Acupuncture for dry eye disease after recovery from COVID-19: A protocol for systematic review and meta-analysis.

BACKGROUND: Dry eye disease (DED) is a condition occurring worldwide. Studies have found that coronavirus disease 2019 (COVID-19) patients may have persistent dry eye symptoms for weeks and months after recovery, and the prevalence of dry eye is higher in COVID-19 patients than in people without COVID-19 infection. As one of the common ophthalmic diseases, the clinical application of acupuncture in the treatment of DED is not widely used nowadays. METHODS: According to the retrieval strategies, randomized controlled trials (RCT) on the acupuncture for DED after recovery from COVID-19 were obtained from Embase, The Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure database, Chinese Biomedical Database, Chinese Science and Technology Periodical database, The WanFang database. Studies were screened based on inclusion and exclusion criteria, and the Cochrane risk bias assessment tool was used to evaluate the quality of the studies. The meta-analysis was performed using Review Manager (RevMan 5.3) and STATA 14.2 software. Ultimately, the evidentiary grade for the results will be evaluated. RESULTS: The study will provide a high-quality and convincing assessment of the efficacy and safety of acupuncture for DED after recovery from COVID-19 and will be published in peer-reviewed journals. CONCLUSION: Our findings will provide references for future clinical decision and guidance development.

Exploring the mechanism of action of Xuanfei Baidu granule (XFBD) in the treatment of COVID-19 based on molecular docking and molecular dynamics.

Purpose: The Corona Virus Disease 2019 (COVID-19) pandemic has become a challenge of world. The latest research has proved that Xuanfei Baidu granule (XFBD) significantly improved patient's clinical symptoms, the compound drug improves immunity by increasing the number of white blood cells and lymphocytes, and exerts anti-inflammatory effects. However, the analysis of the effective monomer components of XFBD and its mechanism of action in the treatment of COVID-19 is currently lacking. Therefore, this study used computer simulation to study the effective monomer components of XFBD and its therapeutic mechanism. Methods: We screened out the key active ingredients in XFBD through TCMSP database. Besides GeneCards database was used to search disease gene targets and screen intersection gene targets. The intersection gene targets were analyzed by GO and KEGG. The disease-core gene target-drug network was analyzed and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the number of hydrogen bonds, the binding free energy, the stability of protein target at the residue level, the solvent accessible surface area, and the radius of gyration. Results: XFBD had 1308 gene targets, COVID-19 had 4600 gene targets, the intersection gene targets were 548. GO and KEGG analysis showed that XFBD played a vital role by the signaling pathways of immune response and inflammation. Molecular docking showed that I-SPD, Pachypodol and Vestitol in XFBD played a role in treating COVID-19 by acting on NLRP3, CSF2, and relieve the clinical symptoms of SARS-CoV-2 infection. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets, CSF2/I-SPD combination has the strongest binding energy. Conclusion: For the first time, it was found that the important active chemical components in XFBD, such as I-SPD, Pachypodol and Vestitol, reduce inflammatory response and apoptosis by inhibiting the activation of NLRP3, and reduce the production of inflammatory factors and chemotaxis of inflammatory cells by inhibiting the activation of CSF2. Therefore, XFBD can effectively alleviate the clinical symptoms of COVID-19 through NLRP3 and CSF2.

Research on the mechanism of berberine in the treatment of COVID-19 pneumonia pulmonary fibrosis using network pharmacology and molecular docking.

