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pmid:37063958

Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and atherosclerosis.

Shuangyang Mo · Yingwei Wang · Xin Yuan · Wenhong Wu · Huaying Zhao · Haixiao Wei · Haiyan Qin · Haixing Jiang · Shanyu Qin

Frontiers in cardiovascular medicine · 2023 doi:10.3389/fcvm.2023.1142296

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complete

Experiment

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Data

partial

Analysis

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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:37063958
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title
Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and atherosclerosis.
doi
10.3389/fcvm.2023.1142296
pmid
37063958
authors array · 9 items
[0]
Shuangyang Mo
[1]
Yingwei Wang
[2]
Xin Yuan
[3]
Wenhong Wu
[4]
Huaying Zhao
[5]
Haixiao Wei
[6]
Haiyan Qin
[7]
Haixing Jiang
[8]
Shanyu Qin
journal
Frontiers in cardiovascular medicine
year
2023
abstract
Background: Atherosclerosis (AS) is one of the leading causes of the cardio-cerebral vascular incident. The constantly emerging evidence indicates a close association between nonalcoholic fatty liver disease (NAFLD) and AS. However, the exact molecular mechanisms underlying the correlation between these two diseases remain unclear. This study proposed exploring the common signature genes, pathways, and immune cells among AS and NAFLD. Methods: The common differentially expressed genes (co-DEGs) with a consistent trend were identified via bioinformatic analyses of the Gene Expression Omnibus (GEO) datasets GSE28829 and GSE49541, respectively. Further, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. We utilized machine learning algorithms of lasso and random forest (RF) to identify the common signature genes. Then the diagnostic nomogram models and receiver operator characteristic curve (ROC) analyses were constructed and validated with external verification datasets. The gene interaction network was established via the GeneMANIA database. Additionally, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to explore the co-regulated pathways and immune cells. Results: A total of 11 co-DEGs were identified. GO and KEGG analyses revealed that co-DEGs were mainly enriched in lipid catabolic process, calcium ion transport, and regulation of cytokine. Moreover, three common signature genes (PLCXD3, CCL19, and PKD2) were defined. Based on these genes, we constructed the efficiently predictable diagnostic models for advanced AS and NAFLD with the nomograms, evaluated with the ROC curves (AUC = 0.995 for advanced AS, 95% CI 0.971-1.0; AUC = 0.973 for advanced NAFLD, 95% CI 0.938-0.998). In addition, the AUC of the verification datasets had a similar trend. The NOD-like receptors (NLRs) signaling pathway might be the most crucial co-regulated pathway, and activated CD4 T cells and central memory CD4 T cells were significantly excessive infiltration in advanced NAFLD and AS. Conclusion: We identified three common signature genes (PLCXD3, CCL19, and PKD2), co-regulated pathways, and shared immune features of NAFLD and AS, which might provide novel insights into the molecular mechanism of NAFLD complicated with AS.
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The differently expressed genes (DEGs) were identified from normalized and preprocessed data via the GEO2R tool (23).
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sections[4] "Identification of co-DEGs" paragraph 2
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The differently expressed genes (DEGs) were identified from normalized and preprocessed data via the GEO2R tool (23).
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Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.
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Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.
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A total of 11 co-DEGs were identified.
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A total of 11 co-DEGs were identified.
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GEO2R tool
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quote
The differently expressed genes (DEGs) were identified from normalized and preprocessed data via the GEO2R tool (23).
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gaps array · 2 items
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method.reader_named_unmapped
[1]
method.machine_learning_random_forest
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complete
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capability:computational_analysis
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assay_families array · 9 items
[0]
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[3]
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candidate
Automated Assays Laravel application and simulated adapters
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tier
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missing_operations array · 1 item
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: random_forest.
capability object · 4 fields
tier
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capability:computational_analysis
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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[0]
GSE28829
[1]
GSE49541
[2]
GSE43292
[3]
GSE48452
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[0]
GSE28829
[1]
GSE49541
[2]
GSE43292
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statements array · 1 item
[0]
Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.
basis
