast China. Conclusions: Hot spots and HH clustering of mpox attack rates identified by local spatial autocorrelation analysis should be considered key areas for precision prevention and control of mpox. Specifically, Guangdong, Beijing, and Tianjin provinces should be prioritized for mpox prevention and control. These findings provide geographically precise and visualized evidence to assist in identifying key areas for targeted prevention and control.

Streptococcus suis is an important swine bacterial pathogen that activates macrophages to secrete inflammatory cytokines. Primary porcine alveolar macrophages (PAMs) are inconvenient to obtain, but it is unknown whether immortalized PAM-Tang cells can replace them as a better cell model for the study of the interaction between S. suis and macrophages. In this study, the phagocytic integrity, polarization, and pro-inflammatory cytokine secretion of PAM-Tang cells were confirmed by live-cell imaging, electron microscopy, confocal microscopy, and ELISA. Interestingly, the S. suis serotype 9 avirulent strain W7119 induced higher levels of adhesion and pro-inflammatory cytokines in PAM-Tang cells than the S. suis serotype 2 virulent strain 700794. Prolonged incubation with S. suis caused more cytotoxic cell damage, and the virulent strain induced higher levels of cytotoxicity to PAM-Tang cells. The virulent strain also induced higher levels of apoptosis in PAM-Tang cells, as shown by terminal deoxynucleotidyl transferase (TdT)-mediated dUTP-biotin nick end labeling (TUNEL) assay. In addition, it is the first report of virulent and avirulent S. suis inducing PAM-Tang polarization towards pro-inflammatory M1 macrophages and p53- and caspase-dependent apoptosis in PAMs. Taken together, this study contributes to a better understand of interactions between macrophages and S. suis isolates of different virulence, and confirms that PAM-Tang cells provide a long-term, renewable resource for investigating macrophage infections with bacteria.

Background: Robinin possesses certain antioxidative and anti-inflammatory properties. However, its mechanisms of action in cardiac hypertrophy (CH) and fibrosis remain inadequately explored. Methods: An in vitro model of CH was established using angiotensin II-treated rat H9c2 cardiomyocytes treated with escalating concentrations of Robinin. For the in vivo model, pulmonary heart disease-induced CH in rats was induced by chronic hypercapnia and TAC. Myocardial cell markers were evaluated through qRT-PCR, Western blotting, ELISA, cellular immunofluorescence, and HE staining. The role of SIRT1 in Robinin’s effects was determined using pharmacological inhibition with SIRT1-IN-1. Results: In vitro, Robinin suppressed hypertrophic (ANP, BNP, β-MHC) and fibrotic markers (MyHC, Collagen I, TGF-β1) and reduced NLRP3 components (IL-1β, IL-18, ASC, Caspase-1) and oxidative stress (OS, ↓MDA, ↑SOD/HO-1/Nrf2) in a dose-dependent manner. These effects were mediated by SIRT1 upregulation and NF-κB inactivation. Crucially, SIRT1 inhibition abolished Robinin’s protection against hypertrophy and inflammation. In vivo, Robinin attenuated pulmonary heart disease-induced hypertrophy, fibrosis, NLRP3 activation, and OS while restoring SIRT1/NF-κB balance. Conclusion: Robinin alleviates CH in pulmonary heart disease by modulating the SIRT1/NF-κB pathway to suppress OS and NLRP3 inflammasome activation, establishing its novel therapeutic potential.

