Nanoparticles of ZnO/Berberine complex contract COVID-19 and respiratory co-bacterial infection in addition to elimination of hydroxychloroquine toxicity.

Purpose: A novel coronavirus (COVID-19) that has not been previously identified in humans and has no specific treatment has recently spread. Treatment trials using antiviral and immune-modulating drugs such as hydroxychloroquine (HCQ) were used to control this viral outbreak however several side effects have emerged. Berberine (BER) is an alkaloid that has been reported to reveal some pharmacological properties including antioxidant and antimicrobial activities. Additionally, Zinc oxide nanoparticles (ZnO-NPs) possess potent antioxidant and anti-inflammatory properties. Therefore, this study was undertaken to estimate the efficiency of both BER and synthetic ZnO/BER complex as an anti-COVID-19 therapy. Methods: First, the ZnO/BER complex was prepared by the facile mixing method. Then in vitro studies on the two compounds were conducted including VeroE6 toxicity, anti-COVID-19 activity, determination of inhibitory activity towards papain-like proteinase (PL pro) and spike protein- and receptor- binding domain (RBD) as well as assessment of drug toxicity on RBCs. Results: The results showed that ZnO/BER complex acts as an anti-COVID-19 by inhibiting spike protein binding with angiotensin-converting enzyme II (ACE II), PL pro activity, spike protein and E protein levels, and expression of both E-gene and RNA dependent RNA polymerase (RdRp) at a concentration lower than that of BER or ZnO-NPs alone. Furthermore, ZnO/BER complex had antioxidant and antimicrobial properties where it prevents the auto oxidation of 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and the culture of lower respiratory system bacteria that affected Covid 19 patients. The ZnO/BER complex prevented as well the HCQ cytotoxic effect on both RBC and WBC (in vitro) and hepatotoxicity, nephrotoxicity and anemia that occurred after HCQ long administration in vivo. Conclusion: The ZnO/BER complex can be accounted as promising anti-COVID 19 candidate because it inhibited the virus entry, replication, and assembly. Furthermore, it could be used to treat a second bacterial infection that took place in hospitalized COVID 19 patients. Moreover, ZnO/BER complex was found to eliminate the toxicity of long-term administration of HCQ in vivo.

Accurate Classification of COVID-19 Based on Incomplete Heterogeneous Data using a KNN Variant Algorithm.

Great efforts are now underway to control the coronavirus 2019 disease (COVID-19). Millions of people are medically examined, and their data keep piling up awaiting classification. The data are typically both incomplete and heterogeneous which hampers classical classification algorithms. Some researchers have recently modified the popular KNN algorithm as a solution, where they handle incompleteness by imputation and heterogeneity by converting categorical data into numbers. In this article, we introduce a novel KNN variant (KNNV) algorithm that provides better results as demonstrated by thorough experimental work. We employ rough set theoretic techniques to handle both incompleteness and heterogeneity, as well as to find an ideal value for K. The KNNV algorithm takes an incomplete, heterogeneous dataset, containing medical records of people, and identifies those cases with COVID-19. We use in the process two popular distance metrics, Euclidean and Mahalanobis, in an effort to widen the operational scope. The KNNV algorithm is implemented and tested on a real dataset from the Italian Society of Medical and Interventional Radiology. The experimental results show that it can efficiently and accurately classify COVID-19 cases. It is also compared to three KNN derivatives. The comparison results show that it greatly outperforms all its competitors in terms of four metrics: precision, recall, accuracy, and F-Score. The algorithm given in this article can be easily applied to classify other diseases. Moreover, its methodology can be further extended to do general classification tasks outside the medical field.

Potential therapeutic and pharmacological strategies for SARS-CoV2.

BACKGROUND: At the end of 2019, the new Coronavirus disease 2019 (COVID-19) strain causing severe acute respiratory syndrome swept the world. From November 2019 till February 2021, this virus infected nearly 104 million, with more than two million deaths and about 25 million active cases. This has prompted scientists to discover effective drugs to combat this pandemic. AREA COVERED: Drug repurposing is the magic bullet for treating severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). Therefore, several drugs have been investigated in silico, in vitro, as well as through human trials such as anti-SARS-CoV2 agents, or to prevent the complications resulting from the virus. In this review, the mechanisms of action of different therapeutic strategies are summarized. According to the WHO, different classes of drugs can be used, including anti-malarial, antiviral, anti-inflammatory, and anti-coagulant drugs, as well as angiotensin-converting enzyme inhibitors, antibiotics, vitamins, zinc, neutralizing antibodies, and convalescent plasma therapy. Recently, there are some vaccines which are approved against SARS-CoV2. EXPERT OPINION: A complete understanding of the structure and function of all viral proteins that play a fundamental role in viral infection, which contribute to the therapeutic intervention and the development of vaccine in order to reduce the mortality rate. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40005-021-00520-4.