Integrated bioinformatics and machine learning algorithms reveal the critical cellular senescence-associated genes and immune infiltration in heart failure due to ischemic cardiomyopathy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37234159", "kind": "science-record", "revision": 4, "content_hash": "sha256:4a4c9fe17c4307ec0564ec20e42adf79e8f7479e4a1906873d319a0a5351d56f", "created_at": "2026-11-01T19:01:56Z", "updated_at": "2026-11-01T22:52:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated bioinformatics and machine learning algorithms reveal the critical cellular senescence-associated genes and immune infiltration in heart failure due to ischemic cardiomyopathy.", "doi": "10.3389/fimmu.2023.1150304", "pmid": "37234159", "authors": ["Ling Guo", "Chong-En Xu"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "Heart failure (HF) is the final stage of many cardiovascular illnesses and the leading cause of death worldwide. At the same time, ischemic cardiomyopathy has replaced valvular heart disease and hypertension as the primary causes of heart failure. Cellular senescence in heart failure is currently receiving more attention. In this paper, we investigated the correlation between the immunological properties of myocardial tissue and the pathological mechanisms of cellular senescence during ischemic cardiomyopathy leading to heart failure (ICM-HF) using bioinformatics and machine learning methodologies. Our goals were to clarify the pathogenic causes of heart failure and find new treatment options. First, after obtaining GSE5406 from the Gene Expression Omnibus (GEO) database and doing limma analysis, differential genes (DEGs) among the ICM-HF and control groups were identified. We intersected these differential genes with cellular senescence-associated genes (CSAG) via the CellAge database to obtain 39 cellular senescence-associated DEGs (CSA-DEGs). Then, a functional enrichment analysis was performed to elucidate the precise biological processes by which the hub genes control cellular senescence and immunological pathways. Then, the respective key genes were identified by Random Forest (RF) method, LASSO (Least Absolute Shrinkage and Selection Operator) algorithms, and Cytoscape's MCODE plug-in. Three sets of key genes were taken to intersect to obtain three CSA-signature genes (including MYC, MAP2K1, and STAT3), and these three CSA-signature genes were validated in the test gene set (GSE57345), and Nomogram analysis was done. In addition, we assessed the relationship between these three CSA- signature genes and the immunological landscape of heart failure encompassing immunological infiltration expression profiles. This work implies that cellular senescence may have a crucial role in the pathogenesis of ICM-HF, which may be closely tied to its effect on the immune microenvironment. Exploring the molecular underpinnings of cellular senescence during ICM-HF is anticipated to yield significant advances in the disease's diagnosis and therapy.", "claims": [{"id": "claim-method", "statement": "The R package Limma (version 3.40.6) was utilized for differential analysis to find DEGs between the ICM-HF and control groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37234159", "locator": "sections[4] \"Data processing\" paragraph 2", "quote": "The R package Limma (version 3.40.6) was utilized for differential analysis to find DEGs between the ICM-HF and control groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406 and GSE57345.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37234159", "locator": "sections[22] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406 and GSE57345."