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1.
IEEE International Conference on Mechatronics and Automation (IEEE ICMA) ; : 950-955, 2021.
Article in English | English Web of Science | ID: covidwho-1883121

ABSTRACT

Due to the COVID-19 epidemic, there has been a high demand for non-contact diagnostic equipment that can reduce exposure and cross-infection. A non-contact medical detection robot is a type of diagnostic equipment and medical service robot with a wide application prospect. However, few non-contact medical detection robots have been designed to collect patients' physiological parameters when they are in inconvenient situations, such as bedridden, during clinical usage. A six-degree-of-freedom (six-DOF) face tracking method based on a six-DOF robot is proposed in this paper. In the proposed system, a face detector equipped with a camera attached to the robot's wrist is used to obtain the real-time face depth and attitude information. The optimal target attitude of the camera is calculated according to the constraints in the base coordinate system. A closed-loop controller is designed to control the robot to reach the target position and posture smoothly. The experiment with a six-DOF robot has verified that the proposed system can achieve the real-time tracking of human faces by a camera. The proposed method can also be used in many other scenarios where six-DOF face tracking is required by robots.

2.
Topics in Antiviral Medicine ; 30(1 SUPPL):363, 2022.
Article in English | EMBASE | ID: covidwho-1880304

ABSTRACT

Background: HIV infection might accelerate aging process and people living with HIV (PLWH) have been observed to have a higher risk of severe COVID-19 outcomes. However, it is unclear whether the worse COVID-19 outcomes can be attributed to the accelerated aging process. This study aimed to examine: 1) the causal effect of HIV infection on severe COVID-19 outcomes;and 2) the threshold of age difference at which PLWH and non-HIV patients will have comparable COVID-19 outcomes. Methods: We identified COVID-19 positive adults between Jan 1, 2020, and Oct 18, 2021, from the U.S. National COVID Cohort Collaborative (N3C), a nationally-sampled electronic medical record repository. We identified PLWH by clinical diagnosis, drug exposure, and laboratory results. Among COVID-19 cases, PLWH were matched 1:1 to non-HIV persons using exact matching (by gender, race, and ethnicity) and propensity score matching (PSM) (by age, gender, race, ethnicity, and pre-COVID comorbidities). To determine age threshold, PLWH were matched to older non-HIV patients with an age differences between 1 to 15 years. We used conditional logistic regression for exact matched data and standard logistic regression for PSM data. Subgroup analyses stratified by CD4 counts (≥200 or CD4<200 cells/mm) were also conducted. Results: Among a total of 2,422,870 COVID-19 positive adults, we identified 15,188 PLWH. Among PLWH with CD4 data, 872 (14.03%) had CD4<200. Using exact match, PLWH had a significantly higher odds of COVID-19-associated hospitalization [OR: 1.95, 95%CI:(1.88,2.02)] or death [OR: 2.05, 95%CI:(1.90,2.22)] compared to non-HIV persons. By repeating PSM modeling with incrementally increasing ages, PLWH persistently had a higher risk of death compared to non-HIV persons until the age difference reached 6 years, while the threshold of age difference for the comparable hospitalization outcome extended to 14 years. Furthermore, when matching PLWH with CD4<200 with non-HIV persons, the threshold of age difference increased to 10 years for similar odds of mortality and at least 15 years for similar odds of hospitalization. PLWH with CD4≥200 more likely to be hospitalized, though had similar outcomes for death, than non-HIV persons. Conclusion: We find that the worse COVID-19 outcomes, among PWH may be potentially related to aging in HIV. Further investigation of the biological mechanisms at the intersections of HIV infection itself (eg, lower CD4 counts) and accelerated aging in HIV causing worse COVID-19 outcomes is needed.

3.
Intelligent Decision Technologies-Netherlands ; 16(1):159-168, 2022.
Article in English | Web of Science | ID: covidwho-1869335

ABSTRACT

The pandemic COVID-19 disease has had a dramatic impact on almost all countries around the world so that many hospitals have been overwhelmed with COVID-19 cases. As medical resources are limited, deciding on the proper allocation of these resources is a very crucial issue. Besides, uncertainty is a major factor that can affect decisions, especially in medical fields. To cope with these issues, we use fuzzy logic (FL) as one of the most suitable methods in modeling systems with high uncertainty and complexity. We intend to make use of the advantages of FL in decisions on cases that need to treat in ICU. In this study, an interval type-2 fuzzy expert system is proposed for the prediction of ICU admission in COVID-19 patients. For this prediction task, we also developed an adaptive neuro-fuzzy inference system (ANFIS). Finally, the results of these fuzzy systems are compared to some well-known classification methods such as Naive Bayes (NB), Case-Based Reasoning (CBR), Decision Tree (DT), and K Nearest Neighbor (KNN). The results show that the type-2 fuzzy expert system and ANFIS models perform competitively in terms of accuracy and F-measure compared to the other diagnosis systems.

