A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics.

During the diagnostic process, clinicians leverage multimodal information, such as the chief complaint, medical images and laboratory test results. Deep-learning models for aiding diagnosis have yet to meet this requirement of leveraging multimodal information. Here we report a transformer-based representation-learning model as a clinical diagnostic aid that processes multimodal input in a unified manner. Rather than learning modality-specific features, the model leverages embedding layers to convert images and unstructured and structured text into visual tokens and text tokens, and uses bidirectional blocks with intramodal and intermodal attention to learn holistic representations of radiographs, the unstructured chief complaint and clinical history, and structured clinical information such as laboratory test results and patient demographic information. The unified model outperformed an image-only model and non-unified multimodal diagnosis models in the identification of pulmonary disease (by 12% and 9%, respectively) and in the prediction of adverse clinical outcomes in patients with COVID-19 (by 29% and 7%, respectively). Unified multimodal transformer-based models may help streamline the triaging of patients and facilitate the clinical decision-making process.

Construction of Gene Expression Patterns to Identify Critical Genes under SARS-CoV-2 Infection Conditions.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a positive-stranded single-stranded RNA virus with an envelope frequently altered by unstable genetic material, making it extremely difficult for vaccines, drugs, and diagnostics to work. Understanding SARS-CoV-2 infection mechanisms requires studying gene expression changes. Deep learning methods are often considered for large-scale gene expression profiling data. Data feature-oriented analysis, however, neglects the biological process nature of gene expression, making it difficult to describe gene expression behaviors accurately. In this paper, we propose a novel scheme for modeling gene expression during SARS-CoV-2 infection as networks (gene expression modes, GEM), to characterize their expression behaviors. On this basis, we investigated the relationships among GEMs to determine SARS-CoV-2's core radiation mode. Our final experiments identified key COVID-19 genes by gene function enrichment, protein interaction, and module mining. Experimental results show that ATG10, ATG14, MAP1LC3B, OPTN, WDR45, and WIPI1 genes contribute to SARS-CoV-2 virus spread by affecting autophagy.

Comparing T- and B-cell responses to COVID-19 vaccines across varied immune backgrounds.

The emergence of adapted variants of the SARS-CoV-2 virus has led to a surge in breakthrough infections worldwide. A recent analysis of immune responses in people who received inactivated vaccines has revealed that individuals with no prior infection have limited resistance to Omicron and its sub-lineages, while those with previous infections exhibit a significant amount of neutralizing antibodies and memory B cells. However, specific T-cell responses remain largely unaffected by the mutations, indicating that T-cell-mediated cellular immunity can still provide protection. Moreover, the administration of a third dose of vaccine has resulted in a marked increase in the spectrum and duration of neutralizing antibodies and memory B cells in vivo, which has enhanced resistance to emerging variants such as BA.2.75 and BA.2.12.1. These results highlight the need to consider booster immunization for previously infected individuals and the development of novel vaccination strategies. The rapid spread of adapted variants of the SARS-CoV-2 virus presents a significant challenge to global health. The findings from this study underscore the importance of tailoring vaccination strategies based on individual immune backgrounds and the potential need for booster shots to combat emerging variants. Continued research and development are crucial to discovering new immunization strategies that will effectively protect public health against the evolving virus.

Identification of priority pathogens for aetiological diagnosis in adults with community-acquired pneumonia in China: a multicentre prospective study.

