{"database":"GEO","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE320nnn/GSE320221/"]},"type":"primary"},"statusCodeValue":200,"statusCode":"OK"}],"scores":null,"additional":{"omics_type":["Transcriptomics"],"species":["Mus musculus"],"gds_type":["Expression profiling by high throughput sequencing"],"full_dataset_link":["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE320221"],"repository":["GEO"],"entry_type":["GSE"],"additional_accession":[]},"is_claimable":false,"name":"Integrating fine needle aspiration and single-cell RNA sequencing for studying metabolic dysfunction-associated steatotic liver disease","description":"Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the leading cause of chronic liver disease and hepatocellular carcinoma. The immune response plays a central role in disease onset and progression and is the focus of many experimental studies. However, traditional models typically rely on terminal sampling procedures that require large tissue quantities, substantial numbers of animals per experimental condition, and cross-sectional study designs. Here, we propose the integration of two powerful techniques to longitudinally study a MASLD animal model: image-guided fine-needle aspiration (FNA) and single-cell RNA sequencing (scRNA-seq).","dates":{"publication":"2026/06/26"},"accession":"GSE320221","cross_references":{"GSM":["GSM9537954","GSM9537953","GSM9537956","GSM9537955"],"GPL":["19057"],"GSE":["320221"],"taxon":["Mus musculus"]}}