High-affinity binding to the SARS-CoV-2 spike trimer by a nanostructured, trivalent protein-DNA synthetic antibody (preprint)

Multivalency enables nanostructures to bind molecular targets with high affinity. Although antibodies can be generated against a wide range of antigens, their shape and size cannot be tuned to match a given target. DNA nanotechnology provides an attractive approach for designing customized multivalent scaffolds due to the addressability and programmability of the nanostructure shape and size. Here, we design a nanoscale synthetic antibody ("nano-synbody") based on a three-helix bundle DNA nanostructure with one, two, or three identical arms terminating in a mini-binder protein that targets the SARS-CoV-2 spike protein. The nano-synbody was designed to match the valence and distance between the three receptor binding domains (RBDs) in the spike trimer, in order to enhance affinity. The protein-DNA nano-synbody shows tight binding to the wild-type, Delta, and several Omicron variants of the SARS-CoV-2 spike trimer, with affinity increasing as the number of arms increases from one to three. The effectiveness of the nano-synbody was also verified using a pseudovirus neutralization assay, with the three-arm nanostructure inhibiting two Omicron variants against which the structures with only one or two arms are ineffective. The structure of the three-arm nano-synbody bound to the Omicron variant spike trimer was solved by negative-stain transmission electron microscopy reconstruction, and shows the protein-DNA nanostructure with all three arms attached to the RBD domains, confirming the intended trivalent attachment. The ability to tune the size and shape of the nano-synbody, as well as its potential ability to attach two or more different binding ligands, will enable the high-affinity targeting of a range of proteins not possible with traditional antibodies.

LS-MolGen: Ligand-and-Structure Dual-driven Deep Reinforcement Learning for Target-specific Molecular Generation Improves Binding Affinity and Novelty (preprint)

Molecule generative models based on deep learning have attracted significant attention in de novo drug design. However, most current generative approaches are either only ligand-based or only structure-based, which do not leverage the complementary knowledge from ligands and the structure of binding target. In this work, we proposed a new ligand and structure combined molecular generative model, LS-MolGen, that integrates representation learning, transfer learning, and reinforcement learning. Focus knowledge from transfer learning and special explore strategy in reinforcement learning enables LS-MolGen to generate novel and active molecules efficiently. The results of evaluation using EGFR and case study of inhibitor design for SARS-CoV-2 Mpro showed that LS-MolGen outperformed other state-of-the-art ligand-based or structure-based generative models and was capable of de novo designing promising compounds with novel scaffold and high binding affinity. Thus, we recommend that this proof-of-concept ligand-and-structure-based generative model will provide a promising new tool for target-specific molecular generation and drug design.

Scale Effects in Ridesplitting: A Case Study of the City of Chicago (preprint)

Ridesplitting -- a type of ride-hailing in which riders share vehicles with other riders -- has become a common travel mode in some major cities. This type of shared ride option is currently provided by transportation network companies (TNCs) such as Uber, Lyft, and Via and has attracted increasing numbers of users, particularly before the COVID-19 pandemic. Previous findings have suggested ridesplitting can lower travel costs and even lessen congestion by reducing the number of vehicles needed to move people. Recent studies have also posited that ridesplitting should experience positive feedback mechanisms in which the quality of the service would improve with the number of users. Specifically, these systems should benefit from economies of scale and increasing returns to scale. This paper demonstrates evidence of their existence using trip data reported by TNCs to the City of Chicago between January and September 2019. Specifically, it shows that increases in the number of riders requesting or authorizing shared trips during a given time period is associated with shorter trip detours, higher rates of riders being matched together, lower costs relative to non-shared trips, and higher willingness for riders to share trips.