BACKGROUND: Community-acquired pneumonia (CAP) is a major public health challenge worldwide. However, the aetiological and disease severity-related pathogens associated with CAP in adults in China are not well established based on the detection of both viral and bacterial agents. METHODS: A multicentre, prospective study was conducted involving 10 hospitals located in nine geographical regions in China from 2014 to 2019. Sputum or bronchoalveolar lavage fluid (BALF) samples were collected from each recruited CAP patient. Multiplex real-time PCR and bacteria culture methods were used to detect respiratory pathogens. The association between detected pathogens and CAP severity was evaluated. RESULTS: Among the 3,403 recruited eligible patients, 462 (13.58%) had severe CAP, and the in-hospital mortality rate was 1.94% (66/3,403). At least one pathogen was detected in 2,054 (60.36%) patients, with two or more pathogens were co-detected in 725 patients. The ten major pathogens detected were Mycoplasma pneumoniae (11.05%), Haemophilus influenzae (10.67%), Klebsiella pneumoniae (10.43%), influenza A virus (9.49%), human rhinovirus (9.02%), Streptococcus pneumoniae (7.43%), Staphylococcus aureus (4.50%), adenovirus (2.94%), respiratory syncytial viruses (2.35%), and Legionella pneumophila (1.03%), which accounted for 76.06-92.52% of all positive detection results across sampling sites. Klebsiella pneumoniae (p < 0.001) and influenza viruses (p = 0.005) were more frequently detected in older patients, whereas Mycoplasma pneumoniae was more frequently detected in younger patients (p < 0.001). Infections with Klebsiella pneumoniae, Staphylococcus aureus, influenza viruses and respiratory syncytial viruses were risk factors for severe CAP. CONCLUSIONS: The major respiratory pathogens causing CAP in adults in China were different from those in USA and European countries, which were consistent across different geographical regions over study years. Given the detection rate of pathogens and their association with severe CAP, we propose to include the ten major pathogens as priorities for clinical pathogen screening in China.

Impact of the COVID-19 pandemic on cancer healthcare utilization in southwestern China on March 2021.

BACKGROUND: Oncological care has been disrupted worldwide during the COVID-19 pandemic. We aimed to quantify the long-term impact of the pandemic on cancer care utilization and to examine how this impact varied by sociodemographic and clinical factors in southwestern China, where the Dynamic Zero-COVID Strategy was implemented. This strategy mainly included lockdowns, stringent testing, and travel restrictions to prevent the spread of COVID-19. METHOD: We identified 859,497 episodes of the utilization of cancer care from electronic medical records between January 1, 2019, and March 31, 2021, from the cancer center of a tertiary hospital serving an estimated population of 8.4 million in southwestern China. Changes in weekly utilization were evaluated via segmented Poisson regression across service categories, stratified by cancer type and sociodemographic factors. RESULTS: A sharp reduction in utilization of in-person cancer services occurred during the first week of the pandemic outbreak in January 2020, followed by a quick rebound in February 2020. Although there were few COVID-19 cases from March 2020 until this analysis, the recovery of most in-person services was slow and remained incomplete as of March 31, 2021. The exceptions were outpatient radiation and surgery, which increased and exceeded pre-pandemic levels, particularly among lung cancer patients; meanwhile, telemedicine utilization increased substantially after the onset of the pandemic. Care disruptions were most prominent for women, rural residents, uninsured, and breast cancer patients. CONCLUSIONS: As of March 2021, despite few COVID-19 cases, the COVID-19 pandemic has had a strong and continuing impact on in-person oncology care utilization in southwestern China under the Dynamic Zero-COVID Strategy. Equitable and timely access to cancer care requires adjustment in strict policies for COVID-19 prevention and control, as well as targeted remedies for the most vulnerable populations during and beyond the pandemic. Future studies should monitor the long-term effects of the COVID-19 pandemic and response strategies on cancer care and outcomes.

SARS-CoV-2 SUD2 and Nsp5 Conspire to Boost Apoptosis of Respiratory Epithelial Cells via an Augmented Interaction with the G-Quadruplex of BclII.