4.
Embase; 2021.
Preprint in English | EMBASE | ID: ppcovidwho-337380

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although unprecedented efforts are underway to develop therapeutic strategies against this disease, scientists have acquired only a little knowledge regarding the structures and functions of the CoV replication and transcription complex (RTC) and 16 non-structural proteins, named NSP1-16. Results: In the present study, we proposed a two-route model to answer how the RTC functions in the jumping transcription of CoVs. The key step leading to this model was that the motif AAACH for METTL3 recognition flanking the transcription regulatory sequence (TRS) motif was discovered to determine the m6A methylation of SARS-CoV-2 RNAs, by reanalyzing public Nanopore RNA-seq data. As the most important finding, TRS hairpins were reported for the first time to interpret NSP15 cleavage, RNA methylation of CoVs and their association at the molecular level. In addition, we reported canonical TRS motifs of all CoVs to prove the importance of our findings. Conclusions: The main conclusions are: (1) TRS hairpins can be used to identify recombination regions in CoV genomes;(2) RNA methylation of CoVs participates in the determination of the RNA secondary structures by affecting the formation of base pairing;and (3) The eventual determination of the CoV RTC global structure needs to consider METTL3 in the experimental design. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, providing a crucial basis for future studies.

5.
Chinese Journal of Biologicals ; 34(5):602-606, 2021.
Article in Chinese | EMBASE | ID: covidwho-1857420

ABSTRACT

The emerging Corona virus Disease 2019 (COVID-19) pandemic poses a massive crisis to global public health. World Health Organization (WHO) declared the global pandemic of COVID-19 on March 11, 2020. The progress of 2019- nCoV vaccines cover nearly all forms of current vaccine research, including inactivated vaccine, recombinant protein vaccine, viral vector-based vaccine, nucleic-acid vaccine and live attenuated vaccine, as well as the vaccine design based on novel concepts such as reverse vaccinology and vaccinomics. This article reviews the COVID-19 vaccines in de¬velopment and clinical trials as well as the challenge in vaccine development.

6.
Chinese Pharmaceutical Journal ; 57(6):428-452, 2022.
Article in Chinese | Scopus | ID: covidwho-1847717

ABSTRACT

OBJECTIVE: Isatidis Radix is the dried root of Isatis indigotica Fortune of Cruciferae. As a representative traditional Chinese medicine for heat-clearing and detoxification, Isatidis Radix and its preparations are widely used in the prevention and treatment of all kinds of colds and have played an active role in the prevention and treatment of SARS, H1N1 and COVID-19. Although the chemical ingredient of Isatidis Radix has been studied deeply, there is no information bank, website or literature that can comprehensively query the information of all compounds at home and abroad, which is not conducive to the development of related research. So establishment of the chemical composition information bank is in need. METHODS: According to the category of chemical ingredients, the Chinese and English names, molecular formulas, exact molecular weights, structural formulas and references of nearly 400 chemical components in Isatidis Radix were comprehensively sorted out, and the chemical composition information bank of Isatidis Radix was constructed. RESULTS: By September 2020, a total of 392 compounds in 17 categories had been extracted, isolated and identified from Isatidis Radix. CONCLUSIONT: The established chemical composition information bank can provide the basis for the separation and identification of chemical components, quality control, material basis mining, network pharmacology research and so on. Copyright 2022 by the Chinese Pharmaceutical Association.