National IoMT platform strategy portfolio decision model under the COVID-19 environment: based on the financial and non-financial value view

The Internet of Medical Things (IoMT) is an emerging technology in the healthcare revolution which provides real-time healthcare information communication and reasonable medical resource allocation. The COVID-19 pandemic has had a significant effect on people’s lives and has affected healthcare capacities. It is important for integrated IoMT platform development to overcome the global pandemic challenges. This study proposed the national IoMT platform strategy portfolio decision-making model from the non-financial (technology, organization, environment) and financial perspectives. As a solution to the decision problem, initially, the decision-making trial and evaluation laboratory (DEMATEL) technology were employed to capture the cause-effect relationship based on the perspectives and criteria obtained from the insight of an expert team. The analytic network process (ANP) and pairwise comparisons were then used to determine the weights for the strategy. Simultaneously, this study incorporated IoMT platform resource limitations into the zero–one goal programming (ZOGP) method to obtain an optimal portfolio selection for IoMT platform strategy planning. The results showed that the integrated MCDM method produced reasonable results for selecting the most appropriate IoMT platform strategy portfolio when considering resource constraints such as system installation costs, consultant fees, infrastructure costs, reduction of medical staff demand, and improvement rates for diagnosis efficiency. The decision-making model of the IoMT platform in this study was conclusive and significantly compelling to aid government decision makers in concentrating their efforts on planning IoMT strategies in response to various pandemic and medical resource allocations.

Automated de novo drug design and Anti-coronavirus activity studies of 3CLpro inhibitors (preprint)

Activity-based lead screening and druggability-based structure optimization are usually torn into two independent processes, although both are related to the chemical structure of target compounds. It leads to an unsatisfactory success ratio and inefficient drug development. DeepRLADS, a de novo molecular design assay, was established based on deep reinforcement learning training, integrating activity screening and structure optimization into a single artificial intelligence (AI)-based drug discovery module. Targeting the relatively easy-verified porcine epidemic diarrhea coronavirus (PEDV) main protease (Mpro, 3CLpro), a diverse virtual library of potential 3CLpro inhibitors was created by splitting existing inhibitors, digitizing fragments, and de novo design, focusing on their potential biological activities and pharmacological properties. The AI-designed compound 11b has a novel catechol-pyrazoline structure, presenting efficient inhibition against Mpro, surprising protection against PEDV infection, low toxicity, and favorable pharmacokinetic properties in vitro and in vivo. Low-dose oral 11b (5 mg/kg) reversed PEDV-induced diarrhea in 5-day-old piglets and greatly improved the survival rate (from 0% to 100%). A preclinical study (560 cases) in eight independent farms indicated an inspiring recovery rate (survival rate: 95.8% in treated piglets VS 9.1% in untreated piglets). Compound 11b is the first proven chemical efficiently protecting piglets in a large-scale preclinical study with multiple centers. It suggested that the novel strategy used by DeepRLADS was a hopeful approach for further AI-based drug design.

Advances in the use of nighttime light data to monitor and assess coastal fisheries under the impacts of human activities and climate and environmental changes: A case study in the Beibu Gulf

Nighttime light remote sensing has attracted increasing attention in fishery management due to its unique advantages in observing light fisheries. NASA's Black Marble product suite (VNP46A1) and Luojia 1–01 images are the latest nighttime light data with improved spatial and temporal resolutions. This paper developed an effective night-light fishing boat (NLFB) dataset to monitor and assess the coastal light fisheries in the Beibu Gulf. Daily NLFB data from 2018 to 2020 were used to map the spatiotemporal variations in fishing intensity, number of fishing boats and locations of core fishing areas. The influencing mechanisms of climate and environmental changes, fishery closures, COVID-19 and typhoons on the temporal and spatial variations in light fisheries were evaluated and discussed. Combined with the fishery boundaries defined by the China-Vietnam bilateral agreements, nighttime light remote sensing revealed the effective management of and restrictions on (such as fishery closures and lockdowns) fishing activities in the Chinese fishery area. The Vietnamese fishery area was under higher fishing pressure, especially in densely populated estuaries where the fish spawn and feed. Therefore, a cross-regional marine protected area (MPA) is recommended as a realistic strategy for the sustainable management of light fisheries in the Beibu Gulf. Nighttime light remote sensing provides a useful opportunity to combat illegal, unreported and unregulated (IUU) fishing in the future.

Linking ethical leadership to employees' emotional exhaustion: a chain mediation model

Purpose>Drawing upon conservation of resources theory, this study aims to explore how ethical leadership relates to subordinates' emotional exhaustion through the chain mediating effects of organizational networking behavior and organizational embeddedness.Design/methodology/approach>Data were collected from 447 airport employees in China. PROCESS macro in SPSS was used to test the hypotheses.Findings>Results indicated that ethical leadership is negatively correlated with emotional exhaustion;organizational networking behavior and organizational embeddedness play a chain mediating role in the negative relationship between ethical leadership and emotional exhaustion.Originality/value>This study provides new insights into the association between ethical leadership and emotional exhaustion, and enriches the antecedents and consequences of organizational networking behavior.