The molecular mechanisms underlying how SUD2 recruits other proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to exert its G-quadruplex (G4)-dependent pathogenic function is unknown. Herein, Nsp5 was singled out as a binding partner of the SUD2-N+M domains (SUD2core) with high affinity, through the surface located crossing these two domains. Biochemical and fluorescent assays demonstrated that this complex also formed in the nucleus of living host cells. Moreover, the SUD2core-Nsp5 complex displayed significantly enhanced selective binding affinity for the G4 structure in the BclII promoter than did SUD2core alone. This increased stability exhibited by the tertiary complex was rationalized by AlphaFold2 and molecular dynamics analysis. In line with these molecular interactions, downregulation of BclII and subsequent augmented apoptosis of respiratory cells were both observed. These results provide novel information and a new avenue to explore therapeutic strategies targeting SARS-CoV-2. IMPORTANCE SUD2, a unique protein domain closely related to the pathogenesis of SARS-CoV-2, has been reported to bind with the G-quadruplex (G4), a special noncanonical DNA structure endowed with important functions in regulating gene expression. However, the interacting partner of SUD2, among other SARS-CoV-2 Nsps, and the resulting functional consequences remain unknown. Here, a stable complex formed between SUD2 and Nsp5 was fully characterized both in vitro and in host cells. Moreover, this complex had a significantly enhanced binding affinity specifically targeting the Bcl2G4 in the promoter region of the antiapoptotic gene BclII, compared with SUD2 alone. In respiratory epithelial cells, the SUD2-Nsp5 complex promoted BclII-mediated apoptosis in a G4-dependent manner. These results reveal fresh information about matched multicomponent interactions, which can be parlayed to develop new therapeutics for future relevant viral disease.

Metatranscriptomic Analysis Reveals Disordered Alterations in Oropharyngeal Microbiome during the Infection and Clearance Processes of SARS-CoV-2: A Warning for Secondary Infections.

This study was conducted to investigate oropharyngeal microbiota alterations during the progression of coronavirus disease 2019 (COVID-19) by analyzing these alterations during the infection and clearance processes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The diagnosis of COVID-19 was confirmed by using positive SARS-CoV-2 quantitative reverse transcription polymerase chain reaction (RT-qPCR). The alterations in abundance, diversity, and potential function of the oropharyngeal microbiome were identified using metatranscriptomic sequencing analyses of oropharyngeal swab specimens from 47 patients with COVID-19 (within a week after diagnosis and within two months after recovery from COVID-19) and 40 healthy individuals. As a result, in the infection process of SARS-CoV-2, compared to the healthy individuals, the relative abundances of Prevotella, Aspergillus, and Epstein-Barr virus were elevated; the alpha diversity was decreased; the beta diversity was disordered; the relative abundance of Gram-negative bacteria was increased; and the relative abundance of Gram-positive bacteria was decreased. After the clearance of SARS-CoV-2, compared to the healthy individuals and patients with COVID-19, the above disordered alterations persisted in the patients who had recovered from COVID-19 and did not return to the normal level observed in the healthy individuals. Additionally, the expressions of several antibiotic resistance genes (especially multi-drug resistance, glycopeptide, and tetracycline) in the patients with COVID-19 were higher than those in the healthy individuals. After SARS-CoV-2 was cleared, the expressions of these genes in the patients who had recovered from COVID-19 were lower than those in the patients with COVID-19, and they were different from those in the healthy individuals. In conclusion, our findings provide evidence that potential secondary infections with oropharyngeal bacteria, fungi, and viruses in patients who have recovered from COVID-19 should not be ignored; this evidence also highlights the clinical significance of the oropharyngeal microbiome in the early prevention of potential secondary infections of COVID-19 and suggests that it is imperative to choose appropriate antibiotics for subsequent bacterial secondary infection in patients with COVID-19.

Comparison of clinical characteristics between COVID-19 and H7N9 fatal cases: An observational study.