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37234159"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE5406"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE5406"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37234159", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2023.1150304", "sha256": "sha256:6618edf66f04ce0119b9ff5edc767ff458de4022f7cddd743afe5d24a5e46654", "bytes": 58447, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2023.1150304", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10206252", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE5406", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE5406", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406 and GSE57345.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406 and GSE57345.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM123518", "GSM123519", "GSM123520", "GSM123521", "GSM123522", "GSM123523", "GSM123524", "GSM123525", "GSM123526", "GSM123527", "GSM123528", "GSM123529", "GSM123530", "GSM123531", "GSM123532", "GSM123533", "GSM123534", "GSM123535", "GSM123536", "GSM123537", "GSM123538", "GSM123539", "GSM123540", "GSM123541", "GSM123542", "GSM123543", "GSM123544", "GSM123545", "GSM123546", "GSM123547", "GSM123548", "GSM123549", "GSM123550", "GSM123551", "GSM123552", "GSM123553", "GSM123554", "GSM123555", "GSM123556", "GSM123557", "GSM123558", "GSM123559", "GSM123560", "GSM123561", "GSM123562", "GSM123563", "GSM123564", "GSM123565", "GSM123566", "GSM123567", "GSM123568", "GSM123569", "GSM123570", "GSM123571", "GSM123572", "GSM123573", "GSM123574", "GSM123575", "GSM123576", "GSM123577", "GSM123578", "GSM123579", "GSM123580", "GSM123581", "GSM123582", "GSM123583", "GSM123584", "GSM123585", "GSM123586", "GSM123587", "GSM123588", "GSM123589", "GSM123590", "GSM123591", "GSM123592", "GSM123593", "GSM123594", "GSM123595", "GSM123596", "GSM123597", "GSM123598", "GSM123599", "GSM123600", "GSM123601", "GSM123602", "GSM123603", "GSM123604", "GSM123605", "GSM123606", "GSM123607", "GSM123608", "GSM123609", "GSM123610", "GSM123611", "GSM123612", "GSM123613", "GSM123614", "GSM123615", "GSM123616", "GSM123617", "GSM123618", "GSM123619", "GSM123620", "GSM123621", "GSM123622", "GSM123623", "GSM123624", "GSM123625", "GSM123626", "GSM123627", "GSM123628", "GSM123629", "GSM123630", "GSM123631", "GSM123632", "GSM123633", "GSM123634", "GSM123635", "GSM123636", "GSM123637", "GSM123638", "GSM123639", "GSM123640", "GSM123641", "GSM123642", "GSM123643", "GSM123644", "GSM123645", "GSM123646", "GSM123647", "GSM123648", "GSM123649", "GSM123650", "GSM123651", "GSM123652", "GSM123653", "GSM123654", "GSM123655", "GSM123656", "GSM123657", "GSM123658", "GSM123659", "GSM123660", "GSM123661", "GSM123662", "GSM123663", "GSM123664", "GSM123665", "GSM123666", "GSM123667", "GSM123668", "GSM123669", "GSM123670", "GSM123671", "GSM123672", "GSM123673", "GSM123674", "GSM123675", "GSM123676", "GSM123677", "GSM123678", "GSM123679", "GSM123680", "GSM123681", "GSM123682", "GSM123683", "GSM123684", "GSM123685", "GSM123686", "GSM123687", "GSM123688", "GSM123689", "GSM123690", "GSM123691", "GSM123692", "GSM123693", "GSM123694", "GSM123695", "GSM123696", "GSM123697", "GSM123698", "GSM123699", "GSM123700", "GSM123701", "GSM123702", "GSM123703", "GSM123704", "GSM123705", "GSM123706", "GSM123707", "GSM123708", "GSM123709", "GSM123710", "GSM123711", "GSM123712", "GSM123713", "GSM123714", "GSM123715", "GSM123716", "GSM123717", "GSM123718", "GSM123719", "GSM123720", "GSM123721", "GSM123722", "GSM123723", "GSM123724", "GSM123725", "GSM123726", "GSM123727"], "sample_count": 210, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "Human ischemic cardiomyopathy, idiopathic cardiomyopathy, and nonfailing controls", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE57345", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57345", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE57345", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406 and GSE57345.