Evaluation of autophagy induction and inhibition in the Huh7.5 cell line through flow cytometry

Background: Autophagy is a physiologic process in which double membrane vesicles engulf damaged proteins and organelles for delivering them to lysosomein order to degrade and recycle them via lysosomal digestion. Beclin1 is one of the basic proteins involved in the initial step of autophagosome formation. In the current study, the effect of exogenous Beclin1 to induce autophagy and the effect of 3MA to inhibit of autophagy was assessed in Huh7.5 cells as an in vitro models of hepatocellular carcinoma. Material and methods: The Recombinant pcDNA-Beclin1was transfected into Huh7.5 cells. Also, the cell treated with 3MA. Next, the autophagy induction and inhibition was conducted via LC3 staining as a main autophagy marker using flow cytometry. Results: The result of this study suggest that the over expression of exogenous Beclin1 in Huh7.5 cells elevated the autophagosome formation as shown by intracellular autophagosomal marker LC3-II staining for about 32.32 % and   3MA decreased  it up to2% in compared with control cells in which the stained LC3-II was12.08. Conclusion: Recombinant beclin1 may be used as a potential autophagy inducer agent and 3-methyl-Adenin inhibits autophagy formation in Huh7.5 cell. The staining autophagy formation marker LC3-II with specific antibody is a reliable method to measure autophagy activation via flow cytometry

Converting high-dimensional complex networks to lower-dimensional ones preserving synchronization features

Studying the stability of synchronization of coupled oscillators is one of the prominent topics in network science. However, in most cases, the computational cost of complex network analysis is challenging because they consist of a large number of nodes. This study includes overcoming this obstacle by presenting a method for reducing the dimension of a large-scale network, while keeping the complete region of stable synchronization unchanged. To this aim, the first and last non-zero eigenvalues of the Laplacian matrix of a large network are preserved using the eigen-decomposition method and Gram-Schmidt orthogonalization. The method is only applicable to undirected networks and the result is a weighted undirected network with smaller size. The reduction method is studied in a large-scale a small-world network of Sprott-B oscillators. The results show that the trend of the synchronization error is well maintained after node reduction for different coupling schemes

Alkaloids as Potential Phytochemicals against SARS-CoV-2: Approaches to the Associated Pivotal Mechanisms

Since its inception, the coronavirus disease 2019 (COVID-19) pandemic has infected millions of people around the world. Therefore, it is necessary to find effective treatments against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), as it is the viral source of COVID-19. Alkaloids are one of the most widespread plant-derived natural compounds with prominent antiviral effects. Accordingly, these phytochemicals have been promising candidates towards discovering effective treatments for COVID-19. Alkaloids have shown potential anti-SARS-CoV activities via inhibiting pathogenesis-associated targets of the Coronaviridae family that are required for the virus life cycle. In the current study, the chemistry, plant sources, and antiviral effects of alkaloids, as well as their anti-SARS-CoV-2 effect with related mechanisms, are reviewed towards discovering an effective treatment against COVID-19