← All .science files
pmid:31487691
TPM2 as a potential predictive biomarker for atherosclerosis.
Ling-Bing Meng · Meng-Jie Shan · Yong Qiu · Ruomei Qi · Ze-Mou Yu · Peng Guo · Chen-Yi Di · Tao Gong
Aging · 2019 doi:10.18632/aging.102231
Paper
complete
Experiment
complete
Data
partial
Analysis
partial
Execution
absent
Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
paper object · 10 fields
authors array · 8 items
claims array · 2 items
[0] object · 6 fields
gaps array · 0 items
experiment object · 8 fields
steps array · 3 items
[0] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 0 items
data object · 3 fields
assets array · 9 items
[0] object · 15 fields
structure object · 4 fields
[1] object · 15 fields
structure object · 15 fields
sample_accessions array · 64 items
[2] object · 15 fields
structure object · 15 fields
sample_accessions array · 68 items
[3] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 15 items
[0] array · 5 items
[1] array · 1 item
[2] array · 5 items
[3] array · 5 items
[4] array · 5 items
[5] array · 5 items
[6] array · 5 items
[7] array · 5 items
[8] array · 1 item
[9] array · 5 items
[10] array · 5 items
[11] array · 5 items
[12] array · 5 items
[13] array · 5 items
[14] array · 5 items
[4] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 13 items
[0] array · 5 items
[1] array · 1 item
[2] array · 5 items
[3] array · 5 items
[4] array · 5 items
[5] array · 5 items
[6] array · 5 items
[7] array · 5 items
[8] array · 1 item
[9] array · 5 items
[10] array · 5 items
[11] array · 5 items
[12] array · 5 items
[5] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 16 items
[0] array · 2 items
[1] array · 3 items
[2] array · 4 items
[3] array · 6 items
[4] array · 6 items
[5] array · 6 items
[6] array · 6 items
[7] array · 6 items
[8] array · 6 items
[9] array · 6 items
[10] array · 6 items
[11] array · 6 items
[12] array · 6 items
[13] array · 6 items
[14] array · 6 items
[15] array · 6 items
[6] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 28 items
[0] array · 2 items
[1] array · 3 items
[2] array · 6 items
[3] array · 5 items
[4] array · 6 items
[5] array · 5 items
[6] array · 6 items
[7] array · 5 items
[8] array · 6 items
[9] array · 5 items
[10] array · 6 items
[11] array · 5 items
[12] array · 6 items
[13] array · 5 items
[14] array · 6 items
[15] array · 5 items
[16] array · 6 items
[17] array · 5 items
[18] array · 6 items
[19] array · 5 items
[20] array · 6 items
[21] array · 5 items
[22] array · 6 items
[23] array · 5 items
[24] array · 6 items
[25] array · 5 items
[26] array · 6 items
[27] array · 5 items
[7] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 10 items
[0] array · 4 items
[1] array · 3 items
[2] array · 4 items
[3] array · 4 items
[4] array · 4 items
[5] array · 4 items
[6] array · 4 items
[7] array · 4 items
[8] array · 4 items
[9] array · 4 items
[8] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 5 items
[0] array · 2 items
[1] array · 2 items
[2] array · 2 items
[3] array · 2 items
[4] array · 2 items
gaps array · 4 items
analysis object · 4 fields
methods array · 5 items
[0] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[1] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[2] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[3] object · 10 fields
dsl_operations array · 3 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[4] object · 10 fields
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
targets array · 0 items
gaps array · 1 item
capability object · 3 fields
requirements array · 1 item
[0] object · 6 fields
assay_families array · 9 items
gaps array · 0 items
readiness object · 8 fields
axes object · 3 fields
method object · 5 fields
required_operations array · 1 item
missing_operations array · 0 items
capability object · 4 fields
data object · 6 fields
accessions array · 2 items
resolved_accessions array · 2 items
statements array · 1 item
can_run object · 3 fields
dsl_operations array · 1 item
assets array · 8 items
steps array · 1 item
