Strategy To Assess Zoonotic Potential Reveals Low Risk Posed by SARS-Related Coronaviruses from Bat and Pangolin.

In the last 2 decades, pathogens originating in animals may have triggered three coronavirus pandemics, including the coronavirus disease 2019 pandemic. Thus, evaluation of the spillover risk of animal severe acute respiratory syndrome (SARS)-related coronavirus (SARSr-CoV) is important in the context of future disease preparedness. However, there is no analytical framework to assess the spillover risk of SARSr-CoVs, which cannot be determined by sequence analysis alone. Here, we established an integrity framework to evaluate the spillover risk of an animal SARSr-CoV by testing how viruses break through key human immune barriers, including viral cell tropism, replication dynamics, interferon signaling, inflammation, and adaptive immune barriers, using human ex vivo lung tissues, human airway and nasal organoids, and human lung cells. Using this framework, we showed that the two pre-emergent animal SARSr-CoVs, bat BtCoV-WIV1 and pangolin PCoV-GX, shared similar cell tropism but exhibited less replicative fitness in the human nasal cavity or airway than did SARS-CoV-2. Furthermore, these viruses triggered fewer proinflammatory responses and less cell death, yet showed interferon antagonist activity and the ability to partially escape adaptive immune barriers to SARS-CoV-2. Collectively, these animal viruses did not fully adapt to spread or cause severe diseases, thus causing successful zoonoses in humans. We believe that this experimental framework provides a path to identifying animal coronaviruses with the potential to cause future zoonoses. IMPORTANCE Evaluation of the zoonotic risk of animal SARSr-CoVs is important for future disease preparedness. However, there are misconceptions regarding the risk of animal viruses. For example, an animal SARSr-CoV could readily infect humans. Alternately, human receptor usage may result in spillover risk. Here, we established an analytical framework to assess the zoonotic risk of SARSr-CoV by testing a series of virus-host interaction profiles. Our data showed that the pre-emergent bat BtCoV-WIV1 and pangolin PCoV-GX were less adapted to humans than SARS-CoV-2 was, suggesting that it may be extremely rare for animal SARSr-CoVs to break all bottlenecks and cause successful zoonoses.

Whole-genome resequencing reveals genetic diversity, differentiation, and selection signatures of yak breeds/populations in Qinghai, China.

The Qinghai Province of China is located in the northeast region of the Qinghai-Tibetan Plateau (QTP) and carries abundant yak genetic resources. Previous investigations of archaeological records, mitochondrial DNA, and Y chromosomal markers have suggested that Qinghai was the major center of yak domestication. In the present study, we examined the genomic diversity, differentiation, and selection signatures of 113 Qinghai yak, including 42 newly sequenced Qinghai yak and 71 publicly available individuals, from nine yak breeds/populations (wild, Datong, Huanhu, Xueduo, Yushu, Qilian, Geermu, Tongde, and Huzhu white) using high-depth whole-genome resequencing data. We observed that most of Qinghai yak breeds/populations have abundant genomic diversity based on four genomic parameters (nucleotide diversity, inbreeding coefficients, linkage disequilibrium decay, and runs of homozygosity). Population genetic structure analysis showed that Qinghai yak have two lineages with two ancestral origins and that nine yak breeds/populations are clustered into three distinct groups of wild yak, Geermu yak, and seven other domestic yak breeds/populations. F ST values showed moderate genetic differentiation between wild yak, Geermu yak, and the other Qinghai yak breeds/populations. Positive selection signals were detected in candidate genes associated with disease resistance (CDK2AP2, PLEC, and CYB5B), heat stress (NFAT5, HSF1, and SLC25A48), pigmentation (MCAM, RNF26, and BOP1), vision (C1QTNF5, MFRP, and TAX1BP3), milk quality (OPLAH and GRINA), neurodevelopment (SUSD4, INSYN1, and PPP1CA), and meat quality (ZRANB1), using the integrated PI, composite likelihood ratio (CLR), and F ST methods. These findings offer new insights into the genetic mechanisms underlying target traits in yak and provide important information for understanding the genomic characteristics of yak breeds/populations in Qinghai.

Clinical experiences of final-year nursing students during the COVID-19 pandemic: A systematic review and meta-synthesis.

