Electrostatic Interactions Are the Primary Determinant of the Binding Affinity of SARS-CoV-2 Spike RBD to ACE2: A Computational Case Study of Omicron Variants.

To explore the mechanistic origin that determines the binding affinity of SARS-CoV-2 spike receptor binding domain (RBD) to human angiotensin converting enzyme 2 (ACE2), we constructed the homology models of RBD-ACE2 complexes of four Omicron subvariants (BA.1, BA.2, BA.3 and BA.4/5), and compared them with wild type complex (RBDWT-ACE2) in terms of various structural dynamic properties by molecular dynamics (MD) simulations and binding free energy (BFE) calculations. The results of MD simulations suggest that the RBDs of all the Omicron subvariants (RBDOMIs) feature increased global structural fluctuations when compared with RBDWT. Detailed comparison of BFE components reveals that the enhanced electrostatic attractive interactions are the main determinant of the higher ACE2-binding affinity of RBDOMIs than RBDWT, while the weakened electrostatic attractive interactions determine RBD of BA.4/5 subvariant (RBDBA.4/5) lowest ACE2-binding affinity among all Omicron subvariants. The per-residue BFE decompositions and the hydrogen bond (HB) networks analyses indicate that the enhanced electrostatic attractive interactions are mainly through gain/loss of the positively/negatively charged residues, and the formation or destruction of the interfacial HBs and salt bridges can also largely affect the ACE2-binding affinity of RBD. It is worth pointing out that since Q493R plays the most important positive contribution in enhancing binding affinity, the absence of this mutation in RBDBA.4/5 results in a significantly weaker binding affinity to ACE2 than other Omicron subvariants. Our results provide insight into the role of electrostatic interactions in determining of the binding affinity of SARS-CoV-2 RBD to human ACE2.

Identification of novel drug targets for the risk and prognosis of COVID-19.

Background: Since the epidemic continues, there is a pressing need to improve our understanding of coronavirus disease 2019 (COVID-19). Mendelian randomization (MR) studies provide us with a method to explore the causality between circulating proteins and COVID-19 susceptibility and severity. We aim to find new perspectives on the pathological mechanism of the disease and possible drug targets for treatment based on this study. Methods: We conducted a phenome-wide MR study to prioritize circulating proteins causally associated with COVID-19 susceptibility, which was defined as "patients tested positive for COVID-19 vs. population controls", and severity, which was defined as "patients hospitalized with COVID-19 vs. population controls". And we repeated the analysis for different definition of COVID-19 susceptibility, severity and control groups. Results: Association of three circulating proteins with COVID-19 susceptibility and severity were demonstrated via our study. C-C motif chemokine 4 (OR =1.887, 95% CI: 1.608-2.165, P=8.04×10-6) and 2'-5'-oligoadenylate synthase 1 (OR =0.511, 95% CI: 0.266-0.757, P=8.51×10-8) were found respectively positively and negatively correlated with increased COVID-19 severity. Tissue factor, contrary to previous studies, was found associated with decreased COVID-19 susceptibility (OR =0.667, 95% CI: 0.484-0.850, P=1.47×10-5) and decreased COVID-19 severity (OR =0.459, 95% CI: 0.132-0.786, P=3.01×10-6). Conclusions: Genetic evidence supports C-C motif chemokine 4 as a risk factor for COVID-19 severity, and 2'-5'-oligoadenylate synthase 1 as a protective factor for COVID-19 severity. The causal association between tissue factor and COVID-19 is contrary to the previous studies, needing further analyses. Further research is warranted to assess the viability of C-C motif chemokine 4 and 2'-5'-oligoadenylate synthase 1 as well as their downstream pathways as drug targets for anti-inflammatory and anti-virus treatment in severe cases.

Evaluation of CRISPR-Based Assays for Rapid Detection of SARS-CoV-2: A Systematic Review and Meta-Analysis.

PURPOSE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen of coronavirus disease 2019. Diagnostic methods based on the clustered regularly interspaced short palindromic repeats (CRISPR) have been developed to detect SARS-CoV-2 rapidly. Therefore, a systematic review and meta-analysis were performed to assess the diagnostic accuracy of CRISPR for detecting SARS-CoV-2 infection. MATERIALS AND METHODS: Studies published before August 2021 were retrieved from four databases, using the keywords "SARS-CoV-2" and "CRISPR." Data were collected from these publications, and the sensitivity, specificity, negative likelihood ratio (NLR), positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic curve was plotted for analysis with MetaDiSc 1.4. The Stata 15.0 software was used to draw Deeks' funnel plots to evaluate publication bias. RESULTS: We performed a pooled analysis of 38 independent studies shown in 30 publications. The reference standard was reverse transcription-quantitative PCR. The results indicated that the sensitivity of CRISPR-based methods for diagnosis was 0.94 (95% CI 0.93-0.95), the specificity was 0.98 (95% CI 0.97-0.99), the PLR was 34.03 (95% CI 20.81-55.66), the NLR was 0.08 (95% CI 0.06-0.10), and the DOR was 575.74 (95% CI 382.36-866.95). The area under the curve was 0.9894. CONCLUSION: Studies indicate that a diagnostic method based on CRISPR has high sensitivity and specificity. Therefore, this would be a potential diagnostic tool to improve the accuracy of SARS-CoV-2 detection.

[Pollution Characteristics and Risk Assessment of DBPs in Typical Drinking Water Sources in Wuhan Under the COVID-19 Pandemic].

