A novel infectious disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was detected in Wuhan, China, in December 2019. The disease (COVID-19) spread rapidly, reaching epidemic proportions in China, and has been found in 27 other countries. As of February 27, 2020, over 82,000 cases of COVID-19 were reported, with > 2800 deaths. No specific therapeutics are available, and current management includes travel restrictions, patient isolation, and supportive medical care. There are a number of pharmaceuticals already being tested [1, 2], but a better understanding of the underlying pathobiology is required. In this context, this article will briefly review the rationale for angiotensin-converting enzyme 2 (ACE2) receptor as a specific target.

Background: The coronavirus disease 2019 (COVID-19) outbreak originating in Wuhan, Hubei province, China, coincided with chunyun, the period of mass migration for the annual Spring Festival. To contain its spread, China adopted unprecedented nationwide interventions on January 23 2020. These policies included large-scale quarantine, strict controls on travel and extensive monitoring of suspected cases. However, it is unknown whether these policies have had an impact on the epidemic. We sought to show how these control measures impacted the containment of the epidemic. Methods: We integrated population migration data before and after January 23 and most updated COVID-19 epidemiological data into the Susceptible-Exposed-Infectious-Removed (SEIR) model to derive the epidemic curve. We also used an artificial intelligence (AI) approach, trained on the 2003 SARS data, to predict the epidemic. Results: We found that the epidemic of China should peak by late February, showing gradual decline by end of April. A five-day delay in implementation would have increased epidemic size in mainland China three-fold. Lifting the Hubei quarantine would lead to a second epidemic peak in Hubei province in mid-March and extend the epidemic to late April, a result corroborated by the machine learning prediction. Conclusions: Our dynamic SEIR model was effective in predicting the COVID-19 epidemic peaks and sizes. The implementation of control measures on January 23 2020 was indispensable in reducing the eventual COVID-19 epidemic size.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for coronavirus 2019 (COVID-19) pneumonia. Little is known about the kinetics, tissue distribution, cross-reactivity, and neutralization antibody response in patients with COVID-19. Two groups of patients with RT-PCR–confirmed COVID-19 were enrolled in this study: 12 severely ill patients in intensive care units who needed mechanical ventilation and 11 mildly ill patients in isolation wards. Serial clinical samples were collected for laboratory detection. Results showed that most of the severely ill patients had viral shedding in a variety of tissues for 20–40 days after onset of disease (8/12, 66.7%), while the majority of mildly ill patients had viral shedding restricted to the respiratory tract and had no detectable virus RNA 10 days after onset (9/11, 81.8%). Mildly ill patients showed significantly lower IgM response compared with that of the severe group. IgG responses were detected in most patients in both the severe and mild groups at 9 days after onset, and remained at a high level throughout the study. Antibodies cross-reactive to SARS-CoV and SARS-CoV-2 were detected in patients with COVID-19 but not in patients with MERS. High levels of neutralizing antibodies were induced after about 10 days after onset in both severely and mildly ill patients which were higher in the severe group. SARS-CoV-2 pseudotype neutralization test and focus reduction neutralization test with authentic virus showed consistent results. Sera from patients with COVID-19 inhibited SARS-CoV-2 entry. Sera from convalescent patients with SARS or Middle East respiratory syndrome (MERS) did not. Anti–SARS-CoV-2 S and N IgG levels exhibited a moderate correlation with neutralization titers in patients’ plasma. This study improves our understanding of immune response in humans after SARS-CoV-2 infection.

Regulated cell death (RCD) refers to the form of cell death that can be regulated by various biomacromolecules. Each cell death modalities have their distinct morphological changes and molecular mechanisms. However, intense evidences suggest that lipid peroxidation can be the common feature that initiates and propagates the cell death. Excessive lipid peroxidation alters the property of membrane and further damage the proteins and nucleic acids, which is implicated in various human pathologies. Here, we firstly review the classical chain process of lipid peroxidation, and further clarify the current understanding of the myriad roles and molecular mechanisms of lipid peroxidation in various RCD types. We also discuss how lipid peroxidation involves in diseases and how such intimate association between lipid peroxidation-driven cell death and diseases can be leveraged to develop rational therapeutic strategies.

SARS-CoV-2 caused a major outbreak of severe pneumonia (COVID-19) in humans. Viral RNA was detected in multiple organs in COVID-19 patients. However, infectious SARS-CoV-2 was only isolated from respiratory specimens. Here, infectious SARS-CoV-2 was successfully isolated from urine of a COVID-19 patient. The virus isolated could infect new susceptible cells and was recognized by its' own patient sera. Appropriate precautions should be taken to avoid transmission from urine.