OBJECTIVES: This systematic review aimed to qualitatively synthesise existing literature to examine the clinical nursing experiences of final-year nursing students during the COVID-19 pandemic and provide recommendations for the effective management of clinical placement of nursing students. DESIGN: A qualitative systematic review was conducted and reported following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. DATA SOURCES: Five electronic databases were searched and qualitative studies were included for analysis if they focussed on the clinical nursing experiences of final-year nursing students during the COVID-19 pandemic. REVIEW METHODS: Data synthesis was conducted by extracting all findings, developing categories, and producing synthesised findings. RESULTS: Four synthesised findings were concluded: 1) facing the unknown and willingness to help, 2) challenging the clinical environment, 3) transition improving professional identity, and 4) finding ways out of the pandemic. CONCLUSIONS: The transition of nursing students to clinical nursing practice during the pandemic is a personally and professionally challenging process, while nursing students try to adapt to the changing clinical environment and enhance their professional identity. Nursing managers and health policymakers should acknowledge the challenges encountered by nursing students during the pandemic and support the professional growth of future nursing teams by providing high-quality supervision.

Impact of COVID-19-related regulatory changes on nationwide access to buprenorphine: An interrupted time series design.

Background: The impact of COVID-19-related healthcare changes on access to buprenorphine (BUP) nationwide in the US is unknown. Methods: We conducted an interrupted time series with the IQVIA LRx database. The study timeline included BUP prescriptions from 52 weeks before (2/23/19-2/21/20) to 52 weeks after (4/4/20-4/2/21) the initial pandemic period (2/22/20-4/3/20). Segmented regression estimated relative changes in total milligrams (MG) of BUP available per week nationwide at 1, 26, and 52 weeks post-initial-pandemic. We evaluated treatment disruptions in previously stable patients, defined as ≥6 months of BUP prescriptions. Results: A total of 31 617 849 prescriptions were included. Total MG BUP dispensed increased at 1 and 26 weeks and then returned to baseline trends at 52 weeks post-initial pandemic period (4.1% [95% CI: 3.7,4.5], 2.1% [1.5,2.6], 0.1% [-0.6,0.9]). Stably-treated patients saw a decrease in 7-, 14-, and 28-day treatment disruptions at 52 weeks post-initial-pandemic period (-21.6% [-25.6,-17.7]; -10.8% [-16.3,-5.3]; -27.3% [-33.0,-21.6]). Men retained an increase in MG BUP compared to women at 52 weeks (0.7% [0.01,1.4] versus -0.6% [-1.5,0.2]). Younger age groups (18-29 years and 30-39 years) had a decrease in MG BUP at 52 weeks compared to expected baseline trend (-16.6 [-24.2, -9.0]; -1.6 [-3.0, -0.1). Patients with Medicaid demonstrated an increase in MG BUP at 52 weeks (8.3% [6.3,10.3]). MG BUP prescribed by APP prescribing increased by over 140 000 mg per week prior to the pandemic and continued to increase. Conclusions: Regulatory changes around buprenorphine prescribing facilitated patient access to buprenorphine during the pandemic.

Knowledge, attitudes, and practices towards COVID-19 among residents of Quang Binh, Vietnam.

INTRODUCTION: The COVID-19 pandemic is raging worldwide; the number of new cases and deaths is increasing daily. This study aims to examine the knowledge, attitudes, and practices (KAP) toward COVID-19 among residents of Quang Binh, Vietnam. METHODOLOGY: A cross-sectional study was conducted between the 1st and 10th of March 2022 in Quang Binh with 413 participants through convenience sampling. A self-designed questionnaire was used for data collection, using SPSS (IBM Corp, Armonk, NY) version 26.0 for management and analysis. RESULTS: Among the 413 participants, 80.5% of participants had good knowledge about COVID-19. Kinh people and those with a high level of education have higher odds of having good knowledge. 78.2% of participants had a positive attitude and 78.2% had good practice toward COVID-19. Knowledge-Practice scores and Attitude-Practice scores have a positive correlation. TV (65.4%) and the internet (66.6%) are the most popular channels for information about COVID-19. Common barriers for participants taking COVID-19 prevention measures were "due to the demands of life" (61%) or "due to the specificity of the work" (47.7%). CONCLUSIONS: Residents of Quang Binh have a moderate KAP towards COVID-19. Health education programs are needed to improve knowledge about COVID-19 among Quang Binh residents, with a focus on ethnic minorities and people with low levels of education.

Increased pathogenicity and aerosol transmission for one SARS-CoV-2 B.1.617.2 Delta variant over the wild-type strain in hamsters.