In order to reveal the pollution characteristics and risk levels of DBPs in typical drinking water sources in Wuhan under the COVID-19 pandemic, 26 sampling sites were selected in typical drinking water sources in Wuhan. N,N-diethyl-1,4-phenylenediamine spectrophotometry and gas chromatograph-micro-cell electron capture detector (GC-µECD) methods were used to detect residual chlorine disinfectants and DBPs in water, respectively, and their health and ecology risks were assessed. The results showed that free chlorine or total residual chlorine were detected in 16 of the 26 water samples, and the maximum concentration was 0.04 mg·L-1, which exceeded the limit of the surface water standard in China. The concentration of residual chlorine was higher in sampling sites near the outfall of a municipal sewage plant. There were 34 types of DBPs measured in 10 sampling sites, and 24 types of substances were detected with the detection rate of 10.00%-100.00%. The ρ (total DBPs) was in the range of 0.11-104.73 µg·L-1, with an average value of 7.26 µg·L-1. The concentration of chloroform was the highest among all the DBPs, ranging from 9.98 µg·L-1 to 11.15 µg·L-1, with an average value of 10.47 µg·L-1. The concentration of 2-bromo-2-iodoacetamide was the lowest, ranging from ND-0.11 µg·L-1, with an average value of 0.01 µg·L-1. The overall detection level of the DBPs area was low in this study area, and the result of the health risk assessment showed that the DBPs had no carcinogenic or non-carcinogenic health risks to human body. However, the results of the ecological risk assessment showed that chloroform presented a high ecological risk to aquatic organisms.

Combined clinical and imaging features better predict the critical outcomes of patients with SARS-COV-2.

ABSTRACT: The purpose of this study was to investigate the predictive value of combined clinical and imaging features, compared with the clinical or radiological risk factors only. Moreover, the expected results aimed to improve the identification of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) patients who may have critical outcomes.This retrospective study included laboratory-confirmed SARS-COV-2 cases between January 18, 2020, and February 16, 2020. The patients were divided into 2 groups with noncritical illness and critical illness regarding severity status within the hospitalization. Univariable and multivariable logistic regression models were used to explore the risk factors associated with clinical and radiological outcomes in patients with SARS-COV-2. The ROC curves were performed to compare the prediction performance of different factors.A total of 180 adult patients in this study included 20 critical patients and 160 noncritical patients. In univariate logistic regression analysis, 15 risk factors were significantly associated with critical outcomes. Of importance, C-reactive protein (1.051, 95% confidence interval 1.024-1.078), D-dimer (1.911, 95% CI, 1.050-3.478), and CT score (1.29, 95% CI, 1.053-1.529) on admission were independent risk factors in multivariate analysis. The combined model achieved a better performance in disease severity prediction (P = .05).CRP, D-dimer, and CT score on admission were independent risk factors for critical illness in adults with SARS-COV-2. The combined clinical and radiological model achieved better predictive performance than clinical or radiological factors alone.

Pulmonary artery trunk enlargement on admission as a predictor of mortality in in-hospital patients with COVID-19.

PURPOSE: To describe the prognostic value of pulmonary artery (PA) trunk enlargement on the admission of in-hospital patients with severe COVID-19 infection by unenhanced CT image. MATERIALS AND METHODS: In-hospital patients confirmed COVID-19 from January 18, 2020, to March 7, 2020, were retrospectively enrolled. PA trunk diameters on admission and death events were collected to calculate the optimum cutoff using a receiver operating characteristic curve. According to the cutoff, the subjects on admission were divided into two groups. Then the in-hospital various parameters were compared between the two groups to assess the predictive value of PA trunk diameter. RESULTS: In the 180 enrolled in-hospital patients (46.99 ± 14.95 years; 93 (51.7%) female, 14 patients (7.8%) died during their hospitalization. The optimum cutoff PA trunk diameter to predict in-hospital mortality was > 29 mm with a sensitivity of 92.59% and a specificity of 91.11%. Kaplan-Meier survival curves for PA trunk diameter on admission showed that a PA trunk diameter > 29 mm was a significant predictor of subsequent death (log-rank < 0.001, median survival time of PA > 29 mm was 28 days). CONCLUSION: PA trunk enlargement can be a useful predictive factor for distinguishing between mild and severe COVID-19 disease progression.

A Large Scale of Nurses Participated in Beating down COVID-19 in China: The Physical and Psychological Distress.

The outbreak of coronavirus disease 2019 (COVID-19) posed an unprecedented threat to health care providers (HCPs) in Wuhan, China, especially for nurses who were frequently exposed to infected or suspected patients. Limited information was available about the working experience of nurses in fighting against the pandemic. To learn the physical and psychological responses of nurses during the pandemic and explore the potential determinants, we conducted a large-scale survey in Wuhan. This multicenter cross-sectional study enrolled 5521 nurses who worked in designated hospitals, mobile cabins, or shelters during the pandemic. A structured online questionnaire was distributed to assess the physical discomforts, emotional distress and cognitive reactions of nurses at work, and the log-binomial regression analysis was performed to explore potential determinants. A considerable proportion of nurses had symptoms of physical discomforts [3677 (66.6%)] and emotional distress [4721 (85.5%)]. Nurses who were directly involved in the care of patients (i.e., care for severe patients: RR, 2.35; 95% CI, 1.95-2.84), with irregular work schedules (RR, 2.36; 95% CI, 1.95-2.87), and working overtime (RR, 1.34; 95% CI, 1.08-1.65) were at a higher risk for physical discomforts. Nurses who were directly involved in the care of patients (i.e., care for severe patients: RR, 1.78; 95% CI, 1.40-2.29), with irregular work schedules (RR, 3.39; 95% CI, 2.43-4.73), and working overtime (RR, 1.51; 95% CI, 1.12-2.04) were at a higher risk for emotional distress. Therefore, formulating reasonable work schedules and improving workforce systems are necessary to alleviate the physical and emotional distress of nurses during the pandemic.