Purpose Pulmonary fibrosis caused by COVID-19 pneumonia is a serious complication of COVID-19 infection, there is a lack of effective treatment methods clinically. This article explored the mechanism of action of berberine in the treatment of COVID-19 (Corona Virus Disease 2019, COVID-19) pneumonia pulmonary fibrosis with the help of the network pharmacology and molecular docking. Methods We predicted the role of berberine protein targets with the Pharmmapper database and the 3D structure of berberine in the Pubchem database. And GeneCards database was used in order to search disease target genes and screen common target genes. Then we used STRING web to construct PPI interaction network of common target protein. The common target genes were analyzed by GO and KEGG by DAVID database. The disease-core target gene-drug network was established and molecular docking was used for prediction. We also analyzed the binding free energy and simulates molecular dynamics of complexes. Results Berberine had 250 gene targets, COVID-19 pneumonia pulmonary fibrosis had 191 gene targets, the intersection of which was 23 in common gene targets. Molecular docking showed that berberine was associated with CCl2, IL-6, STAT3 and TNF-α. GO and KEGG analysis reveals that berberine mainly plays a vital role by the signaling pathways of influenza, inflammation and immune response. Conclusion Berberine acts on TNF-α, STAT3, IL-6, CCL2 and other targets to inhibit inflammation and the activation of fibrocytes to achieve the purpose of treating COVID-19 pneumonia pulmonary fibrosis.

Earlier diagnosis improves COVID-19 prognosis: a nationwide retrospective cohort analysis.

BACKGROUND: Risk of adverse outcomes in COVID-19 patients by stratifying by the time from symptom onset to confirmed diagnosis status is still uncertain. METHODS: We included 1,590 hospitalized COVID-19 patients confirmed by real-time RT-PCR assay or high-throughput sequencing of pharyngeal and nasal swab specimens from 575 hospitals across China between 11 December 2019 and 31 January 2020. Times from symptom onset to confirmed diagnosis, from symptom onset to first medical visit and from first medical visit to confirmed diagnosis were described and turned into binary variables by the maximally selected rank statistics method. Then, survival analysis, including a log-rank test, Cox regression, and conditional inference tree (CTREE) was conducted, regarding whether patients progressed to a severe disease level during the observational period (assessed as severe pneumonia according to the Chinese Expert Consensus on Clinical Practice for Emergency Severe Pneumonia, admission to an intensive care unit, administration of invasive ventilation, or death) as the prognosis outcome, the dependent variable. Independent factors included whether the time from symptom onset to confirmed diagnosis was longer than 5 days (the exposure) and other demographic and clinical factors as multivariate adjustments. The clinical characteristics of the patients with different times from symptom onset to confirmed diagnosis were also compared. RESULTS: The medians of the times from symptom onset to confirmed diagnosis, from symptom onset to first medical visit, and from first medical visit to confirmed diagnosis were 6, 3, and 2 days. After adjusting for age, sex, smoking status, and comorbidity status, age [hazard ratio (HR): 1.03; 95% CI: 1.01-1.04], comorbidity (HR: 1.84; 95% CI: 1.23-2.73), and a duration from symptom onset to confirmed diagnosis of >5 days (HR: 1.69; 95% CI: 1.10-2.60) were independent predictors of COVID-19 prognosis, which echoed the CTREE models, with significant nodes such as time from symptom onset to confirmed diagnosis, age, and comorbidities. Males, older patients with symptoms such as dry cough/productive cough/shortness of breath, and prior COPD were observed more often in the patients who procrastinated before initiating the first medical consultation. CONCLUSIONS: A longer time from symptom onset to confirmed diagnosis yielded a worse COVID-19 prognosis.

The Effect of Prior Angiotensin-Converting Enzyme Inhibitor and Angiotensin Receptor Blocker Treatment on Coronavirus Disease 2019 (COVID-19) Susceptibility and Outcome: A Systematic Review and Meta-analysis.

There have been arguments on whether angiotensin-converting enzyme inhibitor (ACEI) and angiotensin receptor blocker (ARB) treatment alters the risk of coronavirus disease 2019 (COVID-19) susceptibility and disease severity. We identified a total of 102 eligible studies for systematic review, in which 49 studies adjusting for confounders were included in the meta-analysis. We found no association between prior ACEI/ARB use and risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the general population (adjusted odds ratio [aOR], 1.00; 95% confidence interval [CI], .94-1.05). The risk of mortality (aOR, .87; 95% CI, .66-1.04) and severe outcomes (aOR, .95; 95% CI, .73-1.24) were also unchanged among COVID-19 patients taking ACEIs/ARBs. These findings remained consistent in subgroup analyses stratified by populations, drug exposures, and other secondary outcomes. This systematic review provides evidence-based support to current medical guidelines and position statements that ACEIs/ARBs should not be discontinued. Additionally, there has been no evidence for initiating ACEI/ARB regimen as prevention or treatment of COVID-19.