During the two-year pandemic of coronavirus disease 2019 (COVID-19), its causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been evolving. SARS-CoV-2 Delta, a variant of concern, has become the dominant circulating strain worldwide within just a few months. Here, we performed a comprehensive analysis of a new B.1.617.2 Delta strain (Delta630) compared with the early WIV04 strain (WIV04) in vitro and in vivo, in terms of replication, infectivity, pathogenicity, and transmission in hamsters. When inoculated intranasally, Delta630 led to more pronounced weight loss and more severe disease in hamsters. Moreover, 40% mortality occurred about one week after infection with 104 PFU of Delta630, whereas no deaths occurred even after infection with 105 PFU of WIV04 or other strains belonging to the Delta variant. Moreover, Delta630 outgrew over WIV04 in the competitive aerosol transmission experiment. Taken together, the Delta630 strain showed increased replication ability, pathogenicity, and transmissibility over WIV04 in hamsters. To our knowledge, this is the first SARS-CoV-2 strain that causes death in a hamster model, which could be an asset for the efficacy evaluation of vaccines and antivirals against infections of SARS-CoV-2 Delta strains. The underlying molecular mechanisms of increased virulence and transmission await further analysis.

Data science in the intensive care unit.

In this editorial, we comment on the current development and deployment of data science in intensive care units (ICUs). Data in ICUs can be classified into qualitative and quantitative data with different technologies needed to translate and interpret them. Data science, in the form of artificial intelligence (AI), should find the right interaction between physicians, data and algorithm. For individual patients and physicians, sepsis and mechanical ventilation have been two important aspects where AI has been extensively studied. However, major risks of bias, lack of generalizability and poor clinical values remain. AI deployment in the ICUs should be emphasized more to facilitate AI development. For ICU management, AI has a huge potential in transforming resource allocation. The coronavirus disease 2019 pandemic has given opportunities to establish such systems which should be investigated further. Ethical concerns must be addressed when designing such AI.

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accurate machine-learning model to identify patients at risks of NIV failure after extubation in intensive care units (ICUs). METHODS: Patients who underwent NIV after extubation in the eICU Collaborative Research Database (eICU-CRD) were included. NIV failure was defined as need for invasive ventilatory support (reintubation or tracheotomy) or death after NIV initiation. A total of 93 clinical and laboratory variables were assessed, and the recursive feature elimination algorithm was used to select key features. Hyperparameter optimization was conducted with an automated machine-learning toolkit called Neural Network Intelligence. A machine-learning model called Categorical Boosting (CatBoost) was developed and compared with nine other models. The model was then prospectively validated among patients enrolled in the Cardiac Surgical ICU of Zhongshan Hospital, Fudan University. RESULTS: Of 929 patients included in the eICU-CRD cohort, 248 (26.7%) had NIV failure. The time from extubation to NIV, age, Glasgow Coma Scale (GCS) score, heart rate, respiratory rate, mean blood pressure (MBP), saturation of pulse oxygen (SpO2), temperature, glucose, pH, pressure of oxygen in blood (PaO2), urine output, input volume, ventilation duration, and mean airway pressure were selected. After hyperparameter optimization, our model showed the greatest accuracy in predicting NIV failure (AUROC: 0.872 [95% CI 0.82-0.92]) among all predictive methods in an internal validation. In the prospective validation cohort, our model was also superior (AUROC: 0.846 [95% CI 0.80-0.89]). The sensitivity and specificity in the prediction group is 89% and 75%, while in the validation group they are 90% and 70%. MV duration and respiratory rate were the most important features. Additionally, we developed a web-based tool to help clinicians use our model. CONCLUSIONS: This study developed and prospectively validated the CatBoost model, which can be used to identify patients who are at risk of NIV failure. Thus, those patients might benefit from early triage and more intensive monitoring. TRIAL REGISTRATION: NCT03704324. Registered 1 September 2018, https://register. CLINICALTRIALS: gov .

Myocarditis and pericarditis risk after covid-19 vaccination

A weak evidence base leaves important questions unanswered

Design for Pandemic Information: Examining the Effect of Graphs on Anxiety and Social Distancing Intentions in the COVID-19.

To increase public awareness and disseminate health information, the WHO and health departments worldwide have been visualizing the latest statistics on the spread of COVID-19 to increase awareness and thus reduce its spread. Within various sources, graphs are frequently used to illustrate COVID-19 datasets. Limited research has provided insights into the effect of different graphs on emotional stress and ineffective behavioral strategies from a cross-cultural perspective. The result of current research suggests a graph with a high proportion size of the colored area (e.g., stacked area graph) might increase people's anxiety and social distancing intentions; people in collectivist culture might have a high level of anxiety and social distancing intentions; the effect of different graphs on social distancing intentions is mediated by anxiety experienced. Theoretical contribution and practical implications on health communication were also discussed in this study.

