Cheng Cheng

Bio: Cheng Cheng is an academic researcher from Zhengzhou University. The author has contributed to research in topics: Incubation period & Angiotensin II receptor type 1. The author has an hindex of 2, co-authored 4 publications receiving 27 citations.

The incubation period of COVID-19: a global meta-analysis of 53 studies and a Chinese observation study of 11 545 patients.

Abstract: BACKGROUND: The incubation period is a crucial index of epidemiology in understanding the spread of the emerging Coronavirus disease 2019 (COVID-19). In this study, we aimed to describe the incubation period of COVID-19 globally and in the mainland of China. METHODS: The searched studies were published from December 1, 2019 to May 26, 2021 in CNKI, Wanfang, PubMed, and Embase databases. A random-effect model was used to pool the mean incubation period. Meta-regression was used to explore the sources of heterogeneity. Meanwhile, we collected 11 545 patients in the mainland of China outside Hubei from January 19, 2020 to September 21, 2020. The incubation period fitted with the Log-normal model by the coarseDataTools package. RESULTS: A total of 3235 articles were searched, 53 of which were included in the meta-analysis. The pooled mean incubation period of COVID-19 was 6.0 days (95% confidence interval [CI] 5.6-6.5) globally, 6.5 days (95% CI 6.1-6.9) in the mainland of China, and 4.6 days (95% CI 4.1-5.1) outside the mainland of China (P = 0.006). The incubation period varied with age (P = 0.005). Meanwhile, in 11 545 patients, the mean incubation period was 7.1 days (95% CI 7.0-7.2), which was similar to the finding in our meta-analysis. CONCLUSIONS: For COVID-19, the mean incubation period was 6.0 days globally but near 7.0 days in the mainland of China, which will help identify the time of infection and make disease control decisions. Furthermore, attention should also be paid to the region- or age-specific incubation period.

Role of Renin-Angiotensin System in Acute Lung Injury Caused by Viral Infection

Abstract: The renin-angiotensin system (RAS) is the most important regulatory system of electrolyte homeostasis and blood pressure and acts through angiotensin-converting enzyme (ACE)/angiotensin II (Ang II)/Ang II type 1 (AT1) receptor axis and angiotensin-converting enzyme 2 (ACE2)/angiotensin (1-7)/MAS receptor axis. RAS dysfunction is related to the occurrence and development of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) and causes a serious prognosis and even death. ALI/ARDS can be induced by various ways, one of which is viral infections, such as SARS-CoV, SARS-CoV-2, H5N1, H7N9, and EV71. This article reviews the specific mechanism on how RAS dysfunction affects ALI/ARDs caused by viral infections. SARS-CoV and SARS-CoV-2 enter the host cells by binding with ACE2. H5N1 and H7N9 avian influenza viruses reduce the ACE2 level in the body, and EV71 increases Ang II concentration. Treatment with angiotensin-converting enzyme inhibitor and angiotensin AT1 receptor blocker can alleviate ALI/ARDS symptoms. This review provides suggestions for the treatment of lung injury caused by viral infections.

Incubation Period of COVID-19 From 11545 Patients in Observation Study

Abstract: Background The incubation period is a key index of epidemiology in understanding of the spread of infectious diseases and the decision-making of the disease control. However, the incubation period of the emerging COVID-19 is still unclear. Methods Between January 19, 2020 and September 21, 2020, we collected information on 11545 patients in Mainland China outside Hubei. The 218 patients with precise data was validation population. The incubation period was fitted with lognormal model by the coarseDataTools package in R. Results In 11545 patients, the mean incubation period of COVID-19 was 7.1 days (95% Confidence interval [CI], 7.0–7.2). About 5.4% of patients had precise incubation period less than 3 days, 10.2% longer than 14 days, and 2.1% longer than 21 days. There was no statistically significant difference in incubation period between male and female (P = 0.603). It was similar in the 218 patients. The mean accurate incubation period was 6.8 days (6.2–7.4). Of which, 14.7% (32/218) of patients had incubation period less than 3 days, 12.4% (27/218) longer than 14 days, and 0.9% (2/218) longer than 21 days. Conclusions For COVID-19, the mean incubation period is 7.1 days and 10.2% of patients developed disease 14 days after infection, which challenges the current 14-day quarantine strategy.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Natural bioactive molecules: An alternative approach to the treatment and control of covid-19

Abstract: Several coronaviruses (CoVs) have been associated with serious health hazards in recent decades, resulting in the deaths of thousands around the globe. The recent coronavirus pandemic has emphasized the importance of discovering novel and effective antiviral medicines as quickly as possible to prevent more loss of human lives. Positive-sense RNA viruses with group spikes protruding from their surfaces and an abnormally large RNA genome enclose CoVs. CoVs have already been related to a range of respiratory infectious diseases possibly fatal to humans, such as MERS, SARS, and the current COVID-19 outbreak. As a result, effective prevention, treatment, and medications against human coronavirus (HCoV) is urgently needed. In recent years, many natural substances have been discovered with a variety of biological significance, including antiviral properties. Throughout this work, we reviewed a wide range of natural substances that interrupt the life cycles for MERS and SARS, as well as their potential application in the treatment of COVID-19.

Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential

Abstract: The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.