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406 and GSE57345.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1379812", "GSM1379813", "GSM1379814", "GSM1379815", "GSM1379816", "GSM1379817", "GSM1379818", "GSM1379819", "GSM1379820", "GSM1379821", "GSM1379822", "GSM1379823", "GSM1379824", "GSM1379825", "GSM1379826", "GSM1379827", "GSM1379828", "GSM1379829", "GSM1379830", "GSM1379831", "GSM1379832", "GSM1379833", "GSM1379834", "GSM1379835", "GSM1379836", "GSM1379837", "GSM1379838", "GSM1379839", "GSM1379840", "GSM1379841", "GSM1379842", "GSM1379843", "GSM1379844", "GSM1379845", "GSM1379846", "GSM1379847", "GSM1379848", "GSM1379849", "GSM1379850", "GSM1379851", "GSM1379852", "GSM1379853", "GSM1379854", "GSM1379855", "GSM1379856", "GSM1379857", "GSM1379858", "GSM1379859", "GSM1379860", "GSM1379861", "GSM1379862", "GSM1379863", "GSM1379864", "GSM1379865", "GSM1379866", "GSM1379867", "GSM1379868", "GSM1379869", "GSM1379870", "GSM1379871", "GSM1379872", "GSM1379873", "GSM1379874", "GSM1379875", "GSM1379876", "GSM1379877", "GSM1379878", "GSM1379879", "GSM1379880", "GSM1379881", "GSM1379882", "GSM1379883", "GSM1379884", "GSM1379885", "GSM1379886", "GSM1379887", "GSM1379888", "GSM1379889", "GSM1379890", "GSM1379891", "GSM1379892", "GSM1379893", "GSM1379894", "GSM1379895", "GSM1379896", "GSM1379897", "GSM1379898", "GSM1379899", "GSM1379900", "GSM1379901", "GSM1379902", "GSM1379903", "GSM1379904", "GSM1379905", "GSM1379906", "GSM1379907", "GSM1379908", "GSM1379909", "GSM1379910", "GSM1379911", "GSM1379912", "GSM1379913", "GSM1379914", "GSM1379915", "GSM1379916", "GSM1379917", "GSM1379918", "GSM1379919", "GSM1379920", "GSM1379921", "GSM1379922", "GSM1379923", "GSM1379924", "GSM1379925", "GSM1379926", "GSM1379927", "GSM1379928", "GSM1379929", "GSM1379930", "GSM1379931", "GSM1379932", "GSM1379933", "GSM1379934", "GSM1379935", "GSM1379936", "GSM1379937", "GSM1379938", "GSM1379939", "GSM1379940", "GSM1379941", "GSM1379942", "GSM1379943", "GSM1379944", "GSM1379945", "GSM1379946", "GSM1379947", "GSM1379948", "GSM1379949", "GSM1379950", "GSM1379951", "GSM1379952", "GSM1379953", "GSM1379954", "GSM1379955", "GSM1379956", "GSM1379957", "GSM1379958", "GSM1379959", "GSM1379960", "GSM1379961", "GSM1379962", "GSM1379963", "GSM1379964", "GSM1379965", "GSM1379966", "GSM1379967", "GSM1379968", "GSM1379969", "GSM1379970", "GSM1379971", "GSM1379972", "GSM1379973", "GSM1379974", "GSM1379975", "GSM1379976", "GSM1379977", "GSM1379978", "GSM1379979", "GSM1379980", "GSM1379981", "GSM1379982", "GSM1379983", "GSM1379984", "GSM1379985", "GSM1379986", "GSM1379987", "GSM1379988", "GSM1379989", "GSM1379990", "GSM1379991", "GSM1379992", "GSM1379993", "GSM1379994", "GSM1379995", "GSM1379996", "GSM1379997", "GSM1379998", "GSM1379999", "GSM1380000", "GSM1380001", "GSM1380002", "GSM1380003", "GSM1380004", "GSM1380005", "GSM1380006", "GSM1380007", "GSM1380008", "GSM1380009", "GSM1380010", "GSM1380011", "GSM1380012", "GSM1380013", "GSM1380014", "GSM1380015", "GSM1380016", "GSM1380017", "GSM1380018", "GSM1380019", "GSM1380020", "GSM1380021", "GSM1380022", "GSM1380023", "GSM1380024", "GSM1380025", "GSM1380026", "GSM1380027", "GSM1380028", "GSM1380029", "GSM1380030", "GSM1380031", "GSM1380032", "GSM1380033", "GSM1380034", "GSM1380035", "GSM1380036", "GSM1380037", "GSM1380038", "GSM1380039", "GSM1380040", "GSM1380041", "GSM1380042", "GSM1380043", "GSM1380044", "GSM1380045", "GSM1380046", "GSM1380047", "GSM1380