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
gaps array · 0 items
review object · 5 fields
machine_critique object · 5 fields
reader object · 5 fields
evidence_check object · 2 fields
usage object · 3 fields
stages array · 1 item
[0] object · 4 fields
gaps array · 3 items
provenance object · 7 fields
entities array · 3 items
activities array · 3 items
[0] object · 4 fields
used array · 3 items
[0] object · 3 fields
[1] object · 3 fields
[2] object · 3 fields
[1] object · 4 fields
agents array · 2 items
lineage object · 4 fields
gaps array · 9 items
assays array · 1 item
[0] object · 11 fields
required_operations array · 1 item
source_hashes object · 1 field
evidence array · 1 item
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31487691", "kind": "science-record", "revision": 8, "content_hash": "sha256:bedca05353b2a38d640c4682cc4854a96254cce004e7b700dcb54407ccbcda70", "created_at": "2026-11-01T15:40:49Z", "updated_at": "2026-11-01T22:00:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "TPM2 as a potential predictive biomarker for atherosclerosis.", "doi": "10.18632/aging.102231", "pmid": "31487691", "authors": ["Ling-Bing Meng", "Meng-Jie Shan", "Yong Qiu", "Ruomei Qi", "Ze-Mou Yu", "Peng Guo", "Chen-Yi Di", "Tao Gong"], "journal": "Aging", "year": 2019, "abstract": "Cardiac-cerebral vascular disease (CCVD), is primarily induced by atherosclerosis, and is a leading cause of mortality. Numerous studies have investigated and attempted to clarify the molecular mechanisms of atherosclerosis; however, its pathogenesis has yet to be completely elucidated. Two expression profiling datasets, GSE43292 and GSE57691, were obtained from the Gene Expression Omnibus (GEO) database. The present study then identified the differentially expressed genes (DEGs), and functional annotation of the DEGs was performed. Finally, an atherosclerosis animal model and neural network prediction model was constructed to verify the relationship between hub gene and atherosclerosis. The results identified a total of 234 DEGs between the normal and atherosclerosis samples. The DEGs were mainly enriched in actin filament, actin binding, smooth muscle cells, and cytokine-cytokine receptor interactions. A total of 13 genes were identified as hub genes. Following verification of animal model, the common DEG, Tropomyosin 2 (TPM2), was found, which were displayed at lower levels in the atherosclerosis models and samples. In summary, DEGs identified in the present study may assist clinicians in understanding the pathogenesis governing the occurrence and development of atherosclerosis, and TPM2 exhibits potential as a promising diagnostic and therapeutic biomarker for atherosclerosis.", "claims": [{"id": "claim-method", "statement": "The Pearson-rho test was executed to compare the expression of hub genes and status of atherosclerosis for the correlation analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31487691", "locator": "sections[33] \"Statistical analysis\" paragraph 2", "quote": "The Pearson-rho test was executed to compare the expression of hub genes and status of atherosclerosis for the correlation analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE43292 dataset contained 32 non-atherosclerotic arterial tissues samples and 32 atherosclerotic arterial tissues samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31487691", "locator": "sections[20] \"Access to public data\" paragraph 2", "quote": "The GSE43292 dataset contained 32 non-atherosclerotic arterial tissues samples and 32 atherosclerotic arterial tissues samples."}], "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:31487691"], "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:GSE43292"], "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:GSE43292"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31487691", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.102231", "sha256": "sha256:803e66a1c33ec33ec6ba71f237a738ff82b0ec849c505c7940b856252dcd9a79", "bytes": 66937, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.18632/aging.102231", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6756910", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"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": "The GSE43292 dataset contained 32 non-atherosclerotic arterial tissues samples and 32 atherosclerotic arterial tissues samples.