Phytochemical analysis of Berberis lyceum methanolic extract and its antiviral activity through the restoration of MAPK signaling pathway modulated by HCV NS5A

Objective:To evaluate the antiviral activity and phytochemicals of selected plant extracts and their effect on the mitogen-activated protein kinase(MAPK)signaling pathway modulated by hepatitis C virus(HCV)nonstructural protein 5 A(NS5A).Methods:A total of ten plant extracts were initially screened for their toxicities against Hep G2 cells.The non-toxic plants were tested for their inhibitory effect on the expression of HCV NS5A at both m RNA and protein levels using real-time PCR and Western blotting assays,respectively.The differential expression of the genes associated with MAPK pathway in the presence of NS5A gene and plant extract was measured through real-time PCR.Subsequently,the identification of secondary metabolites was carried out by phytochemical and HPLC analysis.Results:The phytochemical profiling of Berberis lyceum revealed the presence of alkaloids,phenols,saponins,tannins,flavonoids,carbohydrates,terpenoids,steroids,and glycosides.Similarly,quercetin,myricetin,gallic acid,caffeic acid,and ferulic acid were identified through HPLC analysis.The methanolic extract of Berberis lyceum strongly inhibited HCV RNA replication with an IC50 of 11.44μg/m L.RT-PCR and Western blotting assays showed that the extract reduced the expression of HCV NS5A in a dosedependent manner.Berberis lyceum extract also attenuated NS5A-induced dysregulation of the MAPK signaling pathway.Conclusions:Our findings suggest that Berberis lyceum extract strongly inhibits HCV propagation by reducing HCV NS5A-induced perturbation of MAPK signaling.

Stochastic maximum power point tracking of photovoltaic energy system under partial shading conditions

A large portion of the available power generation of a photovoltaic (PV) array could be wasted due to partial shading, temperature and irradiance effects, which create current/voltage imbalance between the PV modules. Partial shading is a phenomenon which occurs when some modules in a PV array receive non-uniform irradiation due to dust, cloudy weather or shadows of nearby objects such as buildings, trees, mountains, birds etc. Maximum power point tracking (MPPT) techniques are designed in order to deal with this problem. In this research, a Markov Decision Process (MDP) based MPPT technique is proposed. MDP consists of a set of states, a set of actions in each state, state transition probabilities, reward function, and the discount factor. The PV system in terms of the MDP framework is modelled first and once the states, actions, transition probabilities, and reward function, and the discount factor are defined, the resulting MDP is solved for the optimal policy using stochastic dynamic programming. The behavior of the resulting optimal policy is analyzed and characterized, and the results are compared to existing MPPT control methods.