The safety and efficacy of melatonin in the treatment of COVID-19: A systematic review and meta-analysis.

BACKGROUND: As an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the common signs of coronavirus disease 2019 (COVID-19) are respiratory symptoms, fever, cough, shortness of breath, and dyspnea, with multiple organ injuries in severe cases. Therefore, finding drugs to prevent and treat COVID-19 is urgently needed and expected by the public. Several studies suggested beneficial effects of melatonin for the relevant prevention and treatment. To explore the effect and safety of melatonin in the treatment and provide theoretical support and reference for seeking the most suitable drug for COVID-19, the meta-analysis was carried out accordingly. METHODS: It included randomized clinical trials of patients with COVID-19 treated with melatonin. Total effective rate was the primary outcome, while C-reactive protein (CRP), arterial oxygen saturation (SaO2), white blood cell count (WBC) were the secondary measures. Random-effect and fixed-effect models were used to evaluate the effect size of some indicators in this meta-analysis. RESULTS: Six eligible studies with 338 participants were included. One hundred seventy subjects were treated with melatonin adjuvant therapy and 168 subjects were assigned to the control group, with total excellent effective rate in subjects treated with melatonin [odds ratio = 3.05, 95 % confidence interval (CI) = 1.47, 6.31, P = .003]. Homogeneity was analyzed by fixed effect model (I2 = 0%). There was no significant difference in CRP between the melatonin group and the control group (weighted mean difference [WMD] = -0.36, 95% CI = -3.65, 2.92, P = .83). Significant difference was not existed in SaO2 between the melatonin treatment group and the control group (WMD = 1, 95% CI = -1.21, 3.22, P = .37). In terms of WBC, there was no significant difference between the 2 groups (WMD = -1.07, 95% CI = -2.44, 0.30, P = .13). CONCLUSIONS: The meta-analysis showed that melatonin had the beneficial effects for COVID-19 prevention and treatment as an adjunctive agent in combination with basic treatment for the treatment.

The Roles of Dipeptidyl Peptidase 4 (DPP4) and DPP4 Inhibitors in Different Lung Diseases: New Evidence.

CD26/Dipeptidyl peptidase 4 (DPP4) is a type II transmembrane glycoprotein that is widely expressed in various organs and cells. It can also exist in body fluids in a soluble form. DPP4 participates in various physiological and pathological processes by regulating energy metabolism, inflammation, and immune function. DPP4 inhibitors have been approved by the Food and Drug Administration (FDA) for the treatment of type 2 diabetes mellitus. More evidence has shown the role of DPP4 in the pathogenesis of lung diseases, since it is highly expressed in the lung parenchyma and the surface of the epithelium, vascular endothelium, and fibroblasts of human bronchi. It is a potential biomarker and therapeutic target for various lung diseases. During the coronavirus disease-19 (COVID-19) global pandemic, DPP4 was found to be an important marker that may play a significant role in disease progression. Some clinical trials on DPP4 inhibitors in COVID-19 are ongoing. DPP4 also affects other infectious respiratory diseases such as Middle East respiratory syndrome and non-infectious lung diseases such as pulmonary fibrosis, lung cancer, chronic obstructive pulmonary disease (COPD), and asthma. This review aims to summarize the roles of DPP4 and its inhibitors in infectious lung diseases and non-infectious diseases to provide new insights for clinical physicians.

Artificial Intelligence for COVID-19: A Systematic Review.

Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead to enormous losses. This study systematically reviews the application of Artificial Intelligence (AI) techniques in COVID-19, especially for diagnosis, estimation of epidemic trends, prognosis, and exploration of effective and safe drugs and vaccines; and discusses the potential limitations. Methods: We report this systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched PubMed, Embase and the Cochrane Library from inception to 19 September 2020 for published studies of AI applications in COVID-19. We used PROBAST (prediction model risk of bias assessment tool) to assess the quality of literature related to the diagnosis and prognosis of COVID-19. We registered the protocol (PROSPERO CRD42020211555). Results: We included 78 studies: 46 articles discussed AI-assisted diagnosis for COVID-19 with total accuracy of 70.00 to 99.92%, sensitivity of 73.00 to 100.00%, specificity of 25 to 100.00%, and area under the curve of 0.732 to 1.000. Fourteen articles evaluated prognosis based on clinical characteristics at hospital admission, such as clinical, laboratory and radiological characteristics, reaching accuracy of 74.4 to 95.20%, sensitivity of 72.8 to 98.00%, specificity of 55 to 96.87% and AUC of 0.66 to 0.997 in predicting critical COVID-19. Nine articles used AI models to predict the epidemic of the COVID-19, such as epidemic peak, infection rate, number of infected cases, transmission laws, and development trend. Eight articles used AI to explore potential effective drugs, primarily through drug repurposing and drug development. Finally, 1 article predicted vaccine targets that have the potential to develop COVID-19 vaccines. Conclusions: In this review, we have shown that AI achieved high performance in diagnosis, prognosis evaluation, epidemic prediction and drug discovery for COVID-19. AI has the potential to enhance significantly existing medical and healthcare system efficiency during the COVID-19 pandemic.

Histopathological features of multiorgan percutaneous tissue core biopsy in patients with COVID-19.

AIMS: The global outbreak of COVID-19 has resulted in an increased mortality. However, whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can affect multiple organs is still unclear. In this study, postmortem percutaneous biopsies of multiple organs from deceased patients were performed to understand the histopathological changes caused by COVID-19. METHODS: Biopsy specimens of pulmonary, cardiac, hepatic and lymphoid tissues were obtained from three patients, who died due to COVID-19 pneumonia. H&E stain, Masson trichrome stain, immunohistochemistry stain and in-situ hybridisation were used. RESULTS: Pulmonary damages caused by SARS-CoV-2 infection was diffuse alveolar damage (DAD). In the early phase, the histological findings were mainly those of exudative features of DAD. The later phase was characterised by organisation of DAD combined with bacterial pneumonia. No serious damage was found in the bronchiolar epithelium and submucosal glands. The hepatic tissue revealed features of ischaemic necrosis, but findings suggestive of mild lobular hepatitis were also observed. The lymphoid tissue revealed features of non-specific acute lymphadenitis. The cardiac tissue revealed changes of underlying disease. SARS-CoV-2 RNAs were not detected in hepatocytes, cholangiocytes and lymphocytes of lymph nodes. CONCLUSIONS: COVID-19 predominantly involves the pulmonary tissue, causes DAD and aggravates the cardiovascular disease. However, other extrapulmonary tissues did not reveal any virus-specific findings, but were affected by multiple factors. The findings in this report caution the pathologists that they should not mistakenly attribute all the histological features to CoV infection. Moreover, the clinicians should pay attention to the potentially injurious and correctable causes.