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The GSE43292 dataset contained 32 non-atherosclerotic arterial tissues samples and 32 atherosclerotic arterial tissues samples.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1060117", "GSM1060118", "GSM1060119", "GSM1060120", "GSM1060121", "GSM1060122", "GSM1060123", "GSM1060124", "GSM1060125", "GSM1060126", "GSM1060127", "GSM1060128", "GSM1060129", "GSM1060130", "GSM1060131", "GSM1060132", "GSM1060133", "GSM1060134", "GSM1060135", "GSM1060136", "GSM1060137", "GSM1060138", "GSM1060139", "GSM1060140", "GSM1060141", "GSM1060142", "GSM1060143", "GSM1060144", "GSM1060145", "GSM1060146", "GSM1060147", "GSM1060148", "GSM1060149", "GSM1060150", "GSM1060151", "GSM1060152", "GSM1060153", "GSM1060154", "GSM1060155", "GSM1060156", "GSM1060157", "GSM1060158", "GSM1060159", "GSM1060160", "GSM1060161", "GSM1060162", "GSM1060163", "GSM1060164", "GSM1060165", "GSM1060166", "GSM1060167", "GSM1060168", "GSM1060169", "GSM1060170", "GSM1060171", "GSM1060172", "GSM1060173", "GSM1060174", "GSM1060175", "GSM1060176", "GSM1060177", "GSM1060178", "GSM1060179", "GSM1060180"], "sample_count": 64, "group_sizes": null, "group_sizes_basis": null, "platform": "6244", "taxon": "Homo sapiens", "title": "Genome-wide expression study of human carotid atheroma", "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:GSE57691", "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=GSE57691", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE57691", "version": null, "note": "The GSE43292 dataset contained 32 non-atherosclerotic arterial tissues samples and 32 atherosclerotic arterial tissues samples.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The GSE43292 dataset contained 32 non-atherosclerotic arterial tissues samples and 32 atherosclerotic arterial tissues samples.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1386783", "GSM1386784", "GSM1386785", "GSM1386786", "GSM1386787", "GSM1386788", "GSM1386789", "GSM1386790", "GSM1386791", "GSM1386792", "GSM1386793", "GSM1386794", "GSM1386795", "GSM1386796", "GSM1386797", "GSM1386798", "GSM1386799", "GSM1386800", "GSM1386801", "GSM1386802", "GSM1386803", "GSM1386804", "GSM1386805", "GSM1386806", "GSM1386807", "GSM1386808", "GSM1386809", "GSM1386810", "GSM1386811", "GSM1386812", "GSM1386813", "GSM1386814", "GSM1386815", "GSM1386816", "GSM1386817", "GSM1386818", "GSM1386819", "GSM1386820", "GSM1386821", "GSM1386822", "GSM1386823", "GSM1386824", "GSM1386825", "GSM1386826", "GSM1386827", "GSM1386828", "GSM1386829", "GSM1386830", "GSM1386831", "GSM1386832", "GSM1386833", "GSM1386834", "GSM1386835", "GSM1386836", "GSM1386837", "GSM1386838", "GSM1386839", "GSM1386840", "GSM1386841", "GSM1386842", "GSM1386843", "GSM1386844", "GSM1386845", "GSM1386846", "GSM1386847", "GSM1386848", "GSM1386849", "GSM1386850"], "sample_count": 68, "group_sizes": null, "group_sizes_basis": null, "platform": "10558", "taxon": "Homo sapiens", "title": "Differential gene expression in human abdominal aortic aneurysm and atherosclerosis", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:31487691:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:e2599c8fd77eaa4124f489a7184ee7eb4ba6f19a86a76a5c2fd2e1f604031f4a", "bytes": 1124, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[6]/table-wrap[1]#t1", "version": null, "note": "Functional enrichment analysis of DEGs in atherosclerosis using GSEA.", "structure": {"pmcid": "PMC6756910", "section_index": 6, "section_title": "Functional annotation of DEGs by GO and KEGG analyses", "row_count": 15, "column_count": 5}, "table": {"label": "Table 1", "caption": "Functional enrichment analysis of DEGs in atherosclerosis using GSEA.", "rows": [["Gene