Objective: The outbreak of COVID-19 in 2020 is reminiscent of the H7N9 outbreak in 2013, which poses a huge threat to human health. We aim to compare clinical features and survival factors in fatal cases of COVID-19 and H7N9. Methods: Data on confirmed COVID-19 and H7N9 fatal cases identified in mainland China were analyzed to compare demographic characteristics and clinical severity. Survival curves were estimated by the Kaplan-Meier method and compared using log-rank tests and a restricted mean survival time model. A Cox regression model was used to identify survival factors in fatal cases of COVID-19 and H7N9. Results: Similar demographic characteristics were observed in fatal cases of COVID-19 and H7N9. The proportion of fatal cases of H7N9 receiving antibiotics, antiviral drugs, and oxygen treatment was higher than that of COVID-19. The potential protective factors for fatal COVID-19 cases were receiving antibiotics (HR: 0.37, 95% CI: 0.22-0.61), oxygen treatment (HR: 0.66, 95% CI: 0.44-0.99), and corticosteroids (HR: 0.46, 95% CI: 0.35-0.62). In contrast, antiviral drugs (HR: 0.21, 95% CI: 0.08-0.56) and corticosteroids (HR: 0.45, 95% CI: 0.29-0.69) were the protective factors for H7N9 fatal cases. Conclusion: The proportion of males, those having one or more underlying medical condition, and older age was high in COVID-19 and H7N9 fatal cases. Offering antibiotics, oxygen treatment, and corticosteroids to COVID-19 cases extended the survival time. Continued global surveillance remains an essential component of pandemic preparedness.

Network pharmacology- and molecular simulation-based exploration of therapeutic targets and mechanisms of heparin for the treatment of sepsis/COVID-19.

Critically infected patients with COVID-19 (coronavirus disease 2019) are prone to develop sepsis-related coagulopathy as a result of a robust immune response. The mechanism underlying the relationship between sepsis and COVID-19 is largely unknown. LMWH (low molecular weight heparin) exhibits both anti-inflammatory and anti-coagulating properties that result in a better prognosis of severely ill patients with COVID-19 co-associated with sepsis-induced coagulopathy or with a higher D-dimer value. Heparin-associated molecular targets and their mechanism of action in sepsis/COVID-19 are not well understood. In this work, we characterize the pharmacological targets, biological functions and therapeutic actions of heparin in sepsis/COVID-19 from the perspective of network pharmacology. A total of 38 potential targets for heparin action against sepsis/COVID-19 and 8 core pharmacological targets were identified, including IL6, KNG1, CXCL8, ALB, VEGFA, F2, IL10 and TNF. Moreover, enrichment analysis showed that heparin could help in treating sepsis/COVID-19 through immunomodulation, inhibition of the inflammatory response, regulation of angiogenesis and antiviral activity. The pharmacological effects of heparin against these targets were further confirmed by molecular docking and simulation analysis, suggesting that heparin exerts effective binding capacity by targeting the essential residues in sepsis/COVID-19. Prospective clinical practice evaluations may consider the use of these key prognostic indicators for the treatment of sepsis/COVID-19.Communicated by Ramaswamy H. Sarma.

Comparison of clinical characteristics between COVID-19 and H7N9 fatal cases: An observational study

Objective The outbreak of COVID-19 in 2020 is reminiscent of the H7N9 outbreak in 2013, which poses a huge threat to human health. We aim to compare clinical features and survival factors in fatal cases of COVID-19 and H7N9. Methods Data on confirmed COVID-19 and H7N9 fatal cases identified in mainland China were analyzed to compare demographic characteristics and clinical severity. Survival curves were estimated by the Kaplan–Meier method and compared using log-rank tests and a restricted mean survival time model. A Cox regression model was used to identify survival factors in fatal cases of COVID-19 and H7N9. Results Similar demographic characteristics were observed in fatal cases of COVID-19 and H7N9. The proportion of fatal cases of H7N9 receiving antibiotics, antiviral drugs, and oxygen treatment was higher than that of COVID-19. The potential protective factors for fatal COVID-19 cases were receiving antibiotics (HR: 0.37, 95% CI: 0.22–0.61), oxygen treatment (HR: 0.66, 95% CI: 0.44–0.99), and corticosteroids (HR: 0.46, 95% CI: 0.35–0.62). In contrast, antiviral drugs (HR: 0.21, 95% CI: 0.08–0.56) and corticosteroids (HR: 0.45, 95% CI: 0.29–0.69) were the protective factors for H7N9 fatal cases. Conclusion The proportion of males, those having one or more underlying medical condition, and older age was high in COVID-19 and H7N9 fatal cases. Offering antibiotics, oxygen treatment, and corticosteroids to COVID-19 cases extended the survival time. Continued global surveillance remains an essential component of pandemic preparedness.

