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It is a global issue to set up a practical, sensitive, and useful model to eradicate or mitigate the coronavirus disease 2019 (COVID-19). Taking Central China's Hubei Province for example, three models were established. Firstly, a susceptible-probable-infectious-recovered (SPIR) model was proposed to predict the monthly number of confirmed and susceptible cases in each city. Next, an epidemic prefecture clustering model was set up to find proper vaccine delivery sites, according to the distance of each city. Finally, a dynamic material delivery optimization model was established for multiple epidemic prefectures, aiming to speed up vaccine production and storage in each delivery site. [ABSTRACT FROM AUTHOR]

Background: Accurate estimation of food portion sizes remains an important challenge in dietary data collection. The present study aimed to develop a food atlas with adequate visual reference to improve the accuracy of dietary surveys in China. Methods: A food atlas for dietary surveys in China was developed using three visual reference systems, namely, regularly placed food portions, the two‐dimensional background coordinates and common objects known in daily life. The atlas was validated by estimating a meal before and after using the food atlas, and differences in weight estimation were compared using a paired t‐test. In total, 50 college students participated in the study. Results: After determination of food varieties; design of the food display; purchase, processing, cooking and weighing of food; photographing food; post‐image processing and data processing, a total of 799 pictures of 303 types of food and two types of tableware were produced. The mean value of food weight estimated with the atlas was closer to the actual weight, and the variation range of these values was smaller and more stable than that estimated without the atlas. The differences estimated before and after using the atlas for all foods were significant (P < 0.05). Comparing the differences in weight before using the atlas, the error ranges of food samples were reduced. Conclusions: A food atlas has been developed for a retrospective dietary survey in China, which can be used to enable a better understanding of nutritional adequacy in the Chinese population. [ABSTRACT FROM AUTHOR]

• We previously developed GA-HA nanoparticles as liver-targeting drug carriers. • Adenine inhibits hepatic carcinoma cell proliferation time- and dose-dependently. • GA-HA NPs enhanced Ade liver-targeting and cellular uptake in vitro and in vivo. • Ade/GA-HA NPs showed good anti-tumor effects against HCC with good biocompatibility. • Ade/GA-HA NPs may serve as a liver-targeting drug delivery system for clinical use. Hepatocellular carcinoma (HCC), a common malignancy in China and globally, is primarily treated through surgical resection and liver transplantation, with chemotherapy as a significant synergistic option. Adenine (Ade), a nucleobase, exhibits antitumor effects by blocking human hepatic carcinoma cells in S phase and inhibiting tumor cell proliferation. However, its use is limited owing to its low solubility, poor targeting ability, and nephrotoxicity. Therefore, liver-targeting drug delivery systems have attracted considerable attention for the treatment of HCC. In this study, we explored the liver-targeting efficacy and antitumor effect of adenine-loaded glycyrrhetinic acid-modified hyaluronic acid (Ade/GA-HA) nanoparticles in vitro and in vivo. The GA-HA nanoparticles possessed obvious targeting specificity toward liver cancer cells, which was mainly achieved by the specific binding of the GA ligand to the GA receptor that was highly expressed on the liver cell membrane. In vitro and in vivo results showed that Ade/GA-HA nanoparticles could inhibit liver cancer cell proliferation and migration, promote apoptosis, and significantly inhibit the growth of tumor tissues. Altogether, this study is the first to successfully demonstrate that the targeting activity and antitumor effect of Ade against HCC are enhanced by using GA-HA nanoparticles in vitro and in vivo. [ABSTRACT FROM AUTHOR]

Porcine epidemic diarrhea (PED) is a highly contagious, intestinal infectious disease in pigs, characterized by severe diarrhea, vomiting and dehydration. PED is widely epidemic in China as well as in many eastern Asian and America countries, causing tremendous losses in pig industry. However, little was known about the disease frequency and the associated risk factors of PED in pig farms. A cross-sectional study was conducted to estimate the herd prevalence and to identify the potential risk factors of porcine epidemic diarrhea virus (PEDV) infection of pig farms (≥100 pigs) in Junan county, China. A two-stage random sampling strategy was adopted, and a total of 751 fecal samples from suckling piglets of 82 farms were collected and tested by RT-PCR and sequencing for PEDV. Meanwhile, information on the putative risk factors of PEDV infection of those farms were collected in forms of questionnaires, followed by a descriptive analysis, univariable and multivariable logistic regression analysis. The results showed that the herd-level true prevalence of PEDV infection of pig farms in Junan was 35.16 % (95 %CI: 22.91–53.89); there were two variables significantly associated with PEDV infection, which were 'having more than 1000 slaughter pigs per annum' (OR = 5.42, 95 %CI: 1.19–24.72), and 'Weaning at 21−25 days' old' (OR = 4.50, 95 %CI:1.25−16.20). The research suggested that PED was highly endemic in pig farms in Junan county; larger herd size and weaning at an earlier age were potential risk factors associated with PEDV infection in pig farms in Junan. This study set an example in the research on herd-level prevalence of PEDV infection and risk factors associated with PEDV infection, and the results were of practical significance for the future planning of prevention and control of PED in Junan or other areas of China. [ABSTRACT FROM AUTHOR]