Screening of hub genes and immunocytes related to tendon injury based on bioinformatics and machine learning models.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40858849", "kind": "science-record", "revision": 4, "content_hash": "sha256:541bee11412d4a4023079603c2a78c83335e6dd77997d5c0c8dded182cd6bde4", "created_at": "2026-11-01T20:30:58Z", "updated_at": "2026-11-01T22:57:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Screening of hub genes and immunocytes related to tendon injury based on bioinformatics and machine learning models.", "doi": "10.1038/s41598-025-15210-6", "pmid": "40858849", "authors": ["Shulong Sun", "Hua Li", "Yan Li", "Liubing Yang", "Juanjuan Zhang", "Yujing Cao"], "journal": "Scientific reports", "year": 2025, "abstract": "Tendon injury is a common and challenging clinical problem, and its healing process involves complex cellular and biological factors. Therefore, this study aims to reveal the mechanism of tendon healing and provide theoretical basis for clinical treatment. We first selected GSE26051 dataset from the GEO database and used R language to obtain 721 DEGs (459 up-regulated and 262 down-regulated). Subsequently, the 7378 genes of tendon injury obtained from the GeneCards database were intersected with DEGs to obtain 228 common genes. We constructed a PPI network of common genes using the STRING database, visualized it using Cytoscape software, and selected the top 10 (MYH6, MYL3, MYH1, MYH8, MYL1, TTN, TCAP, PKP2, ACTN2, CSRP3) genes through the CytoHubba plugin. We further identified hub genes (MYH1, MYH6, PKP2, MYH8) via machine learning models. Afterwards, the cytoskeleton in muscle cells and IL-17 signaling pathways were obtained by GO and KEGG analysis of common genes. Finally, the macrophages M2 was screened through immune infiltration analysis. This study revealed that hub genes such as MYH1, MYH6, MYH8 and PKP2 were mainly enriched in the cytoskeleton in muscle cells signaling pathway, and macrophage M2 played an important role in the inflammatory phase of tendon healing.", "claims": [{"id": "claim-method", "statement": "For additional identification of hub genes, three machine learning algorithms (LASSO, RF, and SVM) were employed to examine the hub genes derived from the earlier PPI network.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40858849", "locator": "sections[12] \"Identification of hub genes linked to tendon injury via machine learning\" paragraph 2", "quote": "For additional identification of hub genes, three machine learning algorithms (LASSO, RF, and SVM) were employed to examine the hub genes derived from the earlier PPI network."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Based on the criteria for selection, GSE26051 dataset was chosen for this research, encompassing gene expression profiles of tendon tissues from 23 patients with tendon injuries and 23 healthy tendons.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40858849", "locator": "sections[9] \"Dataset collection and preprocessing\" paragraph 2", "quote": "Based on the criteria for selection, GSE26051 dataset was chosen for this research, encompassing gene expression profiles of tendon tissues from 23 patients with tendon injuries and 23 healthy tendons."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We first selected GSE26051 dataset from the GEO database and used R language to obtain 721 DEGs (459 up-regulated and 262 down-regulated).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40858849", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We first selected GSE26051 dataset from the GEO database and used R language to obtain 721 DEGs (459 up-regulated and 262 down-regulated)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We first selected GSE26051 dataset from the GEO database and used R language to obtain 721 DEGs (459 up-regulated and 262 down-regulated).", "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:40858849"], "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:GSE26051"], "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:GSE26051"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40858849", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-025-15210-6", "sha256": "sha256:719b444e5fe4faa7747afeb30ab3ce467f9db9bb7e9a5ea9a95b4952967e4d68", "bytes": 47582, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-025-15210-6", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12381286", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE26051", "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=GSE26051", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE26051", "version": null, "note": "Based on the criteria for selection, GSE26051 dataset was chosen for this research, encompassing gene expression profiles of tendon tissues from 23 patients with tendon injuries and 23 healthy tendons.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Based on the criteria for selection, GSE26051 dataset was chosen for this research, encompassing gene expression profiles of tendon tissues from 23 patients with tendon injuries and 23 healthy tendons.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM639748", "GSM639749", "GSM639750", "GSM639751", "GSM639752", "GSM639753", "GSM639754", "GSM639755", "GSM639756", "GSM639757", "GSM639758", "GSM639759", "GSM639760", "GSM639761", "GSM639762", "GSM639763", "GSM639764", "GSM639765", "GSM639766", "GSM639767", "GSM639768", "GSM639769", "GSM639770", "GSM639771", "GSM639772", "GSM639773", "GSM639774", "GSM639775", "GSM639776", "GSM639777", "GSM639778", "GSM639779", "GSM639780", "GSM639781", "GSM639782", "GSM639783", "GSM639784", "GSM639785", "GSM639786", "GSM639787", "GSM639788", "GSM639789", "GSM639790", "GSM639791", "GSM639792", "GSM639793"], "sample_count": 46, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Analysis of Human Tendinopathy Gene Expression", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE26051 not downloaded", "asset:data:geo:GSE26051 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "For additional identification of hub genes, three machine learning algorithms (LASSO, RF, and SVM) were employed to examine the hub genes derived from the earlier PPI network."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "PPI"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: support_vector_machine."}, "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": ["GSE26051"], "resolved_accessions": ["GSE26051"], "statements": ["Based on the criteria for selection, GSE26051 dataset was chosen for this research, encompassing gene expression profiles of tendon tissues from 23 patients with tendon injuries and 23 healthy tendons."], "basis": "The paper names GSE26051 in GEO (Gene Expression Omnibus) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "assets": ["source:pmid:40858849", "data:geo:GSE26051"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE26051"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T20:00:42Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 11525, "completion_tokens": 1988, "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:40858849", "type": "paper", "label": "pmid:40858849"}, {"id": "source:pmid:40858849", "type": "manuscript", "label": "PMID 40858849 full text"}, {"id": "data:geo:GSE26051", "type": "dataset", "label": "GEO GSE26051"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:40858849", "type": "paper", "label": "pmid:40858849"}, {"id": "source:pmid:40858849", "type": "manuscript", "label": "PMID 40858849 full text"}, {"id": "data:geo:GSE26051", "type": "dataset", "label": "GEO GSE26051"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-40858849", "type": "extraction", "used": ["source:pmid:40858849"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE26051", "type": "accession_resolution", "used": ["data:geo:GSE26051"], "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:40858849", "parent_hash": "sha256:15fa515332cf51ba7d004caea281e6e3e537bd91b72d62530970b08bf8d99a32", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE26051 licence not read", "asset:data:geo:GSE26051 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["train_classifier", "cross_validate", "roc_auc"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["For additional identification of hub genes, three machine learning algorithms (LASSO, RF, and SVM) were employed to examine the hub genes derived from the earlier PPI network."], "order_basis": "analysis_only", "id": "assay:1"}]}