CASA: a comprehensive database resource for the COVID-19 Alternative Splicing Atlas.

BACKGROUND: As a key process in transcriptional regulatory mechanisms, alternative splicing (AS) plays a crucial role in maintaining the diversity of RNA and protein expression, and mediates the immune response in infectious diseases, especially for the COVID-19. Therefore, urgent data gathering and more research of AS profiles in microbe-infected human cells are needed to improve understanding of COVID-19 and related infectious diseases. Herein, we have created CASA, the COVID-19 Alternative Splicing Atlas to provide a convenient computing platform for studies of AS in COVID-19 and COVID-19-related infectious diseases. METHODS: In CASA, we reanalyzed thousands of RNA-seq datasets generated from 65 different tissues, organoids and cell lines to systematically obtain quantitative data on AS events under different conditions. A total of 262,994 AS events from various infectious diseases with differing severity were detected and visualized in this database. In order to explore the potential function of dynamics AS events, we performed analysis of functional annotations and drug-target interactions affected by AS in each dataset. RNA-binding proteins (RBPs), which may regulate these dynamic AS events are also provided for users in this database. RESULTS: CASA displays microbe-induced alterations of the host cell splicing landscape across different virus families and helps users identify condition-specific splicing patterns, as well as their potential regulators. CASA may greatly facilitate the exploration of AS profiles and novel mechanisms of host cell splicing by viral manipulation. CASA is freely available at http://www.splicedb.net/casa/ .

Impaired kidney function biomarkers and risk of severe COVID-19: Analysis of population-based cohort data.

BACKGROUND: Patients with impaired kidney function were found at a high risk of COVID-19 hospitalization and mortality in many observational, cross-sectional, and hospital-based studies, but evidence from large-scale prospective cohorts has been lacking. We aimed to examine the association of kidney function-related biomarkers and their genetic predisposition with the risk of developing severe COVID-19 in population-based data. METHODS: We analyzed data from UK Biobank to examine the prospective association of abnormal kidney function biomarkers with severe COVID-19, defined by laboratory-confirmed COVID-19 hospitalizations. Using genotype data, we constructed polygenic risk scores (PRS) to represent an individual's overall genetic risk for these biomarkers. We also identified tipping points where the risk of severe COVID-19 began to increase significantly for each biomarker. RESULTS: Of the 502,506 adults, 1650 (0.32%) were identified as severe COVID-19, before August 12, 2020. High levels of cystatin C (OR: 1.3; 95% CI: 1.2-1.5; FDR = 1.5 × 10-5 ), serum creatinine (OR: 1.7; 95% CI: 1.3-2.1; p = 3.5 × 10-4 ; FDR = 3.5 × 10-4 ), microalbuminuria (OR: 1.4; 95% CI: 1.2-1.6; FDR = 4 × 10-4 ), and UACR (urinary albumin creatinine ratio; OR: 1.4; 95% CI: 1.2-1.6; p = 3.5 × 10-4 ; FDR = 3.5 × 10-4 ) were found significantly associated with severe COVID-19. Individuals with top 10% of PRS for elevated cystatin C, urate, and microalbuminuria had 28% to 43% higher risks of severe COVID-19 than individuals with bottom 30% PRS (p < 0.05). Tipping-point analyses further supported that severe COVID-19 could occur even when the values of cystatin C, urate (male), and microalbuminuria were within their normal value ranges (OR >1.1, p < 0.05). CONCLUSIONS: Findings from this study might point to new directions for clinicians and policymakers in optimizing risk-stratification among patients based on polygenic risk estimation and tipping points of kidney function markers. Our results call for further investigation to develop a better strategy to prevent severe COVID-19 outcomes among patients with genetic predisposition to impaired kidney function. These findings could provide a new tool for clinicians and policymakers in the future especially if we need to live with COVID-19 for a long time.