Characteristic analysis of Omicron‐included SARS‐CoV‐2 variants of concern

In view of the rapid development of the COVID‐19 pandemic and SARS‐CoV‐2 mutation, we characterized the emerging SARS‐CoV‐2 variants of concern (VOCs) by both bioinformatics methods and experiments. The representative genomic sequences of SARS‐CoV‐2 VOCs were first downloaded from NCBI, including the prototypic strain, Alpha (B.1.1.7) strain, Beta (B.1.351) strain, Delta (B.1.617.2), and Omicron (B1.1.529) strain. Bioinformatics analysis revealed that the D614G mutation led to formation of a protruding spike (S) in the tertiary structure of spike protein, which could be responsible for the enhanced binding to angiotensin‐converting enzyme 2 (ACE2) receptor. The epitope analysis further showed that the S protein antigenicity of the Omicron variant changed dramatically, which was possibly associated with its enhanced ability of immune escape. To verify the bioinformatics results, we performed experiments of pseudovirus infection and protein affinity assay. Notably, we found that the spike protein of Omicron variant showed the weakest infectivity and binding ability among all tested strains. Finally, we also proved this through virus infection experiments, and found that the cytotoxicity of Omicron seems to be not strong enough. The results in this study provide guidelines for prevention and control of COVID‐19. In this study, we first predicted and compared the structure of the S protein and B‐cell epitopes of different SARS‐CoV‐2 variants. Then, the binding ability of different SARS‐CoV‐2 variant S proteins to angiotensin‐converting enzyme 2 (ACE2) cells and the affinity of RBD region to ACE2 were further compared through pseudovirus infection and intermolecular binding ability test. Finally, cell infection experiments were performed. The results unexpectedly showed that Omicron possesses lower ACE2 binding capacity, and lower replication capacity than Delta strain.

Positive Changes in Life Outcomes over the Pandemic in Chinese Adolescents: The Role of Resilience and Relation to Mental Health (preprint)

Background: Although the existing literature has well documented the negative effects of COVID-19 on multiple life outcomes in adolescents, some research has also revealed that some life outcomes have become better during COVID-19. Scant research has specifically examined to what extent and in what aspects COVID-19 is beneficial to adolescent development so far. With person-centered approach, this research addressed this gap by: (1) exploring different profiles of positive changes in life outcomes in Chinese adolescents since the outbreak of COVID-19; (2) examining the role of resilience in relation to different profiles; (3) comparing mental health across adolescents categorized into different profiles. Method Participants were 2,567 Chinese adolescents aged 12 to 24. They rated how much their lives of different domains had experienced positive changes since the outbreak of the pandemic. They also answered the questionnaires that measured their resilience and mental health. Results Results of latent profile analysis revealed three different profiles: limited positive changes (33.3%), partial positive changes (49.5%), and overall strong positive changes (17.2%). Moreover, adolescents with a higher level of resilience were more likely to be categorized into the partial positive changes profile compared to the limited positive changes profile and into the overall strong positive changes profile compared to the other two profiles, after controlling for the covariates. Finally, adolescents in the overall strong positive changes profile had better mental health than their counterparts in the other two profiles. Conclusion COVID-19 might be helpful to adolescent development to some extent, especially for those with higher resilience.

Safety and Pharmacokinetics of Intranasally Administered Heparin (preprint)

