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Updated: Nov 21, 2025

Establishing a Silicosis Rat Model via Exposure of Whole-Body to Respirable Silica
Published on: October 28, 2022
Investigation of MicroRNA and transcription factor mediated regulatory network for silicosis using systems biology
J K Choudhari1,2, M K Verma1,3, J Choubey2
1Chhattisgarh Swami Vivekanand Technical University, Bhilai, C.G, 491107, India.
Abstract:
Silicosis is a major health issue among workers exposed to crystalline silica. Genetic susceptibility has been implicated in silicosis. The present research demonstrates key regulatory targets and propagated network of gene/miRNA/transcription factor (TF) with interactions responsible for silicosis by integrating publicly available microarray data using a systems biology approach. Array quality is assessed with the Quality Metrics package of Bioconductor, limma package, and the network is constructed using Cytoscape. We observed and enlist 235 differentially expressed genes (DEGs) having up-regulation expression (85 nos) and down-regulation expression (150 nos.) in silicosis; and 24 TFs for the regulation of these DEGs entangled with thousands of miRNAs. Functional enrichment analysis of the DEGs enlighten that, the maximum number of DEGs are responsible for biological process viz, Rab proteins signal transduction (11 nos.) and Cellular Senescence (20 nos.), whereas IL-17 signaling pathway (16 nos.) and Signalling by Nuclear Receptors (14 nos.) etc. are Biological Pathway involving more DEGs. From the identified 1100 high target microRNA (miRNA)s involved in silicosis, 1055 miRNAs are found to relate with down-regulated genes and 847 miRNAs with up-regulated genes. The CDK19 gene (Up-regulated) is associated with 617 miRNAs whereas down-regulated gene ARID5B is regulated by as high as 747 high target miRNAs. In Prediction of Small-molecule signatures, maximum scoring small-molecule combinations for the DEGs have shown that CGP-60774 (with 20 combinations), alvocidib (with 15 combinations) and with AZD-7762 (24 combinations) with few other drugs having the high probability of success.
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