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pmid:39994392

Atrial fibrillation risk model based on LASSO and SVM algorithms and immune infiltration of key mitochondrial energy metabolism genes.

Xunjie Yang · Weng Lan · Chunyi Lin · Chunyu Zhu · Zicong Ye · Zhishi Chen · Guian Zheng

Scientific reports · 2025 doi:10.1038/s41598-025-91047-3

Paper

complete

Experiment

complete

Data

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Analysis

partial

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:39994392
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2026-11-01T20:30:14Z
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paper object · 10 fields
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title
Atrial fibrillation risk model based on LASSO and SVM algorithms and immune infiltration of key mitochondrial energy metabolism genes.
doi
10.1038/s41598-025-91047-3
pmid
39994392
authors array · 7 items
[0]
Xunjie Yang
[1]
Weng Lan
[2]
Chunyi Lin
[3]
Chunyu Zhu
[4]
Zicong Ye
[5]
Zhishi Chen
[6]
Guian Zheng
journal
Scientific reports
year
2025
abstract
Atrial fibrillation (AF) is a predominant cardiac arrhythmia with unclear etiology. This study used bioinformatics and machine learning to explore the relationship between mitochondrial energy metabolism-related genes (MEMRGs) and immune infiltration in AF. The datasets GSE31821, GSE41177, and GSE79768 were retrieved from the Gene Expression Omnibus (GEO) database, and differential expression analysis identified 59 mitochondrial energy metabolism-related differentially expressed genes (MEMRDEGs) associated with AF. Key MEMRDEGs were selected using the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) methods, and a diagnostic model was developed. Immune infiltration was assessed using single-sample gene set enrichment analysis (ssGSEA) and the microenvironment cell population counter (MCPcounter). The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903. Significant differences in immune cell composition were observed between the AF and control groups. ALDH1L2 was positively correlated with most immune cells, while SLC25A3 showed a negatively correlated with the monocytic lineage. The findings indicate that MEMRGs interact with immune responses in AF, offering insights into the potential molecular mechanisms and therapeutic targets for AF.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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sections[30] "Data availability" paragraph 2
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903.
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The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903.
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The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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Gene expression and miRNA profiles in atrial fibrillation. Role of miR-21.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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Region-specific gene expression profiles in left atria of patients with valvular atrial fibrillation
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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Atrial fibrillation is associated with altered left-to-right atria gene expression ratio: implications for arrhythmogenesis and thrombogenesis
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The differential analysis of the integrated GEO datasets was executed with the limma R package, which compared the gene expression levels of the AF and normal groups to identify DEGs between the two groups. The LASSO regression method was subsequently executed with glmnet (R package)39, with the settings specified as set. seed (500) and family="binomial.” Finally, we built an SVM model using the 52 MEMRDEGs and the SVM technique.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.
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activity-reading-sci-2026-11-01
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pmid:39994392
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paper
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pmid:39994392
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source:pmid:39994392
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PMID 39994392 full text
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id
data:geo:GSE31821
type
dataset
label
GEO GSE31821
agent
agent:corpus-assay-engine
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type
extraction
used array · 1 item
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source:pmid:39994392
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agent:minimax-reader
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activity-resolve-GSE31821
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agent:corpus-assay-engine
agents array · 2 items
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agent:corpus-assay-engine
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software
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agent:minimax-reader
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reading-sci-2026-11-01
dsl_catalogue_fingerprint
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gaps array · 11 items
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asset:data:geo:GSE31821 licence not read
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asset:data:geo:GSE31821 not downloaded
[2]
asset:data:geo:GSE41177 licence not read
[3]
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asset:data:geo:GSE79768 licence not read
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review.machine_critique
assays array · 1 item
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evidence array · 1 item
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The differential analysis of the integrated GEO datasets was executed with the limma R package, which compared the gene expression levels of the AF and normal groups to identify DEGs between the two groups. The LASSO regression method was subsequently executed with glmnet (R package)39, with the settings specified as set. seed (500) and family="binomial.” Finally, we built an SVM model using the 52 MEMRDEGs and the SVM technique.