The paper names GSE28829, GSE49541, GSE43292, GSE48452 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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machine_learning_random_forest
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data:geo:GSE28829
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MiniMax-M3.1-Flash
provider
minimax
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minimax
read_at
2026-11-01T18:36:35Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
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5
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12012
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2418
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256
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PMID 37063958 full text
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data:geo:GSE28829
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label
GEO GSE28829
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[0] object · 4 fields
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classification
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pmid:37063958
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PMID 37063958 full text
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data:geo:GSE28829
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dataset
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GEO GSE28829
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agent:corpus-assay-engine
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data:geo:GSE28829
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agent:corpus-assay-engine
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dsl_catalogue_fingerprint
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[3]
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asset:data:geo:GSE48452 licence not read
[5]
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[6]
asset:data:geo:GSE49541 licence not read
[7]
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method.machine_learning_random_forest
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37063958", "kind": "science-record", "revision": 3, "content_hash": "sha256:a578f771d08d1b9a13b205fbdd5e9f350883cae88b05ddf0014056a2fa664054", "created_at": "2026-11-01T19:01:43Z", "updated_at": "2026-11-01T22:09:16Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and atherosclerosis.", "doi": "10.3389/fcvm.2023.1142296", "pmid": "37063958", "authors": ["Shuangyang Mo", "Yingwei Wang", "Xin Yuan", "Wenhong Wu", "Huaying Zhao", "Haixiao Wei", "Haiyan Qin", "Haixing Jiang", "Shanyu Qin"], "journal": "Frontiers in cardiovascular medicine", "year": 2023, "abstract": "Background: Atherosclerosis (AS) is one of the leading causes of the cardio-cerebral vascular incident. The constantly emerging evidence indicates a close association between nonalcoholic fatty liver disease (NAFLD) and AS. However, the exact molecular mechanisms underlying the correlation between these two diseases remain unclear. This study proposed exploring the common signature genes, pathways, and immune cells among AS and NAFLD.\nMethods: The common differentially expressed genes (co-DEGs) with a consistent trend were identified via bioinformatic analyses of the Gene Expression Omnibus (GEO) datasets GSE28829 and GSE49541, respectively. Further, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. We utilized machine learning algorithms of lasso and random forest (RF) to identify the common signature genes. Then the diagnostic nomogram models and receiver operator characteristic curve (ROC) analyses were constructed and validated with external verification datasets. The gene interaction network was established via the GeneMANIA database. Additionally, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to explore the co-regulated pathways and immune cells.\nResults: A total of 11 co-DEGs were identified. GO and KEGG analyses revealed that co-DEGs were mainly enriched in lipid catabolic process, calcium ion transport, and regulation of cytokine. Moreover, three common signature genes (PLCXD3, CCL19, and PKD2) were defined. Based on these genes, we constructed the efficiently predictable diagnostic models for advanced AS and NAFLD with the nomograms, evaluated with the ROC curves (AUC = 0.995 for advanced AS, 95% CI 0.971-1.0; AUC = 0.973 for advanced NAFLD, 95% CI 0.938-0.998). In addition, the AUC of the verification datasets had a similar trend. The NOD-like receptors (NLRs) signaling pathway might be the most crucial co-regulated pathway, and activated CD4 T cells and central memory CD4 T cells were significantly excessive infiltration in advanced NAFLD and AS.\nConclusion: We identified three common signature genes (PLCXD3, CCL19, and PKD2), co-regulated pathways, and shared immune features of NAFLD and AS, which might provide novel insights into the molecular mechanism of NAFLD complicated with AS.", "claims": [{"id": "claim-method", "statement": "The differently expressed genes (DEGs) were identified from normalized and preprocessed data via the GEO2R tool (23).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37063958", "locator": "sections[4] \"Identification of co-DEGs\" paragraph 2", "quote": "The differently expressed genes (DEGs) were identified from normalized and preprocessed data via the GEO2R tool (23)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37063958", "locator": "sections[25] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 11 co-DEGs were identified.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37063958", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 11 co-DEGs were identified."