set name", "SIZE", "ES", "NES", "Rank at max"], ["Upregulated"], ["GO_SKELETAL_MUSCLE_CONTRACTION", "29", "0.316", "0.939", "2942"], ["GO_NEGATIVE_REGULATION_OF_SMOOTH_MUSCLE_CONTRACTION", "15", "0.360", "0.902", "3373"], ["GO_ACTIN_FILAMENT_POLYMERIZATION", "20", "0.393", "1.205", "2007"], ["GO_ACTIN_FILAMENT_BUNDLE_ORGANIZATION", "47", "0.302", "1.064", "1726"], ["GO_CYTOSOLIC_CALCIUM_ION_TRANSPORT", "48", "0.435", "1.218", "1988"], ["GO_CYTOSOLIC_PART", "192", "0.256", "1.011", "3378"], ["Downregulated"], ["GO_SMOOTH_MUSCLE_CONTRACTION", "44", "−0.580", "−1.577", "2784"], ["GO_MUSCLE_CONTRACTION", "220", "−0.514", "−1.573", "2897"], ["GO_REGULATION_OF_SMOOTH_MUSCLE_CONTRACTION", "60", "−0.505", "−1.422", "2121"], ["GO_ACTIN_FILAMENT_ORGANIZATION", "158", "−0.308", "−1.195", "2174"], ["GO_CYTOSOLIC_TRANSPORT", "188", "−0.237", "−1.144", "2287"], ["GO_ENDOPLASMIC_RETICULUM_TO_CYTOSOL_TRANSPORT", "21", "−0.347", "−1.104", "27"]], "row_count": 15, "column_count": 5, "numeric_cells": 48, "header_rows": 0, "locator": "section[6]/table-wrap[1]#t1"}}, {"id": "asset:table:pmid:31487691:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:4f46bd0cbb062af71f2251b4e3017e8d1a78eeaa7f714428040901fae9a9232b", "bytes": 1015, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[6]/table-wrap[2]#t2", "version": null, "note": "Pathway enrichment analysis of DEGs in atherosclerosis using GSEA.", "structure": {"pmcid": "PMC6756910", "section_index": 6, "section_title": "Functional annotation of DEGs by GO and KEGG analyses", "row_count": 13, "column_count": 5}, "table": {"label": "Table 2", "caption": "Pathway enrichment analysis of DEGs in atherosclerosis using GSEA.", "rows": [["Gene set name", "SIZE", "ES", "NES", "Rank at max"], ["Upregulated"], ["KEGG_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_ PYLORI_INFECTION", "61", "0.563", "1.525", "3156"], ["KEGG_BASE_EXCISION_REPAIR", "31", "0.459", "1.522", "6082"], ["KEGG_ANTIGEN_PROCESSING_AND_PRESENTATION", "57", "0.653", "1.519", "2554"], ["KEGG_T_CELL_RECEPTOR_SIGNALING_PATHWAY", "101", "0.605", "1.510", "3648"], ["KEGG_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY", "88", "0.702", "1.508", "2235"], ["KEGG_PATHOGENIC_ESCHERICHIA_COLI_INFECTION", "45", "0.499", "1.505", "4454"], ["Downregulated"], ["KEGG_DILATED_CARDIOMYOPATHY", "86", "−0.524", "−1.434", "1865"], ["KEGG_HYPERTROPHIC_CARDIOMYOPATHY_HCM", "80", "−0.499", "−1.407", "2006"], ["KEGG_LONG_TERM_POTENTIATION", "65", "−0.390", "−1.300", "1772"], ["KEGG_ADHERENS_JUNCTION", "72", "−0.425", "−1.272", "2780"]], "row_count": 13, "column_count": 5, "numeric_cells": 40, "header_rows": 0, "locator": "section[6]/table-wrap[2]#t2"}}, {"id": "asset:table:pmid:31487691:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:5ba1e19a30429bec5b1674635b47258ece6017ca91c213b780d992dca68dbe36", "bytes": 1035, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#t3", "version": null, "note": "The correlation and linear regression analysis between atherosclerosis and relevant gene expression.", "structure": {"pmcid": "PMC6756910", "section_index": 10, "section_title": "Association between TPM2 and atherosclerosis by Pearson correlation test and univariate linear regression", "row_count": 16, "column_count": 6}, "table": {"label": "Table 3", "caption": "The correlation and linear regression analysis between atherosclerosis and relevant gene expression.", "rows": [["Gene symbol", "Atherosclerosis"], ["Pearson’s correlation coefficient", "", "Univariate linear regression"], ["ρa", "p-value", "βb", "P-value"], ["TPM2", "‒0.567", "<0.001*", "", "‒0.461", "<0.001*"], ["MYH10", "‒0.512", "<0.001*", "", "‒0.329", "<0.001*"], ["ACTA1", "‒0.503", "<0.001*", "", "‒0.236", "<0.001*"], ["IL1B", "0.406", "0.001*", "", "0.211", "0.001*"], ["ITGAX", "0.518", "<0.001*", "", "0.250", "<0.001*"], ["SELL", "0.504", "<0.001*", "", "0.422", "<0.001*"], ["CCR2", "0.400", "0.001*", "", "0.241", "0.001*"], ["LCP2", "0.576", "<0.001*", "", "0.405", "<0.001*"], ["CXCL8", "0.373", "0.002*", "", "0.149", "0.002*"], ["NLRP3", "0.584", "<0.001*", "", "0.480", "<0.001*"], ["FLNC", "‒0.575", "<0.001*", "", "‒0.430", "<0.001*"], ["CXCL2", "0.358", "0.004*", "", "0.213", "0.004*"], ["FPR2", "0.383", "0.002*", "", "0.206", "0.002*"]], "row_count": 