The origin and evolution of emerged swine acute diarrhea syndrome coronavirus with zoonotic potential.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly discovered alphacoronavirus with zoonotic potential that causes diarrhea and vomiting mainly in piglets. Having emerged suddenly in 2017, the prevailing opinion is that the virus originated from HKU2, an alphacoronavirus whose primary host is bats, and at some unknown point achieved interspecies transmission via some intermediate. Here, we further explore the evolutionary history and possible cross-species transmission event for SADS-CoV. Coevolutionary analysis demonstrated that HKU2 may have achieved host switch via SADS-related (SADSr)-CoV, which was isolated from the genus Rhinolophus in 2017. SADS-CoV, HKU2, and SADSr-CoV share similar codon usage patterns and showed a lower tendency to use CpG, which may reflect a method of immune escape. The analyses of virus-host coevolution and recombination support SADSr-CoV is the direct source of SADS-CoV that may have undergone recombination events during its formation. Structure-based spike glycoprotein variance analysis revealed a more nuanced evolutionary pathway to receptor recognition for host switch. We did not find a possible positive selection site, and the dN/dS of the S gene was only 0.29, which indicates that the current SADS-CoV is slowly evolving. These results provide new insights that may help predict future cross-species transmission, and possibly surveil future zoonotic outbreaks and associated public health emergencies.

Epidemiological and etiological analysis of a case cluster caused by norovirus in a nursing home in Lanzhou

Objective To understand the epidemiology and etiology of a cluster of cases with gastroenteritis in a nursing home in Anning district of Lanzhou, and to provide a scientific evidence for the prevention and control of norovirus diarrhea in community nursing centers. Methods From January 28 to February 4 2021, an epidemiological investigation was conducted on all diarrhea cases, nursing staff and chefs in a nursing home in Anning district, Lanzhou city.Samples of patients′ anal swabs, feces, vomitus were collected for norovirus detection by real-time fluorescent PCR.ORF1/ORF2 junction region of norovirus in some selected positive samples（Ct value ≤ 25） was sequenced.MEGA-X software was used to construct a phylogenetic tree for genetic evolution analysis using the neighboring method. Results The first case was confirmed on January20,2021,and the number of cases peaked during January 25and 29.A total of 58clinically diagnosed cases were reported,57were older people,with an incidence of（57/360,15.83%）.Diarrhea（50/58,86.21%）,vomiting（35/58,60.34%）,nausea（13/58,22.41%）and abdominal pain（6/58,10.34%）were common symptoms,all cases were mild.Fifty-three asymptomatic cases were detected among chefs,housekeepers and nurses.A total of 163specimens were tested,the positive rate of norovirus GⅡwas 49.08%（80/163）.The positive rate of fecal samples collected from nurses,chefs and housekeepers was 48.62%（53/109）,and was11.11%（2/18）in environmental surface swabs.The possibility of other pathogenic infections such as SARS-CoV-2was ruled out by further tests.Thirteen positive samples were selected for sequencing,and 9were successfully sequenced,they were all recombinant GⅡ.4Sydney＿2012 [P16]genotypes,forming an independent cluster,while in a large evolutionary branch with the 2020GⅡ.10 [P16]and 2019GⅡ.2 [P16]virus strains in Lanzhou city,showing a relative close genetic connection. Conclusions GⅡ.4Sydney＿2012[P16]genotype of norovirus is found to be causative pathogen of this outbreak,and close contact is the main reason of the outbreak and persistence of the infection,so asymptomatic infections of norovirus play an important role in the disease spreading.Therefore,public health management in nursing homes and other centralized nursing facilities should be strengthened especially for asymptomatic workers in order to prevent virus transmission.

Dynamics and Determinants of the Grain Yield Gap in Major Grain-Producing Areas: A Case Study in Hunan Province, China.

Understanding the dynamics of the grain yield gap (YGAP) and its causative factors is essential for optimizing the layout of grain production and addressing the food crisis, especially in countries with a huge population and less cultivated land, such as China. In the study, a spatial analysis- and machine learning-based framework for YGAP analysis was developed, taking Hunan Province, China, as an application. The results showed that the average YGAP in Hunan Province gradually narrowed from 1990 to 2018, and the YGAPs narrowed in 116 counties. Of which, 26 counties narrowed by more than 4 t ha-1, 58 counties narrowed from 2-4 t ha-1, and 32 counties narrowed within 2 t ha-1. Additionally, we found that the GDP per capita (GDPPC), sunshine hours (SH), per capita annual net income of farmers (PCAI), and rural electricity consumption (REC) play a key role in YGAP change, and the importance of human investment to the YGAP decreased, while socioeconomic environment became the dominant factor that influenced grain production. Comprehensively, the relatively great potential for grain yield growth was generated in sixty-four counties, which are mainly located in the northern, central, and southern Hunan. The findings suggest that it is necessary to consider the trends of economic development in rural areas and population migration in agricultural management. This work provides insights into yield gap dynamics and may contribute to sustainable agricultural management in Hunan Province, China, and other similar regions.