Atrazine (ATR) is a widely used herbicide that persists in aquatic environments, raising concerns regarding its long-term immunotoxicity. As a central immune organ, the spleen represents a potential toxicological target, yet the impact of prolonged ATR ingestion via drinking water on splenic apoptosis and immune exhaustion remains unclear. In this study, male C57BL/6 N mice received ATR in drinking water at 0, 1.5 mg/L or 150 mg/L for 24 or 48 weeks. Spleen index, histopathology, peripheral blood leukocytes, serum cytokines, splenocyte apoptosis, T-cell exhaustion-like phenotype-related markers and RIG-I/MAVS signaling were evaluated. Prolonged ATR exposure increased spleen index in a dose- and time-dependent manner and caused progressive white pulp hyperplasia, disruption of splenic architecture, red pulp congestion and macrophage accumulation. Serum IL-6 and TNF-α levels were elevated, accompanied by reduced lymphocyte counts and increased neutrophils and monocytes in peripheral blood. Splenocyte apoptosis was enhanced, with upregulation of Bax, Casp3 and cleaved caspase-3. In parallel, Pdcd1 (PD-1), Ctla4, Lag3 and Tigit expression and PD-1 protein levels were significantly increased, with PD-1-positive regions overlapping with TUNEL-positive cells. RIG-I and Mavs mRNA and RIG-I protein were also upregulated. These results demonstrate that prolonged ATR exposure via drinking water promotes splenic apoptosis and induces an immune exhaustion-like state in mice, associated with the activation of RIG-I/MAVS-linked apoptotic signaling.

BACKGROUND The World Health Organization declared mpox an international public health emergency. Since January 1, 2022, China has been ranked among the top 10 countries most affected by the mpox outbreak globally. However, there is a lack of spatial epidemiological studies on mpox, which are crucial for accurately mapping the spatial distribution and clustering of the disease. OBJECTIVE This study aims to provide geographically accurate visual evidence to determine priority areas for mpox prevention and control. METHODS Locally confirmed mpox cases were collected between June and November 2023 from 31 provinces of mainland China excluding Taiwan, Macao, and Hong Kong. Spatiotemporal epidemiological analyses, including spatial autocorrelation and regression analyses, were conducted to identify the spatiotemporal characteristics and clustering patterns of mpox attack rate and its spatial relationship with sociodemographic and socioeconomic factors. RESULTS From June to November 2023, a total of 1610 locally confirmed mpox cases were reported in 30 provinces in mainland China, resulting in an attack rate of 11.40 per 10 million people. Global spatial autocorrelation analysis showed that in July (Moran I=0.0938; P=.08), August (Moran I=0.1276; P=.08), and September (Moran I=0.0934; P=.07), the attack rates of mpox exhibited a clustered pattern and positive spatial autocorrelation. The Getis-Ord Gi* statistics identified hot spots of mpox attack rates in Beijing, Tianjin, Shanghai, Jiangsu, and Hainan. Beijing and Tianjin were consistent hot spots from June to October. No cold spots with low mpox attack rates were detected by the Getis-Ord Gi* statistics. Local Moran I statistics identified a high-high (HH) clustering of mpox attack rates in Guangdong, Beijing, and Tianjin. Guangdong province consistently exhibited HH clustering from June to November, while Beijing and Tianjin were identified as HH clusters from July to September. Low-low clusters were mainly located in Inner Mongolia, Xinjiang, Xizang, Qinghai, and Gansu. Ordinary least squares regression models showed that the cumulative mpox attack rates were significantly and positively associated with the proportion of the urban population (t0.05/2,1=2.4041 P=.02), per capita gross domestic product (t0.05/2,1=2.6955; P=.01), per capita disposable income (t0.05/2,1=2.8303; P=.008), per capita consumption expenditure (PCCE; t0.05/2,1=2.7452; P=.01), and PCCE for health care (t0.05/2,1=2.5924; P=.01). The geographically weighted regression models indicated a positive association and spatial heterogeneity between cumulative mpox attack rates and the proportion of the urban population, per capita gross domestic product, per capita disposable income, and PCCE, with high R2 values in north and northeast China. CONCLUSIONS Hot spots and HH clustering of mpox attack rates identified by local spatial autocorrelation analysis should be considered key areas for precision prevention and control of mpox. Specifically, Guangdong, Beijing, and Tianjin provinces should be prioritized for mpox prevention and control. These findings provide geographically precise and visualized evidence to assist in identifying key areas for targeted prevention and control.