16, "column_count": 6, "numeric_cells": 53, "header_rows": 0, "locator": "section[10]/table-wrap[1]#t3"}}, {"id": "asset:table:pmid:31487691:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:f13cddcb198bdc7838698aba219e894e621264b934415bffd9aad2f09f94b856", "bytes": 1323, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#t4", "version": null, "note": "Correlative parameters’ effect on atherosclerosis based on univariate logistic proportional regression analysis.", "structure": {"pmcid": "PMC6756910", "section_index": 11, "section_title": "An independent risk factor for atherosclerosis based on univariate and multivariate logistic regression: TPM2", "row_count": 28, "column_count": 6}, "table": {"label": "Table 4", "caption": "Correlative parameters’ effect on atherosclerosis based on univariate logistic proportional regression analysis.", "rows": [["Parameters", "AS"], ["OR", "95% CI", "P"], ["TPM2", "Low", "29", "1", "", "<0.001*"], ["", "High", "35", "0.090", "0.028–0.293"], ["MYH10", "Low", "26", "1", "", "0.001*"], ["", "High", "38", "0.138", "0.044–0.433"], ["ACTC1", "Low", "35", "1", "", "<0.001*"], ["", "High", "29", "0.127", "0.041–0.391"], ["IL1B", "Low", "29", "1", "", "0.026*"], ["", "High", "35", "3.215", "1.150–8.987"], ["ITGAX", "Low", "27", "1", "", "<0.001*"], ["", "High", "37", "8.273", "2.622–26.100"], ["SELL", "Low", "30", "1", "", "<0.001*"], ["", "High", "34", "13.000", "3.935–42.950"], ["CCR2", "Low", "33", "1", "", "0.007*"], ["", "High", "31", "4.200", "1.478–11.936"], ["LCP2", "Low", "24", "1", "", "0.001*"], ["", "High", "40", "7.892", "2.409–25.857"], ["CXCL8", "Low", "33", "1", "", "0.026*"], ["", "High", "31", "3.182", "1.145–8.841"], ["NLRP3", "Low", "29", "1", "", "<0.001"], ["", "High", "35", "11.074", "3.418–35.878"], ["FLNC", "Low", "35", "1", "", "<0.001*"], ["", "High", "29", "0.062", "0.018–0.214"], ["CXCL2", "Low", "34", "1", "", "0.048*"], ["", "High", "30", "2.790", "1.011–7.698"], ["FPR2", "Low", "39", "1", "", "0.006*"], ["", "High", "25", "4.592", "1.542–13.671"]], "row_count": 28, "column_count": 6, "numeric_cells": 80, "header_rows": 0, "locator": "section[11]/table-wrap[1]#t4"}}, {"id": "asset:table:pmid:31487691:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:8ecb3e948cdd30313d26a0fbae1415daf498ca362b3c6694cd0a7ea51c94bd6d", "bytes": 621, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[2]#t5", "version": null, "note": "Correlative genes’ effect on AS based on multiple logistic proportional regression analysis.", "structure": {"pmcid": "PMC6756910", "section_index": 11, "section_title": "An independent risk factor for atherosclerosis based on univariate and multivariate logistic regression: TPM2", "row_count": 10, "column_count": 4}, "table": {"label": "Table 5", "caption": "Correlative genes’ effect on AS based on multiple logistic proportional regression analysis.", "rows": [["Genes", "", "AS", ""], ["OR", "95% CI", "P"], ["TPM2", "0.140", "0.020–0.988", "0.049*"], ["IL1B", "1.105", "0.181–6.730", "0.914"], ["CCR2", "0.819", "0.152–4.419", "0.817"], ["CXCL8", "1.142", "0.125–10.477", "0.906"], ["CXCL2", "0.486", "0.046–5.171", "0.550"], ["FPR2", "2.658", "0.467–15.111", "0.270"], ["NLRP3", "6.032", "0.880–41.363", "0.067"], ["MYH10", "2.611", "0.222–30.678", "0.445"]], "row_count": 10, "column_count": 4, "numeric_cells": 26, "header_rows": 0, "locator": "section[11]/table-wrap[2]#t5"}}, {"id": "asset:table:pmid:31487691:6", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:36bdc3aa3bafca043204e9a0a91e1de10e2bcb68b47a60a075418bee9a823849", "bytes": 381, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[30]/table-wrap[1]#t6", "version": null, "note": "Primers and their sequences for PCR analysis.", "structure": {"pmcid": "PMC6756910", "section_index": 