The epidemiology and therapeutic options for the COVID-19.

An outbreak of coronavirus disease 2019 (COVID-19), a disease caused by a novel pneumonia virus, has affected over 200 countries and regions worldwide. With the increasing number of patients and deaths, WHO have declared it as a global pandemic currently, indicating a third large-scale epidemic coronavirus has appeared since the emergence of severe acute respiratory syndrome coronavirus (SARS) and Middle-East respiratory syndrome (MERS) in the twenty-first century. Considering the great harm it has caused, researchers throughout the world have been chasing to exploit the pathophysiology, characteristics, and potential remedies for COVID-19 to better battle the outbreak. Therefore, the current study revisits advances of the virology, epidemiology, clinical features, therapeutic options, and prevention of COVID-19. The features of asymptomatic carriers are also been explored.

Cross-Verification of COVID-19 Information Obtained From Unofficial Social Media Accounts and Associated Changes in Health Behaviors: Web-Based Questionnaire Study Among Chinese Netizens.

BACKGROUND: As social media platforms have become significant sources of information during the pandemic, a significant volume of both factual and inaccurate information related to the prevention of COVID-19 has been disseminated through social media. Thus, disparities in COVID-19 information verification across populations have the potential to promote the dissemination of misinformation among clustered groups of people with similar characteristics. OBJECTIVE: This study aimed to identify the characteristics of social media users who obtained COVID-19 information through unofficial social media accounts and were (1) most likely to change their health behaviors according to web-based information and (2) least likely to actively verify the accuracy of COVID-19 information, as these individuals may be susceptible to inaccurate prevention measures and may exacerbate transmission. METHODS: An online questionnaire consisting of 17 questions was disseminated by West China Hospital via its official online platforms, between May 18, 2020, and May 31, 2020. The questionnaire collected the sociodemographic information of 14,509 adults, and included questions surveying Chinese netizens' knowledge about COVID-19, personal social media use, health behavioral change tendencies, and cross-verification behaviors for web-based information during the pandemic. Multiple stepwise regression models were used to examine the relationships between social media use, behavior changes, and information cross-verification. RESULTS: Respondents who were most likely to change their health behaviors after obtaining web-based COVID-19 information from celebrity sources had the following characteristics: female sex (P=.004), age ≥50 years (P=.009), higher COVID-19 knowledge and health literacy (P=.045 and P=.03, respectively), non-health care professional (P=.02), higher frequency of searching on social media (P<.001), better health conditions (P<.001), and a trust rating score of more than 3 for information released by celebrities on social media (P=.005). Furthermore, among participants who were most likely to change their health behaviors according to social media information released by celebrities, female sex (P<.001), living in a rural residence rather than first-tier city (P<.001), self-reported medium health status and lower health care literacy (P=.007 and P<.001, respectively), less frequent search for COVID-19 information on social media (P<.001), and greater level of trust toward celebrities' social media accounts with a trust rating score greater than 1 (P≤.04) were associated with a lack of cross-verification of information. CONCLUSIONS: The findings suggest that governments, health care agencies, celebrities, and technicians should combine their efforts to decrease the risk in vulnerable groups that are inclined to change health behaviors according to web-based information but do not perform any fact-check verification of the accuracy of the unofficial information. Specifically, it is necessary to correct the false information related to COVID-19 on social media, appropriately apply celebrities' star power, and increase Chinese netizens' awareness of information cross-verification and eHealth literacy for evaluating the veracity of web-based information.

