Molecular epidemiology and genetic diversity of canine coronavirus from domestic dogs in Chengdu, China from 2020 to 2021 using a multiplex RT-PCR.

Recent reports on identification of canine coronavirus (CCoV) in humans have emphasized the urgency to strengthen surveillance of animal CoVs. The fact that recombinations between CCoV with feline, porcine CoVs brought about new types of CoVs indicated that more attention should be paid to domestic animals like dogs, cats and pigs, and the CoVs they carried. However, there are about ten kinds of CoVs that infect above animals, and thus representative CoVs with zoonotic potentials were considered in this study. Multiplex RT-PCR against CCoV, Feline coronavirus (FCoV), porcine deltacoronavirus and porcine acute diarrhea syndrome coronavirus was developed to investigate the prevalence of CoVs from domestic dogs in Chengdu, Southwest China. Samples from a total of 117 dogs were collected from a veterinary hospital, and only CCoV (34.2%, 40/117) was detected. Therefore, this study focused on CCoV and its characteristics of S, E, M, N and ORF3abc genes. Compared with CoVs that are capable of infecting humans, CCoV strains showed highest nucleotide identity with the novel canine-feline recombinant detected from humans (CCoV-Hupn-2018). Phylogenetic analysis based on S gene, CCoV strains were not only clustered with CCoV-II strains, but also closely related to FCoV-II strains ZJU1617 and SMU-CD59/2018. As for assembled ORF3abc, E, M, N sequences, CCoV strains had the closest relationship with CCoV-II (B203_GZ_2019, B135_JS_2018 and JS2103). What's more, specific amino acid variations were found, especially in S and N proteins, and some mutations were consistent with FCoV, TGEV strains. Altogether, this study provided a novel insight into the identification, diversification and evolution of CoVs from domestic dogs. It is of top priority to recognize zoonotic potential of CoVs, and continued comprehensive surveillance will help better understand the emergence, spreading, and ecology of animal CoVs.

Epidemiology and Molecular Characterizations of Coronavirus from Companion Animals Living in Chengdu, Southwest China

The recent COVID-19 pandemic has once again caught the attention of people on the probable zoonotic transmission from animals to humans, but the role of companion animals in the coronavirus (CoV) epidemiology still remains unknown. The present study was aimed to investigate epidemiology and molecular characterizations of CoVs from companion animals in Chengdu city, Southwest China. 523 clinical samples from 393 animals were collected from one veterinary hospital between 2020 and 2021, and the presence of CoVs was detected by end-point PCR using pan-CoV assay targeting the RdRp gene. Partial and complete S genes were sequenced for further genotyping and genetic diversity analysis. A total of 162 (31.0%, 162/523) samples and 146 (37.2%, 146/393) animals were tested positive for CoVs. The positive rate in rectal swabs was higher than that in eye/nose/mouth swabs and ascitic fluid but was not statistically different between clinically healthy and diseased ones. Genotyping identified twenty-two feline enteric coronavirus (FCoV) I, four canine enteric coronavirus (CECoV) I, fourteen CECoV IIa, and one CECoV IIb, respectively. Eight complete S genes, including one canine respiratory coronavirus (CRCoV) strain, were successfully obtained. FCoV strains (F21071412 and F21061627) were more closely related to CECoV strains than CRCoV, and C21041821-2 showed potential recombination event. In addition, furin cleavage site between S1 and S2 was identified in two strains. The study supplemented epidemiological information and natural gene pool of CoVs from companion animals. Further understanding of other functional units of CoVs is needed, so as to contribute to the prevention and control of emerging infectious diseases.

Specialty preferences of studying-abroad medical students from low- and middle-income countries.