7.
Shipin Kexue/Food Science ; 43(5):346-355, 2022.
Article in Chinese | Scopus | ID: covidwho-1847651

ABSTRACT

As an important immuneoactive component in eggs, yolk immunoglobulin (IgY) shows great competitiveness in research and production due to its good stability, high safety, low cost, easy availability, strong immune activity, and no drug resistance. This article highlights the significant advantages of IgY as a good antibiotic substitute in the prevention and treatment of viral and bacterial diseases. Also, IgY has great potential in the regulation of nutrient metabolism balance, intestinal microflora and immune homeostasis by affecting key rate-limiting enzymes, and relevant receptors and inflammatory factors specifically. Proper diet and targeted delivery of foodborne IgY may be a new perspective on inflammation regulation, disease control, nutritional balance or homeostasis, and oral microencapsulated IgY is expected to be a new approach against increasing public health emergencies (such as COVID-19 pandemic). © 2022, China Food Publishing Company. All right reserved.

8.
2021 International Conference on Computer, Blockchain and Financial Development, CBFD 2021 ; : 343-346, 2021.
Article in English | Scopus | ID: covidwho-1846065

ABSTRACT

According to the unimaginable influence of Covid-19 and the essential of capital asset pricing in the market, this article analyzes the TV industry of the US stock market before and during the epidemic based on the Fama-French five-factor model. Fama-French five-factor model comprehensively considers the impact of market risk premium (Mkt-RF), market value scale factor, (SMB), book-to-market value ratio factor (HML), profit factor (RMW) and investment factor (CMA) on this industry. Meanwhile, it can conduct a comprehensive evaluation of the impact of Covid-19 on the TV industry. The data in this article was selected from Kenneth R. French's databases and used multiple linear regression to obtain the results. The performance of factors is different due to the outbreak of Covid-19. By analyzing the result, it found that Mkt-RF, SMB are not significant in the model, but HML, RMW, CMA have changed from insignificant to significant. It indicates that during the Covid-19, investors are recommended to pay more attention to the firms with high book-to-market ratios, stable profitability, and aggressive investment style in the USA TV industry. Therefore, research on the stock market of the TV industry plays an important role in the steady development of the economy, the creation of social wealth, and the improvement of people's living standards. © 2021 IEEE.

9.
2021 International Conference on Computer, Blockchain and Financial Development, CBFD 2021 ; : 281-285, 2021.
Article in English | Scopus | ID: covidwho-1843341

ABSTRACT

Hundreds of millions of people around the world suffer from viral infections every year. However, some of them have neither vaccine nor effective treatment during and after viral infection. Such as pneumonia, severe acute respiratory syndrome type 2 (SARS -2), HIV infection and Hepatitis-C virus. These viral diseases also directly and indirectly cause cardiovascular disease (CVD). Recently, the Deep Neural Network (DNN)-assisted molecular interaction (information) (MI) transceiver (transmitter Tx, and receiver Rx) design was brought to the fore to break the issues of traditional molecular information (MI) inside and outside human body. In this paper, we use DNN based approach to design and implement a new transceiver (Tx/Rx). We investigate DNN-assisted MI- Tx/Rx, multilayer perception DNN auto-encoder (MLP-AE), and convolutional neural network auto-encoder (CNN-AE), respectively. We apply an MLP-AE and CNN-AE to simultaneously accomplish the task of modulation, demodulation, and equalization as a point-to-point scheme. © 2021 IEEE.

10.
International Journal of Information Technology and Decision Making ; 2022.
Article in English | Scopus | ID: covidwho-1832568

ABSTRACT

The concepts of relations and information measures have importance whenever we deal with medical diagnosis problems. The aim of this paper is to investigate the global pandemic COVID-19 scenario using relations and information measures in an interval-valued T-spherical fuzzy (IVTSF) environment. An IVTSF set (IVTSFS) allows describing four aspects of human opinions i.e., membership, abstinence, non-membership, and refusal grade that process information in a significant way and reduce information loss. We propose similarity measures and relations in the IVTSF environment and investigate their properties. Both information measures and relations are applied in a medical diagnosis problem keeping in view the global pandemic COVID-19. How to determine the diagnosis based on symptoms of a patient using similarity measures and relations is discussed. Finally, the advantages of dealing with such problems using the IVTSF framework are demonstrated with examples. © 2022 World Scientific Publishing Company.

11.
2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 ; : 599-602, 2022.
Article in English | Scopus | ID: covidwho-1831762

ABSTRACT

Machine propositions are the research frontier of natural language processing technology, and the core of the technology path is the result of the development of reading comprehension and question answering systems. Machine propositions can help save a lot of manpower and time, especially in the case of the continuous development of the Covid-19, and help the teaching acceptance and learning evaluation of online learning. At present, the simultaneous pursuit of autonomous propositions and precision requirements in the academic field of machine propositions is the research focus and difficulty. © 2022 IEEE.

