首页|Department of Orthopedics Reports Findings in Bioinformatics(Identification of endocrine-disrupting chemicals targeting key OPassociatedgenes via bioinformat ics and machine learning)
Department of Orthopedics Reports Findings in Bioinformatics(Identification of endocrine-disrupting chemicals targeting key OPassociatedgenes via bioinformat ics and machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Biotechnology - Bioinf ormatics is the subject of a report. Accordingto news reporting originating in Hanzhong, People’s Republic of China, by NewsRx journalists, researchstated, “O steoporosis (OP), a metabolic disorder predominantly impacting postmenopausal wo men, hasseen considerable progress in diagnosis and treatment over the past few decades. However, the intricateinterplay between genetic factors and endocrine disruptors (EDCs) in the pathogenesis of OP remainsinadequately elucidated.”The news reporters obtained a quote from the research from the Department of Ort hopedics, “The objective of this research is to examine the environmental pollut ants and their regulatory mechanismsthat could potentially influence the pathog enesis of OP, in order to establish a theoretical foundationfor the targeted pr evention and medical management of individuals with OP. Utilizing CTD and GEO datasets, network toxicology and bioinformatics analyses were conducted to identif y target genes from a poolof 98 co-associated genes. Subsequently, a novel pred iction model was developed employing a multiplemachine learning algorithm. The efficacy of the model was validated based on the area under the receiveroperati ng characteristic curve. Finally, real-time quantitative polymerase chain reacti on (qRT-PCR) wasused to confirm the expression levels of key genes in clinical samples. We have identified significant genes(FOXO3 and LUM) associated with OP and conducted Gene Ontology, Kyoto Encyclopedia of Genes andGenomes enrichment analysis, immune infiltration analysis, and molecular docking analysis. Through theanalysis of these key genes, we have identified 13 EDCs that have the poten tial to impact OP. Severalendocrine disruptors, such as Dexamethasone, Perfluor ononanoic acid, genistein, cadmium, and bisphenolA, have been identified as not able environmental pollutants that impact the OP. Molecular dockinganalysis rev ealed significant binding affinity of major EDCs to the post-translational prote in structuresof key genes. This study demonstrates that EDCs, including dexamet hasone, perfluorononanoic acid,genistein, cadmium, and bisphenol A, can be iden tified as important environmental pollutants affectingOP, and that FOXO3 and LU M have the potential to be diagnostic markers for OP.”
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