Dose Optimization of Anxiolytic Compounds Group in Valeriana jatamansi Jones and Mechanism Exploration by Integrating Network Pharmacology and Metabolomics Analysis.

Anxiety disorder impacts the quality of life of the patients. The 95% ethanol extract of rhizomes and roots of Valeriana jatamansi Jones (Zhi zhu xiang, ZZX) has previously been shown to be effective for the treatment of anxiety disorder. In this study, the dose ratio of each component of the anxiolytic compounds group (ACG) in a 95% ethanol extract of ZZX was optimized by a uniform design experiment and mathematical modeling. The anxiolytic effect of ACG was verified by behavioral experiments and biochemical index measurement. Network pharmacology was used to determine potential action targets, as well as predict biological processes and signaling pathways, which were then verified by molecular docking analysis. Metabolomics was then used to screen and analyze metabolites in the rat hippocampus before and after the administration of ZZX-ACG. Finally, the results of metabolomics and network pharmacology were integrated to clarify the anti-anxiety mechanism of the ACG. The optimal dose ratio of ACG in 95% ethanol extract of ZZX was obtained, and our results suggest that ACG may regulate ALB, AKT1, PTGS2, CYP3A4, ESR1, CASP3, CYP2B6, EGFR, SRC, MMP9, IGF1, and MAPK8, as well as the prolactin signaling pathway, estrogen signaling pathway, and arachidonic acid metabolism pathway, thus affecting the brain neurotransmitters and HPA axis hormone levels to play an anxiolytic role, directly or indirectly.

Occurrence and decay of SARS-CoV-2 in community sewage drainage systems.

The rapid spread of the coronavirus disease (COVID-19) pandemic in over 200 countries poses a substantial threat to human health. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, can be discharged with feces into the drainage system. However, a comprehensive understanding of the occurrence, presence, and potential transmission of SARS-CoV-2 in sewers, especially in community sewers, is still lacking. This study investigated the virus occurrence by viral nucleic acid testing in vent stacks, septic tanks, and the main sewer outlets of community where confirmed patients had lived during the outbreak of the epidemic in Wuhan, China. The results indicated that the risk of long-term emission of SARS-CoV-2 to the environment via vent stacks of buildings was low after confirmed patients were hospitalized. SARS-CoV-2 were mainly detected in the liquid phase, as opposed to being detected in aerosols, and its RNA in the sewage of septic tanks could be detected for only four days after confirmed patients were hospitalized. The surveillance of SARS-CoV-2 in sewage could be a sensitive indicator for the possible presence of asymptomatic patients in the community, though the viral concentration could be diluted more than 10 times, depending on the sampling site, as indicated by the Escherichia coli (E. coli) test. The comprehensive investigation of the community sewage drainage system is helpful to understand the occurrence characteristics of SARS-CoV-2 in sewage after excretion with feces and the feasibility of sewage surveillance for COVID-19 pandemic monitoring.

Analyzing Rail Traffic Diversion Based on Machine Learning Technique considering Transportation Security

Based on a stated preference survey, we comprehensively analyze the travel psychology of residents and the advantages and disadvantages of rail transit and conventional buses, travel time, travel cost, travel security, and vehicle comfort and investigate the relationship between the relevant influencing factors and the transition probability from rail transit to buses. A stochastic utility theory is introduced to describe the transfer behavior pertaining to travel modes, and a binary Logit model for diversion transfer is constructed. The decision tree is also used to predict the diversion transfer. Then, based on the large amount of travel willingness data obtained through the stated preference survey, a maximum likelihood estimation method is used to calibrate the parameters of the binary Logit model. The performance of the binary Logit proves to be better than that of the decision tree. Results show that the travel time most notably affects the passenger flow transfer, followed by the vehicle comfort. Finally, Guangzhou Rail Transit Line 3 is considered an example, and the diversion route planning and design are performed according to the constructed diversion transfer probability model to verify the effectiveness and practicability of the model. The research provides an effective theoretical basis and technical reference for other cities to perform rail traffic diversion planning. Based on these results, the following suggestions can be made: (1) the organization of public transportation routes, delivery volume, and travel speed outside should be improved;(2) undertaking combined operation of bus and rail transportation and integrated development is preferred;(3) the transportation management should focus on the comprehensive function development and hardware support of public transportation stations. The convenience and comfort of rail transit are closely related to the facilities and functions of the stations and their connections, which should be highly valued.