12.
2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 ; : 54-56, 2022.
Article in English | Scopus | ID: covidwho-1831761

ABSTRACT

This paper expounds the application and exploration of smart tourism in Daqing under the development of big data technology and the situation of COVID-19. Through the association rules mining, we build Daqing's global tourism data platform and realize intelligent tourism. Combined with the epidemic situation, the digital anti epidemic exploration of Daqing cultural and tourism scenic spot is carried out. Under the guidance of association rule mining and learning, the integration support of each association system is carried out to improve the confidence, so as to establish an all-round, integrated and intelligent smart tourism pattern. © 2022 IEEE.

13.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334813

ABSTRACT

Cryptococcal meningoencephalitis is an emerging infection shifted from primarily ART- naive to being ART-experienced HIV/AIDS patients, COVID-19 patients and also in immune competent individuals, mainly caused by the human opportunistic pathogen Cryptococcus neoformans, yet mechanisms of the brain or CNS dissemination remain to elucidate, which is the deadest process for the disease. Meanwhile, illustrations of clinically relevant responses in cryptococcosis were limited, as the low availabilities of clinical samples. In this study, macaque and mouse infection models were employed and miRNA-mRNA transcriptomes were performed and combined, which revealed cytoskeleton, a major feather in HIV/AIDS patients, was a centric pathway regulated in both two infection models. Notably, assays of clinical immune cells confirmed an enhanced “Trojan Horse” in HIV/AIDS patients, which can be shut down by cytoskeleton inhibitors. Furthermore, we identified a novel enhancer for macrophage “Trojan Horse”, myocilin, and an enhanced fungal burden was achieved in brains of MYOC transgenic mice. Taking together, this study reveals fundamental roles of cytoskeleton and MYOC in blocking fungal CNS dissemination, which not only helps to understand the high prevalence of cryptococcal meningitis in HIV/AIDS, but also facilitates the development of novel drugs for therapies of meningoencephalitis caused by C. neoformans and other pathogenic microorganisms.

14.
Annals of Translational Medicine ; : 12, 2022.
Article in English | Web of Science | ID: covidwho-1822668

ABSTRACT

Background: New England Journal of Medicine (NEJM), Lancet, Journal of the American Medical Association (JAMA), and British Medical Journal (BMJ) are collectively known as "the Top Four Medical Journals (TFMJ)" in China. Through the analysis of Chinese scholars' publications in the TFMJ in the recent 10 years, this study aimed to clarify the current situation of high-quality medical research conducted by Chinese scholars and institutions. Methods: Data were retrieved and downloaded manually from PubMed (2011-2020). Information on the publication year, journal, author, affiliation, and citation, etc. were extracted and analyzed using R software. Results: A total of 761 articles were involved in the final analysis. The number of articles published by Chinese scholars in the TFMJ was 135/29,942 (0.45%) in BMJ, 124/14,033 (0.88%) in JAMA, 314/16,117 (1.94%) in Lancet, and 188/15,242 (1.23%) in NEJM (P<0.001). Besides, the letter was the main research type, which was up to 44.54%, and the original research only accounted for 17.47%. The most popular subspecialty and subject were infectious diseases and COVID-19, respectively. The most productive researcher was Chen Wang, and Bin Cao was the most cited Chinese scholar. The most productive institute was Chinese Academy of Medical Sciences and Peking Union Medical College. The most cited study was "Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China". Conclusions: The presence of Chinese scholars in the TFMJ has grown, but there is still much room to improve. A Matthew effect in China's high-level scientific research was demonstrated.