A paper-based assay for the colorimetric detection of SARS-CoV-2 variants at single-nucleotide resolution.

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted the need for versatile diagnostic assays that can discriminate among emerging variants of the virus. Here we report the development and performance benchmarking of an inexpensive (approximately US$0.30 per test) assay for the rapid (sample-to-answer time within 30 min) colorimetric detection of SARS-CoV-2 variants. The assay, which we integrated into foldable paper strips, leverages nucleic acid strand-displacement reactions, the thermodynamic energy penalty associated with single-base-pair mismatches and the metal-ion-controlled enzymatic cleavage of urea to amplify the recognition of viral RNAs for the colorimetric readout of changes in pH via a smartphone. For 50 throat swab samples, the assay simultaneously detected the presence of SARS-CoV-2 and mutations specific to the SARS-CoV-2 variants Alpha, Beta and Gamma, with 100% concordance with real-time quantitative polymerase chain reaction and RNA sequencing. Customizable and inexpensive paper-based assays for the detection of viruses and their variants may facilitate viral surveillance.

An orally available Mpro inhibitor is effective against wild-type SARS-CoV-2 and variants including Omicron.

Emerging SARS-CoV-2 variants continue to cause waves of new infections globally. Developing effective antivirals against SARS-CoV-2 and its variants is an urgent task. The main protease (Mpro) of SARS-CoV-2 is an attractive drug target because of its central role in viral replication and its conservation among variants. We herein report a series of potent α-ketoamide-containing Mpro inhibitors obtained using the Ugi four-component reaction. The prioritized compound, Y180, showed an IC50 of 8.1 nM against SARS-CoV-2 Mpro and had oral bioavailability of 92.9%, 31.9% and 85.7% in mice, rats and dogs, respectively. Y180 protected against wild-type SARS-CoV-2, B.1.1.7 (Alpha), B.1.617.1 (Kappa) and P.3 (Theta), with EC50 of 11.4, 20.3, 34.4 and 23.7 nM, respectively. Oral treatment with Y180 displayed a remarkable antiviral potency and substantially ameliorated the virus-induced tissue damage in both nasal turbinate and lung of B.1.1.7-infected K18-human ACE2 (K18-hACE2) transgenic mice. Therapeutic treatment with Y180 improved the survival of mice from 0 to 44.4% (P = 0.0086) upon B.1.617.1 infection in the lethal infection model. Importantly, Y180 was also highly effective against the B.1.1.529 (Omicron) variant both in vitro and in vivo. Overall, our study provides a promising lead compound for oral drug development against SARS-CoV-2.

CRISPR-Cas13a cascade-based viral RNA assay for detecting SARS-CoV-2 and its mutations in clinical samples.

SARS-CoV-2 is one of the greatest threats to global human health. Point-of-care diagnostic tools for SARS-CoV-2 could facilitate rapid therapeutic intervention and mitigate transmission. In this work, we report CRISPR-Cas13a cascade-based viral RNA (Cas13C) assay for label-free and isothermal determination of SARS-CoV-2 and its mutations in clinical samples. Cas13a/crRNA was utilized to directly recognize the target of SARS-CoV-2 RNA, and the recognition events sequentially initiate the transcription amplification to produce light-up RNA aptamers for output fluorescence signal. The recognition of viral RNA via Cas13a-guide RNA ensures a high specificity to distinguish SARS-CoV-2 from MERS-CoV and SARS-CoV, as well as viral mutations. A post transcription amplification strategy was triggered after CRISPR-Cas13a recognition contributes to an amplification cascade that achieves high sensitivity for detecting SARS-CoV-2 RNA, with a limit of detection of 0.216 fM. In addition, the Cas13C assay could be able to discriminate single-nucleotide mutation, which was proven with N501Y in SARS-Cov-2 variant. This method was validated by a 100% agreement with RT-qPCR results from 12 clinical throat swab specimens. The Cas13C assay has the potential to be used as a routine nucleic acid test of SARS-CoV-2 virus in resource-limited regions.