30, "section_title": "RT-qPCR assay", "row_count": 5, "column_count": 2}, "table": {"label": "Table 6", "caption": "Primers and their sequences for PCR analysis.", "rows": [["Primer", "Sequence (5′–3′)"], ["β-actin-hF", "CGCAGAAACGAGACGAGATTG"], ["β-actin-hR", "GATGCTCGCTCCAACGACTG"], ["TPM2-hF", "TCCACCAAGGAGGACAAATACG"], ["TPM2-hR", "GTTGTTGAGTTCCAGCAGGGTC"]], "row_count": 5, "column_count": 2, "numeric_cells": 1, "header_rows": 0, "locator": "section[30]/table-wrap[1]#t6"}}], "gaps": ["asset:data:geo:GSE43292 not downloaded", "asset:data:geo:GSE43292 licence not read", "asset:data:geo:GSE57691 not downloaded", "asset:data:geo:GSE57691 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "regression_modelling", "specific": "ols", "label": "Regression modelling", "dsl_operations": ["ols_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 0.8, "band": "high", "quote": "linear regression"}}, {"id": "method-2", "family": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 0.8, "band": "high", "quote": "logistic regression"}}, {"id": "method-3", "family": "clustering", "specific": "hierarchical", "label": "Clustering", "dsl_operations": ["hierarchical_cluster"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "Hierarchical clustering"}}, {"id": "method-4", "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": 0.8, "band": "high", "quote": "protein-protein interaction"}}, {"id": "method-5", "family": null, "specific": null, "label": "Pearson-rho test", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The Pearson-rho test was executed to compare the expression of hub genes and status of atherosclerosis for the correlation analysis."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "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": ["ols_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ols."}, "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": ["GSE43292", "GSE57691"], "resolved_accessions": ["GSE43292", "GSE57691"], "statements": ["The GSE43292 dataset contained 32 non-atherosclerotic arterial tissues samples and 32 atherosclerotic arterial tissues samples."], "basis": "The paper names GSE43292, GSE57691 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": ["ols_fit"], "assets": ["source:pmid:31487691", "data:geo:GSE43292", "asset:table:pmid:31487691:1", "asset:table:pmid:31487691:2", "asset:table:pmid:31487691:3", "asset:table:pmid:31487691:4", "asset:table:pmid:31487691:5", "asset:table:pmid:31487691:6"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE43292"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:16:09Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 3, "usage": {"prompt_tokens": 49177, "completion_tokens": 1399, "cached_tokens": 768}}, "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:31487691", "type": "paper", "label": "pmid:31487691"}, {"id": "source:pmid:31487691", "type": "manuscript", "label": "PMID 31487691 full text"}, {"id": "data:geo:GSE43292", "type": "dataset", "label": "GEO GSE43292"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:31487691", "type": "paper", "label": "pmid:31487691"}, {"id": "source:pmid:31487691", "type": "manuscript", "label": "PMID 31487691 full text"}, {"id": "data:geo:GSE43292", "type": "dataset", "label": "GEO GSE43292"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-31487691", "type": "extraction", "used": ["source:pmid:31487691"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE43292", "type": "accession_resolution", "used": ["data:geo:GSE43292"], "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:31487691", "parent_hash": "sha256:cd3940fc8b596c5f3dfbcf59d1d7d683796eca826d1c7560ff257f2361a3d5bd", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE43292 licence not read", "asset:data:geo:GSE43292 not downloaded", "asset:data:geo:GSE57691 licence not read", "asset:data:geo:GSE57691 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["ols_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["linear regression"], "order_basis": "analysis_only", "id": "assay:1"}]}