Laboratory indicators in COVID-19 and other pneumonias: Analysis for differential diagnosis and comparison of dynamic changes during 400-day follow-up.

BACKGROUND: COVID-19 is spreading rapidly all over the world, the patients' symptoms can be easily confused with other pneumonia types. Therefore, it is valuable to seek a laboratory differential diagnostic protocol of COVID-19 and other pneumonia types on admission, and to compare the dynamic changes in laboratory indicators during follow-up. METHODS: A total of 143 COVID-19, 143 bacterial pneumonia and 145 conventional viral pneumonia patients were included. The model group consisted of 140 COVID-19, 80 bacterial pneumonia and 60 conventional viral pneumonia patients, who were age and sex matched. We established a differential diagnostic model based on the laboratory results of the model group on admission via a nomogram, which was validated in an external validation group. We also compared the 400-day dynamic changes of the laboratory indicators among groups. RESULTS: LASSO regression and multivariate logistic regression showed that eosinophils (Eos), total protein (TP), prealbumin (PA), potassium (K), high-density lipoprotein cholesterol (HDLC), and low-density lipoprotein cholesterol (LDLC) could differentiate COVID-19 from other pneumonia types. The C-index of the nomogram model was 0.922. Applying the nomogram to the external validation group showed an area under the curve (AUC) of 0.902. The 400-day change trends of the laboratory indexes varied among subgroups divided by sex, age, oxygenation index (OI), and pathogen. CONCLUSION: The laboratory model was highly accurate at providing a new method to identify COVID-19 in pneumonia patients. The 400-day dynamic changes in laboratory indicators revealed that the recovery time of COVID-19 patients was not longer than that of other pneumonia types.

Development of a chiral HPLC method for the separation and quantification of hydroxychloroquine enantiomers.

Hydroxychloroquine (2-[[4-[(7-Chloroquinolin-4-yl) amino]pentyl](ethyl) amino]-ethanol, HCQ), an effective anti-malarial drug, has been tested in the clinics for potential treatment of severe coronavirus disease 2019 (COVID-19). Despite the controversy around the clinical benefits of HCQ, the existence of a chiral center in the molecule to possess two optical isomers suggests that there might be an enantiomeric difference on the treatment of COVID-19. Due to their poor resolution and the inability of quantification by previously reported methods for the analysis of HCQ enantiomers, it is necessary to develop an analytical method to achieve baseline separation for quantitative and accurate determination of the enantiomeric purity in order to compare the efficacy and toxicity profiles of different enantiomers. In this study, we developed and validated an accurate and reproducible normal phase chiral high-performance liquid chromatography (HPLC) method for the analysis of two enantiomers of HCQ, and the method was further evaluated with biological samples. With this newly developed method, the relative standard deviations of all analytes were lower than 5%, and the limits of quantification were 0.27 µg/ml, 0.34 µg/ml and 0.20 µg/ml for racemate, R- and S-enantiomer, respectively. The present method provides an essential analytical tool for preclinical and clinical evaluation of HCQ enantiomers for potential treatment of COVID-19.

2019 novel coronavirus outbreak: a quiz or final exam?

The 2019 novel coronavirus (2019-nCoV) is an emerging pathogen and is threatening the global health. Strikingly, more than 28 000 cases and 550 deaths have been reported within two months from disease emergence. Armed with experience from previous epidemics in the last two decades, clinicians, scientists, officials, and citizens in China are all contributing to the prevention of further 2019-nCoV transmission. Efficient preliminary work has enabled us to understand the basic characteristics of 2019-nCoV, but there are still many unanswered questions. It is too early now to judge our performance in this outbreak. Continuous and strengthened efforts should be made not only during the epidemic, but also afterwards in order to prepare for any incoming challenges.