BACKGROUND: This study explored the specialty preferences of China-educated international medical students (IMSs), who are mainly from low- and middle-income countries (LMICs) and constitute a potential medical workforce both for their home countries and foreign countries, and the influence of migration intentions on their specialty preferences. METHODS: A cross-sectional, questionnaire-based survey was conducted at 5 universities in China. The questionnaire link was distributed electronically among the IMSs at the 5 universities via emails. The questionnaire enquired IMSs' demographic information, migration intentions and their specialty preferences. The Chi-square test was applied to determine the influence of the respondent's gender, intention to practise in the home country and intention to practise in a high-income country on their specialty choices. The Chi-square test was also applied to determine the influence of the respondent's gender, year of study and country of origin on their preferences for generalist-orientated or non-generalist orientated specialties. RESULTS: Altogether, 452 IMSs returned their responses, yielding a response rate of 64.1%. Approximately half of the IMSs planned to not return to their home country. The most selected specialty was general surgery and the least selected specialty was physical medicine and rehabilitation. No significant differences were evident in most specialty preferences between those who intended to return home and those who intended to stay abroad. Among the IMSs having intentions of returning to their home country, male students tended to choose a generalist-orientated specialty, while female students tended to choose a non-generalist-orientated specialty. CONCLUSION: China-educated IMSs could play important roles in the primary care services as well as other shortage specialties both for their home countries or foreign countries. Therefore, it is recommended that governments in these countries plan migration and recruitment policies that cater for these studying-abroad medical students from LMICs, especially in this challenging time during the COVID-19 pandemic.

Doctors ranking through heterogeneous information: The new score functions considering patients' emotional intensity.

With the popularity of the Internet and the growing complexity of COVID-19, more and more patients tend to consult doctors online. With the difficulty of doctor selection caused by a massive amount of information, this study proposes a hybrid multi-criteria decision-making framework, which can model patients' emotional intensity through heterogeneous information and rank doctors. Firstly, online reviews (ORs) are transformed into probabilistic linguistic term sets through sentiment analysis. Then, new score functions are proposed considering the nonlinear influence of doctors' information and the patients' negative bias toward ORs. Next, a method of weight determination combining the Term Frequency Inverse Document Frequency and the Decision-making Trial and Evaluation Laboratory method is proposed. Finally, the proposed score functions are applied to the Combined Compromise Solution (CoCoSo) method to aggregate information and rank doctors. The proposed method is verified in a case study on haodf.com. The results show that considering the emotional intensity of heterogeneous information will make the recommendations more realistic. Comparative analysis and sensitivity analysis are further performed to illustrate the availability and effectiveness of the proposed method.

Aptamers: A prospective tool for infectious diseases diagnosis.

It is well known that people's health is seriously threatened by various pathogens (such as Mycobacterium tuberculosis, Treponema pallidum, Novel coronavirus, HIV, Mucor, etc.), which leads to heavy socioeconomic burdens. Therefore, early and accurate pathogen diagnosis is essential for timely and effective therapies. Up to now, diagnosing human contagious diseases at molecule and nano levels is remarkably difficult owing to insufficient valid probes when it comes to determining the biological markers of pathogens. Aptamers are a set of high-specificity and high-sensitivity plastic oligonucleotides screened in vitro via the selective expansion of ligands by exponential enrichment (SELEX). With the advent of aptamer-based technologies, their merits have aroused mounting academic interest. In recent years, as new detection and treatment tools, nucleic acid aptamers have been extensively utilized in the field of biomedicine, such as pathogen detection, new drug development, clinical diagnosis, nanotechnology, etc. However, the traditional SELEX method is cumbersome and has a long screening cycle, and it takes several months to screen out aptamers with high specificity. With the persistent development of SELEX-based aptamer screening technologies, the application scenarios of aptamers have become more and more extensive. The present research briefly reviews the research progress of nucleic acid aptamers in the field of biomedicine, especially in the diagnosis of contagious diseases.

Integrated System for On-Site Rapid and Safe Screening of COVID-19.

Since the outbreak of coronavirus disease 2019 (COVID-19), the epidemic has been spreading around the world for more than 2 years. Rapid, safe, and on-site detection methods of COVID-19 are in urgent demand for the control of the epidemic. Here, we established an integrated system, which incorporates a machine-learning-based Fourier transform infrared spectroscopy technique for rapid COVID-19 screening and air-plasma-based disinfection modules to prevent potential secondary infections. A partial least-squares discrimination analysis and a convolutional neural network model were built using the collected infrared spectral dataset containing 857 training serum samples. Furthermore, the sensitivity, specificity, and prediction accuracy could all reach over 94% from the results of the field test regarding 968 blind testing samples. Additionally, the disinfection modules achieved an inactivation efficiency of 99.9% for surface and airborne tested bacteria. The proposed system is conducive and promising for point-of-care and on-site COVID-19 screening in the mass population.