15.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333658

ABSTRACT

BACKGROUND: Population mobility is closely associated with coronavirus 2019 (COVID-19) transmission, and it could be used as a proximal indicator to predict future outbreaks, which could inform proactive non-pharmaceutical interventions for disease control. South Carolina (SC) is one of the states which reopened early and then suffered from a sharp increase of COVID-19. OBJECTIVE: To examine the spatial-temporal relationship between population mobility and COVID-19 outbreaks and use population mobility to predict daily new cases at both state- and county- levels in SC. METHODS: This longitudinal study used disease surveillance data and Twitter-based population mobility data from March 6 to November 11, 2020 in SC and its top five counties with the largest number of cumulative confirmed cases. Daily new case was calculated by subtracting the cumulative confirmed cases of previous day from the total cases. Population mobility was assessed using the number of users with travel distance larger than 0.5 mile which was calculated based on their geotagged twitters. Poisson count time series model was employed to carry out the research goals. RESULTS: Population mobility was positively associated with state-level daily COVID-19 incidence and those of the top five counties (i.e., Charleston, Greenville, Horry, Spartanburg, Richland). At the state-level, final model with time window within the last 7-day had the smallest prediction error, and the prediction accuracy was as high as 98.7%, 90.9%, and 81.6% for the next 3-, 7-, 14- days, respectively. Among Charleston, Greenville, Horry, Spartanburg, and Richland counties, the best predictive models were established based on their observations in the last 9-, 14-, 28-, 20-, and 9- days, respectively. The 14-day prediction accuracy ranged from 60.3% to 74.5%. CONCLUSIONS: Population mobility was positively associated with COVID-19 incidences at both state- and county- levels in SC. Using Twitter-based mobility data could provide acceptable prediction for COVID-19 daily new cases. Population mobility measured via social media platform could inform proactive measures and resource relocations to curb disease outbreaks and their negative influences.

16.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333625

ABSTRACT

BACKGROUND: To control the COVID-19 pandemic, governments need to ensure a successful large-scale administration of COVID-19 vaccines when safe and efficacious vaccines become available. Vaccine acceptance could be a critical factor influencing vaccine uptake. Health information has been associated with vaccine acceptance. For college students who are embracing a digital era and being exposed to multimedia, the sources of COVID-19 vaccine information and their trust in these sources may play an important role in shaping their acceptance of vaccine uptake. METHODS: In September 2020, we conducted an online survey among 1062 college students in South Carolina to understand their perceptions and attitudes toward COVID-19 vaccination. Descriptive analysis and linear regression analysis were used to investigate vaccine information sources among college students and examine how COVID-19 vaccine acceptance was associated with information source and trust level in each source. RESULTS: The top three sources of COVID-19 vaccine information were health agencies (57.7%), mass media (49.5%), and personal social networks (40.5%). About 83.1% of the participants largely or always trusted scientists, 73.9% trusted healthcare providers, and 70.2% trusted health agencies. After controlling for key demographics, vaccine acceptance was positively associated with scientists as information sources but negatively associated with pharmaceutical companies as sources. Higher trust levels in mass media, health agencies, scientists, and pharmaceutical companies was significantly associated with higher COVID-19 vaccine acceptance. However, trust in social media was negatively associated with vaccine acceptance. DISCUSSION: College students use multiple sources to learn about upcoming COVID-19 vaccines including health agencies, personal networks, and social media. The level of trust in these information sources play a critical role in predicting vaccine acceptance. Trust in health authorities and scientists rather than social media is related to higher level vaccine acceptance. Our findings echo the call for restoring trust in government, healthcare system, scientists, and pharmaceutical industries in the COVID-19 era and highlight the urgency to dispel misinformation in social media. Effective strategies are needed to disseminate accurate information about COVID-19 vaccine from health authorities and scientific research to improve vaccine communication to the public and promote COVID-19 vaccine uptake.

17.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333519

ABSTRACT

The SARS-CoV-2 pandemic, starting in 2019, has challenged the speed at which labs perform science, ranging from discoveries of the viral composition to handling health outcomes in humans. The small ~30kb single-stranded RNA genome of Coronaviruses makes them adept at cross species spread and drift, increasing their probability to cause pandemics. However, this small genome also allows for a robust understanding of all proteins coded by the virus. We employed protein modeling, molecular dynamic simulations, evolutionary mapping, and 3D printing to gain a full proteome and dynamicome understanding of SARS-CoV-2. The Viral Integrated Structural Evolution Dynamic Database (VIStEDD) has been established (prokoplab.com/vistedd), opening future discoveries and educational usage. In this paper, we highlight VIStEDD usage for nsp6, Nucleocapsid (N), and Spike (S) surface glycoprotein. For both nsp6 and N we reveal highly conserved surface amino acids that likely drive protein-protein interactions. In characterizing viral S protein, we have developed a quantitative dynamics cross correlation matrix insight into interaction with the ACE2/SLC6A19 dimer complex. From this quantitative matrix, we elucidated 47 potential functional missense variants from population genomic databases within ACE2/SLC6A19/TMPRSS2, warranting genomic enrichment analyses in SARS-CoV-2 patients. Moreover, these variants have ultralow frequency, but can exist as hemizygous in males for ACE2, which falls on the X-chromosome. Two noncoding variants (rs4646118 and rs143185769) found in ~9% of African descent individuals for ACE2 may regulate expression and be related to increased susceptibility of African Americans to SARS-CoV-2. This powerful database of SARS-CoV-2 can aid in research progress in the ongoing pandemic.