Purpose Intranasally administered unfractionated heparin (UFH) and other sulfated polysaccharides are potential prophylactics for COVID-19. The purpose of this research was to measure the safety and pharmacokinetics of clearance of intranasally administered UFH solution from the nasal cavity. Methods Double-blinded daily intranasal dosing in C57Bl6 mice with four doses (60 ng to 60 ug) of UFH was carried out for fourteen consecutive days, with both blood coagulation measurements and subject adverse event monitoring. The pharmacokinetics of fluorescent-labeled UFH clearance from the nasal cavity were measured in mice by in vivo imaging. Intranasal UFH at 2000 U/day solution with nasal spray device was tested for safety in a small number of healthy human subjects. Results UFH showed no evidence of toxicity in mice at any dose measured. No significant changes were observed in activated partial thromboplastin time (aPTT), platelet count, or frequency of minor irritant events over vehicle-only control. Human subjects showed no significant changes in aPTT time, international normalized ratio (INR), or platelet count over baseline measurements. No serious adverse events were observed. In vivo imaging in a mouse model showed a two-phase clearance of UFH from the nasal cavity. After 12 hours, 2.1% of the initial administered UFH remained in the nasal cavity, decaying to background levels after 24 hours. Conclusions UFH showed no toxic effects for extended daily intranasal dosing in mice as well as humans. The clearance kinetics of intranasal heparin solution from the nasal cavity indicates potentially protective levels for up to 12 hours after dosing.

Development of a Europium Nanoparticles Lateral Flow Immunoassay for NGAL Detection in Urine and Diagnosis of Acute Kidney Injury (preprint)

Background: AKI is related to severe adverse outcomes and mortality with Coronavirus Infection Disease 2019 (COVID-19) patients, that early diagnosed and intervened is imperative. Neutrophil gelatinase-associated lipocalin (NGAL) is one of the most promising biomarkers for detection of acute kidney injury (AKI), but current detection methods are inadequacy, so more rapid, convenient and accuracy methods are needed to detect NGAL for early diagnosis of AKI. Herein, we established a rapid, reliable and accuracy lateral flow immunoassay based on europium nanoparticles (Eu-NPS-LFIA) for the detection of NGAL in human urine specimens. Methods: : A double-antibody sandwich immunofluorescent assay using europium doped nanoparticles was employed and the NGAL monoclonal antibodies conjugate as labels were generated by optimizing electric fusion parameters. Eighty-three urine samples were used to evaluate the clinical application efficiency of this method. Results: : The quantitative detection range of NGAL in AKI was 1-3000 ng/mL, and the detection sensitization was 0.36 ng/mL. The CV of intra-assay and inter-assay were 2.57%-4.98% and 4.11%-7.83%, respectively. Meanwhile, the correlation coefficient between Eu-NPS-LFIA and ARCHITECT analyzer was significant (R 2 =0.9829, n=83, p <0.01). Conclusions: : Thus, a faster and easier operation quantitative assay of NGAL for AKI has been established, which is very important and meaningful to diagnose the early AKI, suggesting that the assay can provide an early warning of final outcome of disease.

An all-solid-state heterojunction oxide transistor for the rapid detection of biomolecules and SARS-CoV-2 spike S1 protein (preprint)

Solid-state transistor sensors that can detect biomolecules in real time are highly attractive for emerging bioanalytical applications. However, combining cost-effective manufacturing with high sensitivity, specificity and fast sensing response, remains challenging. Here we develop low-temperature solution-processed In2O3/ZnO heterojunction transistors featuring a geometrically engineered tri-channel architecture for rapid real-time detection of different biomolecules. The sensor combines a high electron mobility channel, attributed to the quasi-two-dimensional electron gas (q2DEG) at the buried In2O3/ZnO heterointerface, in close proximity to a sensing surface featuring tethered analyte receptors. The unusual tri-channel design enables strong coupling between the buried q2DEG and the minute electronic perturbations occurring during receptor-analyte interactions allowing for robust, real-time detection of biomolecules down to attomolar (aM) concentrations. By functionalizing the tri-channel surface with SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) antibody receptors, we demonstrate real-time detection of the SARS-CoV-2 spike S1 protein down to attomolar concentrations in under two minutes.

Peripheral CD4⁺ T cell subsets and antibody response in COVID-19 convalescent individuals