Developing an Amplification Refractory Mutation System-Quantitative Reverse Transcription-PCR Assay for Rapid and Sensitive Screening of SARS-CoV-2 Variants of Concern.

With the emergence and wide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs), such as the Delta variant (B.1.617.2 lineage and AY sublineage), it is important to track VOCs for sourcing of transmission. Currently, whole-genome sequencing is commonly used for detecting VOCs, but this is limited by the high costs of reagents and sophisticated sequencers. In this study, common mutations in the genomes of SARS-CoV-2 VOCs were identified by analyzing more than 1 million SARS-CoV-2 genomes from public data. Among them, mutations C1709A (a change of C to A at position 1709) and C56G, respectively, were found in more than 99% of the genomes of Alpha and Delta variants and were specific to them. Then, a method using the amplification refractory mutation system combined with quantitative reverse transcription-PCR (ARMS-RT-qPCR) based on the two mutations was developed for identifying both VOCs. The assay can detect as little as 1 copy/µL of the VOCs, and the results for identifying Alpha and Delta variants in clinical samples by the ARMS-RT-qPCR assay showed 100% agreement with the results using sequencing-based methods. The whole assay can be completed in 2.5 h using commercial fluorescent PCR instruments. Therefore, the ARMS-RT-qPCR assay could be used for screening the two highly concerning variants Alpha and Delta by normal PCR laboratories in airports and in hospitals and other health-related organizations. Additionally, based on the unique mutations identified by the genomic analysis, similar molecular assays can be developed for rapid identification of other VOCs. IMPORTANCE The current stage of the pandemic, led by SARS-CoV-2 variants of concern (VOCs), underscores the necessity to develop a cost-effective and rapid molecular diagnosis assay to differentiate the VOCs. In this study, over 1 million SARS-CoV-2 genomic sequences of high quality from GISAID were analyzed and a network of the common mutations of the lineages was constructed. The conserved unique mutations specific for SARS-CoV-2 VOCs were found. Then, ARMS-RT-qPCR assays based on the two unique mutations of the Alpha and Delta variants were developed for the detection of the two VOCs. Application of the assay in clinical samples demonstrated that the current method is a convenient, cost-effective, and rapid way to screen the target SARS-CoV-2 VOCs.

Colorimetric Sensing with Gold Nanoparticles on Electrowetting-Based Digital Microfluidics.

Digital microfluidic (DMF) has been a unique tool for manipulating micro-droplets with high flexibility and accuracy. To extend the application of DMF for automatic and in-site detection, it is promising to introduce colorimetric sensing based on gold nanoparticles (AuNPs), which have advantages including high sensitivity, label-free, biocompatibility, and easy surface modification. However, there is still a lack of studies for investigating the movement and stability of AuNPs for in-site detection on the electrowetting-based digital microfluidics. Herein, to demonstrate the ability of DMF for colorimetric sensing with AuNPs, we investigated the electrowetting property of the AuNPs droplets on the hydrophobic interface of the DMF chip and examined the stability of the AuNPs on DMF as well as the influence of evaporation to the colorimetric sensing. As a result, we found that the electrowetting of AuNPs fits to a modified Young-Lippmann equation, which suggests that a higher voltage is required to actuate AuNPs droplets compared with actuating water droplets. Moreover, the stability of AuNPs was maintained during the processing of electrowetting. We also proved that the evaporation of droplets has a limited influence on the detections that last several minutes. Finally, a model experiment for the detection of Hg2+ was carried out with similar results to the detections in bulk solution. The proposed method can be further extended to a wide range of AuNPs-based detection for label-free, automatic, and low-cost detection of small molecules, biomarkers, and metal ions.

Tailoring glucocorticoids in patients with severe COVID-19: a narrative review.

