Medicinal Effects, Phytochemistry,Pharmacology of Euphorbia prostrata and Promising MolecularMechanisms

Euphorbiaceae is a large family of dicotyledonous angiosperms with diverse genera including Euphorbia prostrata(E.prostrata).Current research has provided scientific evidence for traditional uses of E.prostrata against diverse pathological conditions such as anti-hemorrhoidal,anti-inflammatory,analgesic,wound healing,antioxidant,antibacterial,leishmanicidal,antitumor activity,and so on.The phytochemical screening has revealed the presence of glycosides,phytosterols,flavonoids,polyphenols,tannins,and anthraquinones with chemical structures elucidation of their respective compounds.The uniqueness of such multifactorial compounds present in this species endorses it as the potent therapeutic or prophylactic choice for several fatal diseases.Although ethnomedical applications served as a significant citation for pharmacology,the molecular mechanism has not been reviewed yet.The present paper provides a comprehensive review of research outcomes,pharmacology,toxicology,and molecular signaling of phytochemicals of E.prostrata species as a reference for relevant researchers.The study of bioactive compounds in crude extracts and fractions,the demonstration of primary mechanisms of pharmacology,along with the addition of toxicity,and clinical trials,should be conceded in depth.This review underlines the E.prostrata species that can be a promising phytomedicine since we are committed to excavating more intensely into their pharmacological role.

Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach

Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine,because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches.One of the pathways known to be important for the development of neoplastic diseases and pathological processes is the Hedgehog signaling pathway that normally controls human embryonic development.Systematic accumulation of various types of biological data,including interactions between proteins,regulation of genes transcription,proteomics,and metabolomics experiments results,allows the application of computational analysis of these big data for identification of key molecular mechanisms of certain diseases and pathologies and promising therapeutic targets.The aim of this study is to develop a computational approach for revealing associations between human proteins and genes interacting with the Hedgehog pathway components,as well as for identifying their roles in the development of various types of tumors.We automatically collect sets of abstract texts from the NCBI PubMed bibliographic database.For recognition of the Hedgehog pathway proteins and genes and neoplastic diseases we use a dictionary-based named entity recognition approach,while for all other proteins and genes machine learning method is used.For association extraction,we develop a set of semantic rules.We complete the results of the text analysis with the gene set enrichment analysis.The identified key pathways that may influence the Hedgehog pathway and their roles in tumor development are then verified using the information in the literature.