048", "GSM1380049", "GSM1380050", "GSM1380051", "GSM1380052", "GSM1380053", "GSM1380054", "GSM1380055", "GSM1380056", "GSM1380057", "GSM1380058", "GSM1380059", "GSM1380060", "GSM1380061", "GSM1380062", "GSM1380063", "GSM1380064", "GSM1380065", "GSM1380066", "GSM1380067", "GSM1380068", "GSM1380069", "GSM1380070", "GSM1380071", "GSM1380072", "GSM1380073", "GSM1380074", "GSM1380075", "GSM1380076", "GSM1380077", "GSM1380078", "GSM1380079", "GSM1380080", "GSM1380081", "GSM1380082", "GSM1380083", "GSM1380084", "GSM1380085", "GSM1380086", "GSM1380087", "GSM1380088", "GSM1380089", "GSM1380090", "GSM1380091", "GSM1380092", "GSM1380093", "GSM1380094", "GSM1380095", "GSM1380096", "GSM1380097", "GSM1380098", "GSM1380099", "GSM1380100", "GSM1380101", "GSM1380102", "GSM1380103", "GSM1380104", "GSM1380105", "GSM1380106", "GSM1380107", "GSM1380108", "GSM1380109", "GSM1380110", "GSM1380111", "GSM1380112", "GSM1380113", "GSM1380114", "GSM1380115", "GSM1380116", "GSM1380117", "GSM1380118", "GSM1380119", "GSM1380120", "GSM1380121", "GSM1380122", "GSM1380123", "GSM1380124", "GSM1380718", "GSM1380719", "GSM1380720", "GSM1380721", "GSM1380722", "GSM1380723"], "sample_count": 319, "group_sizes": null, "group_sizes_basis": null, "platform": "11532;9052", "taxon": "Homo sapiens", "title": "RNA-Seq Identifies Novel Myocardial Gene Expression Signatures of Heart Failure", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE5406 not downloaded", "asset:data:geo:GSE5406 licence not read", "asset:data:geo:GSE57345 not downloaded", "asset:data:geo:GSE57345 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The R package Limma (version 3.40.6) was utilized for differential analysis to find DEGs between the ICM-HF and control groups."}}, {"id": "method-2", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "Random Forest"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE5406", "GSE57345"], "resolved_accessions": ["GSE5406", "GSE57345"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5406 and GSE57345."], "basis": "The paper names GSE5406, GSE57345 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:37234159", "data:geo:GSE5406"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE5406"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:41:49Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 15914, "completion_tokens": 1635, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:37234159", "type": "paper", "label": "pmid:37234159"}, {"id": "source:pmid:37234159", "type": "manuscript", "label": "PMID 37234159 full text"}, {"id": "data:geo:GSE5406", "type": "dataset", "label": "GEO GSE5406"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37234159", "type": "paper", "label": "pmid:37234159"}, {"id": "source:pmid:37234159", "type": "manuscript", "label": "PMID 37234159 full text"}, {"id": "data:geo:GSE5406", "type": "dataset", "label": "GEO GSE5406"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37234159", "type": "extraction", "used": ["source:pmid:37234159"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE5406", "type": "accession_resolution", "used": ["data:geo:GSE5406"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:37234159", "parent_hash": "sha256:2427b1137ccfae6ef4f8fbd919fe7bfa322455cb2f9547dd2687ee5a6c4336af", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE5406 licence not read", "asset:data:geo:GSE5406 not downloaded", "asset:data:geo:GSE57345 licence not read", "asset:data:geo:GSE57345 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The R package Limma (version 3.40.6) was utilized for differential analysis to find DEGs between the ICM-HF and control groups."], "order_basis": "analysis_only", "id": "assay:1"}]}