Liver Damage Associated with Polygonum multiflorum

Objective. To summarize the characteristics and analysis of relevant factors and to give references for prevention and further study of liver damage associated with Polygonum multiflorum Thunb. (HSW), we provide a systematic review of case reports and case series about liver damage associated with HSW. Methods. An extensive search of 6 medical databases was performed up to June 2014. Case reports and case series involving liver damage associated with HSW were included. Results. This review covers a total of 450 cases in 76 articles. HSW types included raw and processed HSW decoction pieces and many Chinese patent medicines that contain HSW. Symptoms of liver damage occur mostly a month or so after taking the medicine, mainly including jaundice, fatigue, anorexia, and yellow or tawny urine. Of the 450 patients, two cases who received liver transplantation and seven who died, the remaining 441 cases recovered or had liver function improvement after discontinuing HSW products and conservative care. Conclusion. HSW causes liver toxicity and may cause liver damage in different degrees and even lead to death; most of them are much related to long-term and overdose of drugs. Liver damage associated with HSW is reversible, and, after active treatment, the majority can be cured. People should be alert to liver damage when taking HSW preparations

Mapping Winter Wheat with Optical and SAR Images Based on Google Earth Engine in Henan Province, China

The timely and accurate acquisition of winter wheat acreage is crucial for food security. This study investigated the feasibility of extracting the spatial distribution map of winter wheat in Henan Province by using synthetic aperture radar (SAR, Sentinel-1A) and optical (Sentinel-2) images. Firstly, the SAR images were aggregated based on the growth period of winter wheat, and the optical images were aggregated based on the moderate resolution imaging spectroradiometer normalized difference vegetation index (MODIS-NDVI) curve. Then, five spectral features, two polarization features, and four texture features were selected as feature variables. Finally, the Google Earth Engine (GEE) cloud platform was employed to extract winter wheat acreage through the random forest (RF) algorithm. The results show that: (1) aggregated images based on the growth period of winter wheat and sensor characteristics can improve the mapping accuracy and efficiency; (2) the extraction accuracy of using only SAR images was improved with the accumulation of growth period. The extraction accuracy of using the SAR images in the full growth period reached 80.1%; and (3) the identification effect of integrated images was relatively good, which makes up for the shortcomings of SAR and optical images and improves the extraction accuracy of winter wheat

Risk transboundary transmission areas and driving factors of brucellosis along the borders between China and Mongolia

Objective: Brucellosis is a common and neglected zoonotic infectious disease worldwide caused by Brucella. However, transboundary transmissions among countries, particularly those with high incidences, are seldom investigated. In the present study, by taking China and Mongolia as examples, we aim to identify transboundary transmission risk and driving factors of brucellosis along borders. Methods: 167 brucellosis outbreak locations along the border between China and Mongolia were collected. Wildlife distribution and cross-border activities were mapped. Maximum entropy approach modeling was conducted to predict the potential risk of prevalence of brucellosis with meteorological factors, geographical environment, economic development, living habits et al. The accuracy of the models was assessed by the area under the receiver operating characteristic (ROC) curve (AUC), Kappa test, and correctly classified instances (CCI). Results: The spatial model performed excellent predictive performance with the predictor variables of soils, pastures, goat density, mean precipitation of the wettest month, temperature seasonality, and population density, which with the contribution and permutation important in 27.2 %, 31.9; 23.3 %, 6.8; 18.0 %, 17.2; 11.2 %, 18.1; 10. 3 %, 15.2; 10.0 %, 10.8. The calculated AUC, SD, Kappa, and CCI are 0.870, 0.001, 0.882, and 0.883, respectively. The distribution map of brucellosis showed high-risk areas along the borders. Conclusions: Our study identified high-risk areas and the driving effect of brucellosis along the borders between China and Mongolia. Moreover, there is the possibility of cross-border wildlife activities in high-risk areas, which increases the risk of cross-border brucellosis transmission. The funding provides clues for cooperative prevention and control of brucellosis by reducing transboundary transmission

Host Antiviral Factors Hijack Furin to Block SARS-CoV-2, Ebola Virus, and HIV-1 Glycoproteins Cleavage

AbstractViral envelope glycoproteins are crucial for viral infections. In the process of enveloped viruses budding and release from the producer cells, viral envelope glycoproteins are presented on the viral membrane surface as spikes, promoting the virus's next-round infection of target cells. However, the host cells evolve counteracting mechanisms in the long-term virus-host co-evolutionary processes. For instance, the host cell antiviral factors could potently suppress viral replication by targeting their envelope glycoproteins through multiple channels, including their intracellular synthesis, glycosylation modification, assembly into virions, and binding to target cell receptors. Recently, a group of studies discovered that some host antiviral proteins specifically recognized host proprotein convertase (PC) furin and blocked its cleavage of viral envelope glycoproteins, thus impairing viral infectivity. Here, in this review, we briefly summarize several such host antiviral factors and analyze their roles in furin cleavage of viral envelope glycoproteins, aiming at providing insights for future antiviral studies

Ag85a-S2 Activates cGAS-STING Signaling Pathway in Intestinal Mucosal Cells

Brucellosis is a zoonotic disease caused by Gram-negative bacteria. Most of the brucellosis vaccines in the application are whole-bacteria vaccines. Live-attenuated vaccines are widely used for brucellosis prevention in sheep, goats, pigs, and cattle. Thus, there is also a need for an adjuvanted vaccine for human brucellosis, because the attenuated Brucella vaccines now utilized in animals cause human illness. Here, we developed a live-attenuated Brucella suis strain 2 vaccine (S2) adjuvanted with Ag85a (Ag85a-S2). We found that Ag85a-S2 activated cGAS-STING pathways both in intestinal mucosal cells in vivo and in the BMDM and U937 cell line in vitro. We demonstrated that the cGAS knockout significantly downregulated the abundance of interferon and other cytokines induced by Ag85a-S2. Moreover, Ag85a-S2 triggered a stronger cellular immune response compared to S2 alone. In sum, Ag85a-S2-mediated enhancement of immune responses was at least partially dependent on the cGAS-STING pathway. Our results provide a new candidate for preventing Brucella pathogens from livestock, which might reduce the dosage and potential toxicity compared to S2

Mapping Winter Wheat with Optical and SAR Images Based on Google Earth Engine in Henan Province, China

The timely and accurate acquisition of winter wheat acreage is crucial for food security. This study investigated the feasibility of extracting the spatial distribution map of winter wheat in Henan Province by using synthetic aperture radar (SAR, Sentinel-1A) and optical (Sentinel-2) images. Firstly, the SAR images were aggregated based on the growth period of winter wheat, and the optical images were aggregated based on the moderate resolution imaging spectroradiometer normalized difference vegetation index (MODIS-NDVI) curve. Then, five spectral features, two polarization features, and four texture features were selected as feature variables. Finally, the Google Earth Engine (GEE) cloud platform was employed to extract winter wheat acreage through the random forest (RF) algorithm. The results show that: (1) aggregated images based on the growth period of winter wheat and sensor characteristics can improve the mapping accuracy and efficiency; (2) the extraction accuracy of using only SAR images was improved with the accumulation of growth period. The extraction accuracy of using the SAR images in the full growth period reached 80.1%; and (3) the identification effect of integrated images was relatively good, which makes up for the shortcomings of SAR and optical images and improves the extraction accuracy of winter wheat