BACKGROUND. Marked progress is achieved in understanding the physiopathology of coronavirus disease 2019 (COVID-19), which caused a global pandemic. However, the CD4· T cell population critical for antibody response in COVID-19 is poorly understood. METHODS. In this study, we provided a comprehensive analysis of peripheral CD4· T cells from 13 COVID-19 convalescent patients, defined as confirmed free of SARS-CoV-2 for 2 to 4 weeks, using flow cytometry and magnetic chemiluminescence enzyme antibody immunoassay. The data were correlated with clinical characteristics. RESULTS. We observed that, relative to healthy individuals, convalescent patients displayed an altered peripheral CD4· T cell spectrum. Specifically, consistent with other viral infections, cTfh1 cells associated with SARS-CoV-2-targeting antibodies were found in COVID-19 covalescent patients. Individuals with severe disease showed higher frequencies of Tem and Tfh-em cells but lower frequencies of Tcm, Tfh-cm, Tfr, and Tnaive cells, compared with healthy individuals and patients with mild and moderate disease. Interestingly, a higher frequency of cTfh-em cells correlated with a lower blood oxygen level, recorded at the time of admission, in convalescent patients. These observations might constitute residual effects by which COVID-19 can impact the homeostasis of CD4· T cells in the long-term and explain the highest ratio of class-switched virus-specific antibody producing individuals found in our severe COVID-19 cohort. CONCLUSION. Our study demonstrated a close connection between CD4· T cells and antibody production in COVID-19 convalescent patients. FUNDING. Six Talent Peaks Project in Jiangsu Province and the National Natural Science Foundation of China (NSFC).

Effective Inhibition of SARS-CoV-2 Entry by Heparin and Enoxaparin Derivatives (preprint)

Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) has caused a pandemic of historic proportions and continues to spread globally, with enormous consequences to human health. Currently there is no vaccine, effective therapeutic or prophylactic. Like other betacoronaviruses, attachment and entry of SARS-CoV-2 is mediated by the spike glycoprotein (SGP). In addition to its well-documented interaction with its receptor, human angiotensin converting enzyme 2 (hACE2), SGP has been found to bind to glycosaminoglycans like heparan sulfate, which is found on the surface of virtually all mammalian cells. Here, we pseudotyped SARS-CoV-2 SGP on a third generation lentiviral (pLV) vector and tested the impact of various sulfated polysaccharides on transduction efficiency in mammalian cells. The pLV vector pseudotyped SGP efficiently and produced high titers on HEK293T cells. Various sulfated polysaccharides potently neutralized pLV-S pseudotyped virus with clear structure-based differences in anti-viral activity and affinity to SGP. Concentration-response curves showed that pLV-S particles were efficiently neutralized by a range of concentrations of unfractionated heparin (UFH), enoxaparin, 6-O-desulfated UFH and 6-O-desulfated enoxaparin with an IC50 of 5.99 {micro}g/L, 1.08 mg/L, 1.77 {micro}g/L, and 5.86 mg/L respectively. The low serum bioavailability of intranasally administered UFH, along with data suggesting that the nasal epithelium is a portal for initial infection and transmission, suggest that intranasal administration of UFH may be an effective and safe prophylactic treatment.

Role of novel deep-learning-based CT used in management and discharge of COVID-19 patients at a “square cabin” hospital in China (preprint)

Background: The chest computed tomography (CT) had been used to define the diagnostic and discharge criteria for COVID-19. However, it is difficult to determine the suitability for discharge of a patient with COVID-19 based on CT features in a clinical setting. Deep learning (DL) technology has demonstrated great success in the medical imaging.Purpose: This study applied the novel deep learning (DL) on chest computed tomography (CT) of COVID-19 patients with consecutive negative respiratory pathogen nucleic acid test results at a “square cabin” hospital in Wuhan, China, with the intent to standardize criteria for discharge.Methods: The study included 270 patients (102men, 168 women; mean age, 51.9 ± 15.6[18–65] years) who had two consecutive negative respiratory pathogen tests (sampling interval: ≥1 day) and underwent low-dose CT 1 day after the first negative test, with strict adherence to epidemic prevention standards. The chest CT of COVID-19 patients with negative nucleic acid tests were evalued by DL, and the standard for discharge was a total volume ratio of lesions to lung of less than 50% determined by DL.Results: The average intersection over union is 0.7894. Fifty-seven (21.1%) and 213 (78.9%) patients exhibited normal lung findings and pneumonia, respectively. 54.0% (115/213) involved mild interstitial fibrosis. 18.8% (40/213) had total volume ratio of lesions to lung of more than and equal to 50% according to our severity scale and were monitored continuously in hospital, and three cases of which had a positive follow-up nucleic acid test during hospital observation. None of the 230 discharged cases later tested positive or exhibited pneumonia progression. Conclusions: The novel DL enables the accurate management of COVID-19 patients and can help avoid cluster transmission or exacerbation due to patients with false negitive acid test. 