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "A total of 11 co-DEGs were identified.", "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:37063958"], "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:GSE28829"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:machine_learning_random_forest", "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:GSE28829"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:machine_learning_random_forest"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37063958", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcvm.2023.1142296", "sha256": "sha256:4197675994849ce031a39c1003da6582fbc3ade2e60eb4b7b03299f83288a28c", "bytes": 46140, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fcvm.2023.1142296", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10098172", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE28829", "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=GSE28829", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE28829", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM714070", "GSM714071", "GSM714072", "GSM714073", "GSM714074", "GSM714075", "GSM714076", "GSM714077", "GSM714078", "GSM714079", "GSM714080", "GSM714081", "GSM714082", "GSM714083", "GSM714084", "GSM714085", "GSM714086", "GSM714087", "GSM714088", "GSM714089", "GSM714090", "GSM714091", "GSM714092", "GSM714093", "GSM714094", "GSM714095", "GSM714096", "GSM714097", "GSM714098"], "sample_count": 29, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene Expression in early and advanced atherosclerotic plaque from human carotid", "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:GSE43292", "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=GSE43292", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE43292", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. 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This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49541; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43292; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48452.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1178970", "GSM1178971", "GSM1178972", "GSM1178973", "GSM1178974", "GSM1178975", "GSM1178976", "GSM1178977", "GSM1178978", "GSM1178979", "GSM1178980", "GSM1178981", "GSM1178982", "GSM1178983", "GSM1178984", "GSM1178985", "GSM1178986", "GSM1178987", "GSM1178988", "GSM1178989", "GSM1178990", "GSM1178991", "GSM1178992", "GSM1178993", "GSM1178994", "GSM1178995", "GSM1178996", "GSM1178997", "GSM1178998", "GSM1178999", "GSM1179000", "GSM1179001", "GSM1179002", "GSM1179003", "GSM1179004", "GSM1179005", "GSM1179006", "GSM1179007", "GSM1179008", "GSM1179009", "GSM1179010", "GSM1179011", "GSM1179012", "GSM1179013", "GSM1179014", "GSM1179015", "GSM1179016", "GSM1179017", "GSM1179018", "GSM1179019", "GSM1179020", "GSM1179021", "GSM1179022", "GSM1179023", "GSM1179024", "GSM1179025", "GSM1179026", "GSM1179027", "GSM1179028", "GSM1179029", "GSM1179030", "GSM1179031", "GSM1179032", "GSM1179033", "GSM1179034", "GSM1179035", "GSM1179036", "GSM1179037", "GSM1179038", "GSM1179039", "GSM1179040", "GSM1179041", "GSM1179042"], "sample_count": 73, "group_sizes": null, "group_sizes_basis": null, "platform": "11532", "taxon": "Homo sapiens", "title": "Human liver biopsy of different phases from control to NASH", "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:GSE49541", "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=GSE49541", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE49541", "version": null, "note": "Publicly available datasets were analyzed in this study. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:37063958", "data:geo:GSE28829"], "steps": []}, "must_build": {"dsl_operations": [{"operation": "machine_learning_random_forest", "unlocks_papers": null, "priority": null}], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE28829"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:36:35Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12012, "completion_tokens": 2418, "cached_tokens": 256}}, "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:37063958", "type": "paper", "label": "pmid:37063958"}, {"id": "source:pmid:37063958", "type": "manuscript", "label": "PMID 37063958 full text"}, {"id": "data:geo:GSE28829", "type": "dataset", "label": "GEO GSE28829"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37063958", "type": "paper", "label": "pmid:37063958"}, {"id": "source:pmid:37063958", "type": "manuscript", "label": "PMID 37063958 full text"}, {"id": "data:geo:GSE28829", "type": "dataset", "label": "GEO GSE28829"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37063958", "type": "extraction", "used": ["source:pmid:37063958"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE28829", "type": "accession_resolution", "used": ["data:geo:GSE28829"], "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:37063958", "parent_hash": "sha256:08d544ca28d3af2145a328a6a48345924d9b52aec49d672a99672fc6249efb85", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE28829 licence not read", "asset:data:geo:GSE28829 not downloaded", "asset:data:geo:GSE43292 licence not read", "asset:data:geo:GSE43292 not downloaded", "asset:data:geo:GSE48452 licence not read", "asset:data:geo:GSE48452 not downloaded", "asset:data:geo:GSE49541 licence not read", "asset:data:geo:GSE49541 not downloaded", "execution.not_run", "method.machine_learning_random_forest", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:run_analysis blocked on method:machine_learning_random_forest"], "assays": [{"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["random forest"], "order_basis": "analysis_only", "id": "assay:1"}]}