System dynamics analysis on the effectiveness of vaccination and social mobilization policies for COVID-19 in the United States.

The COVID-19 pandemic has presented significant public health and economic challenges worldwide. Various health and non-pharmaceutical policies have been adopted by different countries to control the spread of the virus. To shed light on the impact of vaccination and social mobilization policies during this wide-ranging crisis, this paper applies a system dynamics analysis on the effectiveness of these two types of policies on pandemic containment and the economy in the United States. Based on the simulation of different policy scenarios, the findings are expected to help decisions and mitigation efforts throughout this pandemic and beyond.

Severe Acute Respiratory Syndrome Coronavirus 2 ORF8 Protein Inhibits Type I Interferon Production by Targeting HSP90B1 Signaling.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global pandemic that has currently infected over 430 million individuals worldwide. With the variant strains of SARS-CoV-2 emerging, a region of high mutation rates in ORF8 was identified during the early pandemic, which resulted in a mutation from leucine (L) to serine (S) at amino acid 84. A typical feature of ORF8 is the immune evasion by suppressing interferon response; however, the mechanisms by which the two variants of ORF8 antagonize the type I interferon (IFN-I) pathway have not yet been clearly investigated. Here, we reported that SARS-CoV-2 ORF8L and ORF8S with no difference inhibit the production of IFN-ß, MDA5, RIG-I, ISG15, ISG56, IRF3, and other IFN-related genes induced by poly(I:C). In addition, both ORF8L and ORF8S proteins were found to suppress the nuclear translocation of IRF3. Mechanistically, the SARS-CoV-2 ORF8 protein interacts with HSP90B1, which was later investigated to induce the production of IFN-ß and IRF3. Taken together, these results indicate that SARS-CoV-2 ORF8 antagonizes the RIG-I/MDA-5 signaling pathway by targeting HSP90B1, which subsequently exhibits an inhibitory effect on the production of IFN-I. These functions appeared not to be influenced by the genotypes of ORF8L and ORF8S. Our study provides an explanation for the antiviral immune suppression of SARS-CoV-2 and suggests implications for the pathogenic mechanism and treatment of COVID-19.

The Adoption of QR Code Mobile Payment Technology During COVID-19: A Social Learning Perspective.

The increasing number of quick response (QR) code mobile payment users heralds the coming of a cashless society. However, the extent to which the coronavirus disease 2019 (COVID-19) pandemic accelerated the adoption of QR code mobile payment has not been sufficiently researched. Based on social learning theory, this study models how external interaction with the environment has affected the internal appraisal and behavioral intention to adopt QR code mobile payment during COVID-19. Empirical results from 248 respondents revealed that perceived severity and social influence positively affected the perception of utilitarian and health benefits of respondents, which in turn influenced the behavioral intention to use the QR code mobile payment. The theoretical contribution and managerial implications of this study are also discussed.

Predictors for Fear of Cancer Recurrence in Breast Cancer Patients Referred to Radiation Therapy During the COVID-19 Pandemic: A Multi-Center Cross-Section Survey.