Computational Evaluation of the COVID-19 3c-like Protease Inhibition Mechanism, and Drug Repurposing Screening (preprint)

The rapid spread of the COVID-19 outbreak is now a global threat with over a million diagnosed cases and more than 70 thousand deaths. Specific treatments and effective drugs regarding such disease are in urgent need. To contribute to the drug discovery against COVID-19, we performed computational study to understand the inhibition mechanism of the COVID-19 3c-like protease, and search for possible drug candidates from approved or experimental drugs through drug repurposing screening against the DrugBank database. Two novel computational methods were applied in this study. We applied the “Consecutive Histogram Monte Carlo” (CHMC) sampling method for understanding the inhibition mechanism from studying the 2-D binding free energy landscape. We also applied the “Movable Type” (MT) free energy method for the lead compound screening by evaluating the binding free energies of the COVID-19 3c-like protease – inhibitor complexes. Lead compounds from the DrugBank database were first filtered using ligand similarity comparison to 19 published SARS 3c-like protease inhibitors. 70 selected compounds were then evaluated for protein-ligand binding affinities using the MT free energy method. 4 drug candidates with strong binding affinities and reasonable protein-ligand binding modes were selected from this study, i.e. Enalkiren (DB03395), Rupintrivir (DB05102), Saralasin (DB06763) and TRV-120027 (DB12199).

FEP-based screening prompts drug repositioning against COVID-19 (preprint)

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and, thus, repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a new virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (Mpro). The accurate FEP-ABFE predictions were based on the use of a new restraint energy distribution (RED) function designed to accelerate the FEP-ABFE calculations and make the practical FEP-ABFE-based virtual screening of the existing drug library possible for the first time. As a result, out of twenty-five drugs predicted, fifteen were confirmed as potent inhibitors of SARS-CoV-2 Mpro. The most potent one is dipyridamole (Ki=0.04 M) which has showed promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (Ki=0.36 M) and chloroquine (Ki=0.56 M) were also found to potently inhibit SARS-CoV-2 Mpro for the first time. We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts. Significance StatementDrug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. It has been demonstrated that a new virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions can reach an unprecedently high hit rate, leading to successful identification of 16 potent inhibitors of SARS-CoV-2 main protease (Mpro) from computationally selected 25 drugs under a threshold of Ki = 4 M. The outcomes of this study are valuable for not only drug repurposing to treat COVID-19, but also demonstrating the promising potential of the FEP-ABFE prediction-based virtual screening approach.

Role of the Eye in Transmitting Human Coronavirus: What We Know and What We Do Not Know (preprint)

The outbreak of recently identified 2019 novel coronavirus (2019-nCOV) infection has become a world-wide health threat. Currently, more information is needed for further understanding the transmission, clinical characteristics, and infection control procedures of 2019-nCOV. Recently, the role of the eye in transmitting 2019-nCOV has been intensively discussed. Previous investigations about other high infectious human COVs, that is, severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV), may provide helpful information. In this review, we describe the genomics and morphology of human CoVs, the epidemiology, systemic and ophthalmic manifestations, mechanisms of human CoVs infection, and infection control procedures. The role of the eye in the transmission of SARS-CoV and 2019-nCOV is discussed. Although the conjunctiva is directly exposed to extraocular pathogens, and the mucosa of ocular surface and upper respiratory tract is connected by nasolacrimal duct and share same entry receptors for some respiratory viruses. The eye is rarely involved in human CoVs infection, conjunctivitis is quite rare in patients with SARS-CoV and 2019-nCoV infection, and COV RNA positive rate by RT-PCR test in tears and conjunctival secretions from patients with SARS-CoV and 2019-nCoV infection is also very low, which imply that the eye is neither a preferred organ of human COVs infection, nor is a preferred gateway of entry for human COVs to infect respiratory tract. However, pathogens exposed to the ocular surface might be transported to nasal and nasopharyngeal mucosa by constant tear rinsing through lacrimal duct, and then cause respiratory tract infection. Considering close doctor-patient contact is quite common in ophthalmic practice which are apt to transmit human COVs by droplets and fomites, hand hygiene and personal protection are still highly recommended for health care workers to avoid hospital-related viral transmission during ophthalmic practice.