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Japanese encephalitis virus (JEV) genotype dominance has shifted to genotype I (GI) from genotype III (GIII) in China as demonstrated by molecular epidemiological surveillance. In this study, we performed a serological survey in JEV-non-vaccinated pigs to confirm JEV genotype shift at the sero-epidemiological level. The average ratio of GI/GIII infection was 1.87, suggesting co-circulation of GI and GIII infections with GI infection being more prevalent in pigs in China. To gain an insight into the reasons for this JEV genotype shift, the replication kinetics of seven recently-isolated JEV isolates including three GI strains and four GIII strains were compared in mosquito C6/36 cells, chicken fibroblast cells (DF-1) and porcine iliac artery endothelial cells (PIEC). We observed that GI strains replicated more efficiently than GIII strains in DF-1 and PIEC cells, particularly in DF-1 cells with titers reaching 22.9–225.3 fold higher than GIII strains. This shows an enhanced replication efficiency of GI viruses in avian cells. To examine this enhanced replication efficiency in vivo, young domestic ducklings were used as the animal model and inoculated with GI and GIII strains at day 2 post-hatching. We observed that GI-inoculated ducklings developed higher viremia titers and displayed a comparatively longer viremic duration than GIII-inoculated ducklings. These results conform to the hypothesis of an enhanced replication efficiency for GI viruses in birds. There are 36 amino acid differences between GI and GIII viruses, some of which may be responsible for the enhanced replication efficiency of GI viruses in birds. Based on these findings, we speculated that the enhanced replication of GI viruses in birds would have resulted in higher exposure and therefore infection in mosquitoes, which could result in an increased transmission efficiency of GI viruses in the birds-mosquitoes-birds enzootic transmission cycle, thereby contributing to JEV genotype shift.

Assessing heavy metal pollution in river sediments and identifying the key factors contributing to metal pollution are critical components for devising river environmental protection and remediation strategies to protect human and ecological health. This is especially important in urban areas where metals from a wide range of sources contribute to sediment pollution. In this study, the metal enrichment factor (EF) was used to measure the watershed distribution of Cu, Zn, Pb and Cd in sediments in the Wen-Rui Tang urban river system in Wenzhou, Eastern China. The Geographical Detector Method (GDM) was specifically evaluated for its ability to analyze spatial relationships between metal EFs and their anthropogenic and natural control factors, including densities of industry (DI), livestock (DL), service industries (DS), population (DP), and roads (DR), along with agricultural area (AG), sediment total organic carbon (TOC), and soil types (ST). Results showed that the watershed was highly contaminated by all metals with an EF trend of Cd ≫ Zn N Cu N Pb. The spatial distribution of EFs demonstrated high contamination of all metals in the southwestern region of the watershed where industrial activities were concentrated, and higher Cu and Zn concentrations in the northeastern region having a high density of livestock production. GDM results identified DI as the dominant determinant for all metals, while TOC and ST were determined to have a moderate secondary influence for Zn, Pb and Cd. Additionally, GDM revealed several additive and nonlinear interactions between anthropogenic and natural factors influencing metal concentrations. Compared to other correlation, multiple linear regression and geographically weighted regression, GDM demonstrated distinct advantages of being able to assess both categorical and continuous variables and determine both single and multiple factor interactions. These attributes provide a more comprehensive understanding of metal spatial

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Metagenomic analysis of mosquito-borne and mosquito-specific viruses is useful to understand the viral diversity and for the surveillance of pathogens of medical and veterinary importance. Yunnan province is located at the southwest of China and has rich abundance of mosquitoes. Arbovirus surveillance is not conducted regularly in this province particularly at animal farms, which have public health as well as veterinary importance. Here, we have analyzed 10 pools of mosquitoes belonging to Culex tritaeniorhyncus, Aedes aegypti, Anopheles sinensis, and Armigeres subalbatus species, collected from different animal farms located at Yunnan province of China by using metagenomic next-generation sequencing technique. The generated viral metagenomic data reveal that the viral community matched by the reads was highly diverse and varied in abundance among animal farms, which contained more than 19 viral taxonomic families, specific to vertebrates, invertebrates, fungi, plants, protozoa, and bacteria. Additionally, a large number of viral reads were related to viruses that are non-classified. The viral reads related to animal viruses included parvoviruses, anelloviruses, circoviruses, flaviviruses, rhabdoviruses, and seadornaviruses, which might be taken by mosquitoes from viremic animal hosts during blood feeding. Notably, the presence of viral reads matched with Japanese encephalitis virus, Getah virus, and porcine parvoviruses in mosquitoes collected from different geographic sites suggested a potential circulation of these viruses in their vertebrate hosts. Overall, this study provides a comprehensive knowledge of diverse viral populations present at animal farms of Yunnan province of China, which might be a potential source of diseases for humans and domestic animals.

The theory of classical variational assimilation assumes that biases are unbiased Gaussian. This article investigates the bias characteristic estimate and the bias correction of Geostationary Interferometric Infrared Sounder (GIIRS) on board the FY-4A satellite. Quality-control procedures for GIIRS long-wave temperature channels brightness temperature include cloud detection based on the Advanced Geosynchronous Radiation Imager (AGRI) and outlier removal. The mean biases for most channels are within ±2 K after quality control except for the contaminated channels. Statistical evaluation of the first-guess departures of GIIRS observations in GRAPES (Global/Regional Assimilation and Prediction Enhanced System) global 4D-Var reveal that biases for the long-wave temperature channels depend on fields of view (FOVs) and latitudinal distribution. Additionally, the diurnal variation of biases is obvious only for the upper tropospheric channels, and the biases for high tropospheric channels are smaller than the biases for low tropospheric channels. Finally, off-line bias correction that was used in this study accounts for the field-of-regard (FOR) dependence and the diurnal variation bias characteristics of GIIRS. After bias correction, the results show that biases of long-wave temperature sounding channels are reduced to ±0.02 K, and the standard deviations are less than 1 K except for the contaminated channels. The probability density function of the differences between observations and simulations for some common assimilation channels is closer to the unbiased Gaussian distribution.