Readiness of healthcare providers for e-hospitals: a cross-sectional analysis in China before the COVID-19 period.

OBJECTIVES: The growth and development of smartphones and eHealth technologies have enabled the potential for extended care hospitals (e-hospitals) in China in order to facilitate the success of a primary healthcare centre (PHC)-based integrated delivery model. Although the adoption of e-hospitals is essential, few studies have directed their research towards understanding the perspectives of healthcare providers. This study aims to identify the current readiness of healthcare providers to adopt e-hospital technologies, determine the factors influencing this adoption and describe the perceived facilitators and barriers in regard to working at e-hospitals. DESIGN: A cross-sectional study conducted in Sichuan, China, between June and September 2019. SETTINGS: Information was collected from healthcare providers who have more than 3 years of work experience from a tertiary hospital, secondary hospital, PHCs and private hospital. PARTICIPANTS: 2298 medical professionals were included in this study. OUTCOME MEASURE: This study included a self-administered questionnaire that was used to assess participants' sociodemographic characteristics, online medical practices, willingness to use e-hospitals and perceived facilitators/barriers to working at e-hospitals. Multivariate regression analysis was performed in order to evaluate the independent factors associated with e-hospital work. RESULTS: Overall, 86.3% had a positive response towards working at e-hospitals. Age (p<0.05), familiarity with e-hospitals (p<0.001) and prior work practices in online healthcare settings (p<0.001) were associated with participants' readiness to work at e-hospitals. Gender, education level, professional level, the tier of their affiliated hospital and workload were not statistically associated. Healthcare providers who had positive attitudes towards e-hospitals considered improved efficiency, patient satisfaction, communication among physicians, increased reputation and income, and alleviated workload to be advantages of adoption. The participants who were unwilling to work at e-hospitals perceived lack of time, insufficient authenticity/reliability and underdeveloped policies as potential barriers. CONCLUSION: Improving operative proficiency in electronic devices, accommodating to work schedules, increasing familiarity with e-hospitals and regulating practices will improve the readiness of healthcare providers to work at e-hospitals.

Mechanistic Studies of an Automated Lipid Nanoparticle Reveal Critical Pharmaceutical Properties Associated with Enhanced mRNA Functional Delivery In Vitro and In Vivo.

Recently, lipid nanoparticles (LNPs) have attracted attention due to their emergent use for COVID-19 mRNA vaccines. The success of LNPs can be attributed to ionizable lipids, which enable functional intracellular delivery. Previously, the authors established an automated high-throughput platform to screen ionizable lipids and identified that the LNPs generated using this automated technique show comparable or increased mRNA functional delivery in vitro as compared to LNPs prepared using traditional microfluidics techniques. In this study, the authors choose one benchmark lipid, DLin-MC3-DMA (MC3), and investigate whether the automated formulation technique can enhance mRNA functional delivery in vivo. Interestingly, a 4.5-fold improvement in mRNA functional delivery in vivo by automated LNPs as compared to LNPs formulated by conventional microfluidics techniques, is observed. Mechanistic studies reveal that particles with large size accommodate more mRNA per LNP, possess more hydrophobic surface, are more hemolytic, bind a larger protein corona, and tend to accumulate more in macropinocytosomes, which may quantitatively benefit mRNA cytosolic delivery. These data suggest that mRNA loading per particle is a critical factor that accounts for the enhanced mRNA functional delivery of automated LNPs. These mechanistic findings provide valuable insight underlying the enhanced mRNA functional delivery to accelerate future mRNA LNP product development.