OBJECTIVE: To discuss the pathogenesis of severe coronavirus disease 2019 (COVID-19) infection and the pharmacological effects of glucocorticoids (GCs) toward this infection. To review randomized controlled trials (RCTs) using GCs to treat patients with severe COVID-19, and investigate whether GC timing, dosage, or duration affect clinical outcomes. Finally. to discuss the use of biological markers, respiratory parameters, and radiological evidence to select patients for improved GC therapeutic precision. BACKGROUND: COVID-19 has become an unprecedented global challenge. As GCs have been used as key immunomodulators to treat inflammation-related diseases, they may play key roles in limiting disease progression by modulating immune responses, cytokine production, and endothelial function in patients with severe COVID-19, who often experience excessive cytokine production and endothelial and renin-angiotensin system (RAS) dysfunction. Current clinical trials have partially proven this efficacy, but GC timing, dosage, and duration vary greatly, with no unifying consensus, thereby creating confusion. METHODS: Publications through March 2021 were retrieved from the Web of Science and PubMed. Results from cited references in published articles were also included. CONCLUSIONS: GCs play key roles in treating severe COVID-19 infections. Pharmacologically, GCs could modulate immune cells, reduce cytokine and chemokine, and improve endothelial functions in patients with severe COVID-19. Benefits of GCs have been observed in multiple clinical trials, but the timing, dosage and duration vary across studies. Tapering as an option is not widely accepted. However, early initiation of treatment, a tailored dosage with appropriate tapering may be of particular importance, but evidence is inconclusive and more investigations are needed. Biological markers, respiratory parameters, and radiological evidence could also help select patients for specific tailored treatments.

Interruption Risk Assessment and Transmission of Fresh Cold Chain Network Based on a Fuzzy Bayesian Network

The fresh cold chain network is complex, and the interruption risk can significantly impact it. Based on the Bayesian theory, we constructed a fresh cold chain network interruption risk topology structure. The probability of each root node was predicted and calculated based on the fuzzy set theory. The evaluation model was then validated and improved through the virus transmission model based on risk transmission. Sensitivity analysis was used to determine significant risk factors. Several strategies for minimizing interruption risks were identified.

Using remote consultation to enhance diagnostic accuracy of bedside transthoracic echocardiography during COVID-19 pandemic.

OBJECTIVE: The aim of this study was to evaluate the clinical significance of remote consultation over bedside transthoracic echocardiography (RC-B-TTE) for patients with coronavirus disease 2019 (COVID-19). METHODS: Five frontline echocardiographers performed and interpreted B-TTE for 30 patients with COVID-19 in the isolation wards, and the on-site B-TTE reports (OSR) were generated. Then remote consultation over the 30 B-TTE studies was conducted by two experienced echocardiographic consultants while blinded to the OSR, and the corresponding remote consultation reports (RCR) were generated. Subsequently, the five frontline echocardiographers were convened together to discuss the difference between the OSR and RCR, and to confirm the correct interpretation and the misdiagnosis using a "majority-vote" consensus as the diagnostic "gold standard". Afterwards the reasons for the misdiagnosis were given by the frontline echocardiographers themselves. The inter-rater agreement between the OSR and the "gold standard" was assessed using Kappa coefficient and percent agreement. RESULTS: Complete correctness of the 30 copies of the RCR were determined by the 5 frontline echocardiographers. The reliability of the OSR in the findings of cardiac chamber dilation, left ventricular hypertrophy and pulmonary hypertension were weak (Kappa <0.6). The reliability of the OSR in the recognition of major cardiac abnormalities was very weak (Kappa =0.304, percent agreement =63.3%). Misdiagnosis of major abnormalities was found in 11 copies of OSR (11/30, 36.7%). CONCLUSIONS: The protocol of RC-B-TTE has shown noticeable superiority in ameliorating diagnostic accuracy of echocardiography, which should be generalized to clinical practice during the COVID-19 or similar pandemic.

Next-Generation Sequencing Reveals the Progression of COVID-19.

The novel coronavirus SARS-CoV-2 (causing the disease COVID-19) has caused a highly transmissible and ongoing pandemic worldwide. Due to its rapid development, next-generation sequencing plays vital roles in many aspects. Here, we summarize the current knowledge on the origin and human transmission of SARS-CoV-2 based on NGS analysis. The ACE2 expression levels in various human tissues and relevant cells were compared to provide insights into the mechanism of SAS-CoV-2 infection. Gut microbiota dysbiosis observed by metagenome sequencing and the immunogenetics of COVID-19 patients according to single-cell sequencing analysis were also highlighted. Overall, the application of these sequencing techniques could be meaningful for finding novel intermediate SARS-CoV-2 hosts to block interspecies transmission. This information will further benefit SARS-CoV-2 diagnostic development and new therapeutic target discovery. The extensive application of NGS will provide powerful support for our fight against future public health emergencies.