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39994392", "kind": "science-record", "revision": 4, "content_hash": "sha256:2a78d9a029c572f2c8c4c3da9b2ba2ae2fcca8a6f44be532c3f0730af6c0ae34", "created_at": "2026-11-01T20:30:14Z", "updated_at": "2026-11-01T22:56:09Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Atrial fibrillation risk model based on LASSO and SVM algorithms and immune infiltration of key mitochondrial energy metabolism genes.", "doi": "10.1038/s41598-025-91047-3", "pmid": "39994392", "authors": ["Xunjie Yang", "Weng Lan", "Chunyi Lin", "Chunyu Zhu", "Zicong Ye", "Zhishi Chen", "Guian Zheng"], "journal": "Scientific reports", "year": 2025, "abstract": "Atrial fibrillation (AF) is a predominant cardiac arrhythmia with unclear etiology. This study used bioinformatics and machine learning to explore the relationship between mitochondrial energy metabolism-related genes (MEMRGs) and immune infiltration in AF. The datasets GSE31821, GSE41177, and GSE79768 were retrieved from the Gene Expression Omnibus (GEO) database, and differential expression analysis identified 59 mitochondrial energy metabolism-related differentially expressed genes (MEMRDEGs) associated with AF. Key MEMRDEGs were selected using the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) methods, and a diagnostic model was developed. Immune infiltration was assessed using single-sample gene set enrichment analysis (ssGSEA) and the microenvironment cell population counter (MCPcounter). The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903. Significant differences in immune cell composition were observed between the AF and control groups. ALDH1L2 was positively correlated with most immune cells, while SLC25A3 showed a negatively correlated with the monocytic lineage. The findings indicate that MEMRGs interact with immune responses in AF, offering insights into the potential molecular mechanisms and therapeutic targets for AF.", "claims": [{"id": "claim-data-access", "statement": "The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39994392", "locator": "sections[30] \"Data availability\" paragraph 2", "quote": "The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39994392", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The diagnostic model, based on the key genes ACAT1, ALDH1L2, HTT, OGDH, and SLC25A3, achieved an area under the curve (AUC) of 0.903.", "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:39994392"], "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:GSE31821"], "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:GSE31821"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39994392", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-025-91047-3", "sha256": "sha256:ec0b2ca9078e8650c145260c45b930c521f53b3f8e805bbde5332b2c709a6f3d", "bytes": 67722, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-025-91047-3", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11850640", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE31821", "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=GSE31821", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE31821", "version": null, "note": "The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. 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Role of miR-21.", "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:GSE41177", "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=GSE41177", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE41177", "version": null, "note": "The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1005418", "GSM1005419", "GSM1005420", "GSM1005421", "GSM1005422", "GSM1005423", "GSM1005424", "GSM1005425", "GSM1005426", "GSM1005427", "GSM1005428", "GSM1005429", "GSM1005430", "GSM1005431", "GSM1005432", "GSM1005433", "GSM1005434", "GSM1005435", "GSM1005436", "GSM1005437", "GSM1005438", "GSM1005439", "GSM1005440", "GSM1005441", "GSM1005442", "GSM1005443", "GSM1005444", "GSM1005445", "GSM1006245", "GSM1006246", "GSM1006247", "GSM1006248", "GSM1006249", "GSM1006250", "GSM1006251", "GSM1006252", "GSM1006253", "GSM1006254"], "sample_count": 38, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Region-specific gene expression profiles in left atria of patients with valvular atrial fibrillation", "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:GSE79768", "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=GSE79768", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE79768", "version": null, "note": "The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE31821", "GSE41177", "GSE79768"], "resolved_accessions": ["GSE31821", "GSE41177", "GSE79768"], "statements": ["The data that support the findings of this study are available from the corresponding author upon reasonable request.The datasets supporting the results of this study are publicly available and can be accessed as follows: Gene expression data: The data used in this study are available from the Gene Expression Omnibus (GEO) repository, accessible at the following links: GSE31821: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE31821 GSE41177: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE41177 GSE79768: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? acc=GSE79768 KEGG pathway gene sets: The gene sets hsa00190, hsa05415, hsa05016, hsa05208, and hsa05012 were sourced from KEGG (Kyoto Encyclopedia of Genes and Genomes), and permission to use these materials has been obtained from KEGG. The KEGG database can be accessed at https://www.kegg.jp."], "basis": "The paper names GSE31821, GSE41177, GSE79768 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:39994392", "data:geo:GSE31821"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE31821"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:46:45Z", "independence": "single_reader"}, "evidence_check": {"method": "reordered", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 17320, "completion_tokens": 2486, "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:39994392", "type": "paper", "label": "pmid:39994392"}, {"id": "source:pmid:39994392", "type": "manuscript", "label": "PMID 39994392 full text"}, {"id": "data:geo:GSE31821", "type": "dataset", "label": "GEO GSE31821"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39994392", "type": "paper", "label": "pmid:39994392"}, {"id": "source:pmid:39994392", "type": "manuscript", "label": "PMID 39994392 full text"}, {"id": "data:geo:GSE31821", "type": "dataset", "label": "GEO GSE31821"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39994392", "type": "extraction", "used": ["source:pmid:39994392"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE31821", "type": "accession_resolution", "used": ["data:geo:GSE31821"], "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:39994392", "parent_hash": "sha256:172b6d70e50fa632ee185d27d4cbbe34d234fbaaf04e0bd0ee49b8618e885287", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE31821 licence not read", "asset:data:geo:GSE31821 not downloaded", "asset:data:geo:GSE41177 licence not read", "asset:data:geo:GSE41177 not downloaded", "asset:data:geo:GSE79768 licence not read", "asset:data:geo:GSE79768 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "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 differential analysis of the integrated GEO datasets was executed with the limma R package, which compared the gene expression levels of the AF and normal groups to identify DEGs between the two groups. The LASSO regression method was subsequently executed with glmnet (R package)39, with the settings specified as set. seed (500) and family=\"binomial.” Finally, we built an SVM model using the 52 MEMRDEGs and the SVM technique."], "order_basis": "analysis_only", "id": "assay:1"}]}