OBJECTIVE: The outbreak of COVID-19 pandemic has greatly impacted on radiotherapy (RT) strategy for breast cancer patients, which might lead to increased distressing psychological symptoms. We performed a multi-center cross-section survey to investigate prevalence of fear of cancer recurrence (FCR) and predictors for FCR in patients referred to RT during pandemic. METHODS: 542 patients were consecutively enrolled from three regions in China including Yangtze Delta River Region, Guangdong and Shanxi province. Patients' characteristics were collected using an information sheet, Fear of progression questionnaire-short form, Hospital Anxiety/Depression Scale and EORTC QLQ-C30. The hierarchical multiple regression models were performed. RESULTS: 488 patients with complete data were eligible. The RT strategy was affected in 265 (54.3%) patients, including 143 with delayed RT initiation, 66 believing to have delayed RT initiation but actually not, 24 with RT interruptions, 19 shifting to local hospitals for RT and the remaining 13 influenced on both RT schedule and hospital level. The model explained 59.7% of observed variances in FCR (p<0.001) and showed that influence of RT strategy had significantly impacted on FCR (△R2 = 0.01, △F=2.966, p=0.019). Hospitals in Shanxi province (ß=-0.117, p=0.001), emotional function (ß=-0.19, p<0.001), social function (ß=-0.111, p=0.006), anxiety (ß=0.434, p<0.001) and RT interruption (ß=0.071, p=0.035) were independent predictors. CONCLUSIONS: RT strategy for breast cancer patients was greatly influenced during pandemic. RT interruption is an independent predictor for high FCR. Our findings emphasize the necessity to ensure continuum of RT, and efforts should be taken to alleviate FCR through psychological interventions.

Suboptimal declines and delays in early breast cancer treatment after COVID-19 quarantine restrictions in China: A national survey of 8397 patients in the first quarter of 2020.

BACKGROUND: Cancer patients had been profoundly affected by the outbreak of COVID-19 especially after quarantine restrictions in China. We aimed to explore the treatment changes and delays of early breast cancer (EBC) during the first quarter of 2020. METHODS: We did this retrospective, multicentre, cohort study at 97 cancer centres in China. EBC patients who received treatment regardless of preoperative therapy, surgery or postoperative therapy during first quarter of 2020 were included. FINDINGS: 8397 patients were eligible with a median age of 50 (IQR 43-56). 0·2% (15/8397) of EBC patients were confirmed as COVID-19 infection. Only 5·2% of breast cancer diagnosis occurred after quarantine in Hubei compared with 15·3% in other provinces (OR= 0·30, 95%CI 0·24-0·38). postoperative endocrine therapy were least affected compared with different regions after quarantine (OR=0·37 [95%CI 0·19-0·73]). The proportion of surgery decreased from 16·4% in December last year to 2·6% in February in Hubei. Compared with intervals from diagnosis to treatment before quarantine restrictions, the average time increased with significance from 3·5 to 7·7 days in Hubei and 5·7 to 7·7 days in other provinces (p< 0·001). There were also 18·5 and 7·2 days delay in Hubei and other provinces respectively when calculating interval from surgery to postoperative therapy. INTERPRETATION: EBC from high risk regions had a comparative rate of COVID-19 infection. After implementation of COVID-19 quarantine restrictions, fewer diagnosis and surgery with significant delays were seen when compared with treatment before. FUNDING: Beijing Medical Award Foundation (YJ0120).

[Analysis of variation and evolution of SARS-CoV-2 genome].

OBJECTIVE: To analyze the evolution and variation of SARS-CoV-2 during the epidemic starting at the end of 2019. METHODS: We downloaded the full-length genome sequence of SARS-CoV-2 from the databases of GISAID and NCBI. Using the software for bioinformatics including MEGA-X, BEAST, and TempEst, we constructed the genomic evolution tree, inferred the time evolution signal of the virus, calculated the tMRCA time of the virus and analyzed the selection pressure of the virus during evolution. RESULTS: The phylogenetic tree showed that SARS-CoV-2 belonged to the Sarbecovirus subgenus of ß Coronavirus genus together with bat coronavirus BetaCoV/bat/Yunnan/RaTG13/2013, bat-SL-CoVZC45, bat-SL-CoVZXC21 and SARS-CoV. The genomic sequences of SARS-CoV-2 isolated from the ongoing epidemic showed a weak time evolution signal with an average tMRCA time of 73 days (95% CI: 38.9-119.3 days). No positive time evolution signal was found between SARS-CoV-2 and BetaCoV/bat/Yunnan/RaTG13/2013, but the former virus had a strong positive temporal evolution relationship with bat-SL-CoVZC45 and SARS-CoV. The major cause for mutations of SARS-CoV-2 was the pressure of purification selection during the epidemic. CONCLUSIONS: SARS-CoV-2 may have emerged as early as November, 2019, originating most likely from bat-associated coronavirus. This finding may provide evidence for tracing the sources and evolution of the virus.