Nature against Diabetic Retinopathy: A Review on Antiangiogenic, Antioxidant, and Anti-Inflammatory Phytochemicals.

Background and Purpose. Diabetes mellitus (DM), hyperglycemia, and hypertension can result in diabetic retinopathy (DR), which is a major cause of blindness on a global scale. Development of DR is associated with decreased endothelial cells, increased basal membrane thickness, permeation of the retinal blood barrier, and neovascularization in patients. The purpose of the present review is to provide an overview of the findings regarding applications of phytochemicals for DR treatment and could be a beneficial resource for further clinical studies and also a basis for pharmaceutical purposes for drug design. Materials and Methods. A narrative literature review was performed from electronic databases including Web of Science, PubMed, and Scopus to analyze the effects of different phytochemicals to prevent or treat oxidation, angiogenesis, and inflammation in diabetic retinopathy. The inclusion criteria were original studies, which included the effects of different phytochemicals on diabetic retinopathy. The exclusion criteria included studies other than original articles, studies which assessed the effects of phytochemicals on nondiabetic retinopathy, and studies which used phytochemical-rich extracts. Results and Conclusions. Studies have shown that increased levels of inflammatory cytokines, angiogenic, and oxidative stress factors are involved in the progression and pathogenesis of DR. Therefore, phytochemicals with their anti-inflammatory, antiangiogenic, and antioxidant properties can prevent DR progression and retinal damage through various cellular mechanisms. It is also shown that some phytochemicals can simultaneously affect the inflammation, oxidation, and angiogenesis in DR.

Noncoding RNA Roles in Pharmacogenomic Responses to Aspirin: New Molecular Mechanisms for an Old Drug.

Aspirin, as one of the most frequently prescribed drugs, can have therapeutic effects on different conditions such as cardiovascular and metabolic disorders and malignancies. The effects of this common cardiovascular drug are exerted through different molecular and cellular pathways. Altered noncoding RNA (ncRNA) expression profiles during aspirin treatments indicate a close relationship between these regulatory molecules and aspirin effects through regulating gene expressions. A better understanding of the molecular networks contributing to aspirin efficacy would help optimize efficient therapies for this very popular drug. This review is aimed at discussing and highlighting the identified interactions between aspirin and ncRNAs and their targeting pathways and better understanding pharmacogenetic responses to aspirin.

Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic.

Coronavirus disease 2019 (COVID-19) has made many concerns for healthcare services especially, in finding useful therapeutic(s). Despite the scientists' struggle to find and/or creating possible drugs, so far there is no treatment with high efficiency for the disease. During the pandemic, researchers have performed some molecular analyses to find potential therapeutics out of both the natural and synthetic available medicines. Computer simulations and related data have shown a significant role in drug discovery and development before. In this field, antiviral drugs, phytochemicals, anti-inflammatory agents, etc. were essential groups of compounds tested against COVID-19, using molecular modeling, molecular dynamics (MD), and docking tools. The results indicate promising effects of such compounds to be used in further experimental and clinical trials; Chloroquine, Chloroquine-OH, and Umifenovir as viral entry inhibitors, Remdesivir, Ribavirin, Lopinavir, Ritonavir, and Darunavir as viral replication inhibitors, and Sirolimus are the examples, which were tested clinically on patients after comprehensive assessments of the available data on molecular simulation. This review summarizes the outcomes of various computer simulations data in the battle against COVID-19.