18.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333504

ABSTRACT

COVID-19 has become a global pandemic caused by a novel coronavirus SARS-CoV-2. Understanding the origins of SARS-CoV-2 is critical for deterring future zoonosis and for drug discovery and vaccine development. We show evidence of strong purifying selection around the receptor binding motif (RBM) in the spike gene and in other genes among bat, pangolin and human coronaviruses, indicating similar strong evolutionary constraints in different host species. We also demonstrate that SARS-CoV-2's entire RBM was introduced through recombination with coronaviruses from pangolins, possibly a critical step in the evolution of SARS-CoV-2's ability to infect humans. Similar purifying selection in different host species and frequent recombination among coronaviruses suggest a common evolutionary mechanism that could lead to new emerging human coronaviruses. ONE SENTENCE SUMMARY: Extensive Recombination and Strong Purifying Selection among coronaviruses from different hosts facilitate the emergence of SARS-CoV-2.

19.
Networks and Heterogeneous Media ; 0(0):21, 2022.
Article in English | Web of Science | ID: covidwho-1792333

ABSTRACT

Deterministic compartmental models for infectious diseases give the mean behaviour of stochastic agent-based models. These models work well for counterfactual studies in which a fully mixed large-scale population is relevant. However, with finite size populations, chance variations may lead to significant departures from the mean. In real-life applications, finite size effects arise from the variance of individual realizations of an epidemic course about its fluid limit. In this article, we consider the classical stochastic Susceptible-Infected-Recovered (SIR) model, and derive a martingale formulation consisting of a deterministic and a stochastic component. The deterministic part coincides with the classical deterministic SIR model and we provide an upper bound for the stochastic part. Through analysis of the stochastic component depending on varying population size, we provide a theoretical explanation of finite size effects. Our theory is supported by quantitative and direct numerical simulations of theoretical infinitesimal variance. Case studies of coronavirus disease 2019 (COVID-19) transmission in smaller populations illustrate that the theory provides an envelope of possible outcomes that includes the field data.

20.
Nan Fang Yi Ke Da Xue Xue Bao ; 42(3): 399-404, 2022 Mar 20.
Article in Chinese | MEDLINE | ID: covidwho-1791799

ABSTRACT

OBJECTIVE: To analyze the mutations in transcription regulatory sequences (TRSs) of coronaviruss (CoV) to provide the basis for exploring the patterns of SARS-CoV-2 transmission and outbreak. METHODS: A combined evolutionary and molecular functional analysis of all sets of publicly available genomic data of viruses was performed. RESULTS: A leader transcription regulatory sequence (TRS-L) usually comprises the first 60-70 nts of the 5' UTR in a CoV genome, and the body transcription regulatory sequences (TRS-Bs) are located immediately upstream of the genes other than ORF1a and 1b. In each CoV genome, the TRS-L and TRS-Bs share a specific consensus sequence, namely the TRS motif. Any changes of nucleotide residues in the TRS motifs are defined as TRS motif mutations. Mutations in the TRS-L or multiple TRS-Bs result in superattenuated variants. The spread of super-attenuated variants may cause an increase in asymptomatic or mild infections, prolonged incubation periods and a decreased detection rate of the viruses, thus posing new challenges to SARS-CoV-2 prevention and control. The super-attenuated variants also increase their possibility of long-term coexistence with humans. The Delta variant is significantly different from all the previous variants and may lead to a large-scale transmission. The Delta variant (B.1.617.2) with TRS motif mutation has already appeared and shown signs of spreading in Singapore, which, and even the Southeast Asia, may become the new epicenter of the next wave of SARS-CoV-2 outbreak. CONCLUSION: TRS motif mutation will occur in all variants of SARS-CoV-2 and may result in super-attenuated variants. Only super-attenuated variants with TRS motif mutations will eventually lose the abilities of cross-species transmission and causing outbreaks.


Subject(s)
COVID-19 , Mutation , SARS-CoV-2 , COVID-19/virology , Genome, Viral , Humans , SARS-CoV-2/genetics
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