Exploratory experiment designed to discover new patterns targeting HMGCS2 in human patients, mouse models. Primary outcome: differential gene expression patterns
Microarray and single-cell RNA expression datasets were analyzed to identify lipid metabolism-related differentially expressed genes in pulmonary fibrosis. This bioinformatics analysis revealed HMGCS2 as a key regulator that was specifically decreased in AECIIs during fibrosis development. The analysis integrated multiple omics datasets to provide comprehensive gene expression profiles related to lipid metabolism dysfunction in pulmonary fibrosis.
Computational analysis of microarray and single-cell RNA-seq datasets
Identification of dysregulated lipid metabolism genes
Significant differential expression of lipid metabolism genes
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