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pmid:33052139

Weighted gene coexpression network analysis identifies the key role associated with acute coronary syndrome.

Yong Wang · Liu Miao · Lin Tao · Jian-Hong Chen · Chuan-Meng Zhu · Ye Li · Bin Qi · Fei Liao · Rong-Shan Li

Aging · 2020 doi:10.18632/aging.103859

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

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title
Weighted gene coexpression network analysis identifies the key role associated with acute coronary syndrome.
doi
10.18632/aging.103859
pmid
33052139
authors array · 9 items
[0]
Yong Wang
[1]
Liu Miao
[2]
Lin Tao
[3]
Jian-Hong Chen
[4]
Chuan-Meng Zhu
[5]
Ye Li
[6]
Bin Qi
[7]
Fei Liao
[8]
Rong-Shan Li
journal
Aging
year
2020
abstract
The present study sought to identify potential hub genes and pathways of acute coronary syndrome (ACS). We downloaded the dataset (GSE56045) from the Gene Expression Omnibus (GEO) database and analyzed weighted gene coexpression networks (WGCNA). Gene Ontology annotation, Disease Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software. The protein-protein interaction (PPI) network was constructed using Cytoscape, and the Molecular Complex Detection app was employed to identify significant modules and hub genes. The hub genes were then validated in other microarrays and patients by RT-PCR. Two modules were identified and associated with coronary artery disease (CAD) and included 219 genes. After function and PPI analyses, 24 genes were identified to be potentially associated with CAD. Linear correlation was performed to calculate the relationship between the gene expression levels and coronary artery calcification score and found that CCR7 (R = -0.081, P = 0.0065), CD2 (R = -0.075, P = 0.0012), CXCR5 (R = -0.065, P = 0.029) and IL7R (R = -0.06, P = 0.043) should be validated in other dataset. By comparing the gene expression levels in different groups in GSE23561, GSE34822, GSE59867, GSE60993 and GSE129935, only two genes (CCR7 and CXCR5) showed significance. The nomogram showed that CXCR5 showed the risk of ACS. Further analysis in chest patients found CXCR5 played a key role resulting in ACS. Our WGCNA analysis identified CXCR5 as a risk factor for ACS, and the potential pathogenesis may be associated with immune inflammation.
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First, we analyzed the relationship between the expression level of these 24 genes and the coronary artery calcification score by linear correlation in GSE56045.
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First, we analyzed the relationship between the expression level of these 24 genes and the coronary artery calcification score by linear correlation in GSE56045.
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We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
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sections[11] "Microarray data" paragraph 2
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We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
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We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
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GSM1352234
[233]
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[234]
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[235]
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[236]
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[237]
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[238]
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[239]
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[240]
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[241]
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[242]
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[243]
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[244]
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[245]
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[246]
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[247]
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[248]
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[249]
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[250]
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[251]
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[252]
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[253]
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[254]
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[255]
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[256]
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[257]
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[258]
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[259]
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[260]
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[261]
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[262]
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[263]
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[264]
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[265]
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[266]
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[267]
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[268]
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[269]
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[270]
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[271]
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[272]
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[273]
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[274]
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[275]
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[276]
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[277]
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[278]
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[279]
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[280]
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[281]
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[282]
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[283]
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[284]
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[285]
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[286]
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[287]
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[288]
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[289]
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[290]
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[291]
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[292]
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[293]
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[294]
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[295]
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[296]
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[297]
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[298]
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[299]
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[300]
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[301]
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[302]
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[303]
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[304]
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[305]
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[306]
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[307]
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[308]
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[309]
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[310]
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[311]
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[312]
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[313]
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[314]
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[315]
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[316]
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[317]
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[318]
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[319]
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[320]
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[321]
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[322]
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[323]
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[324]
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[325]
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[326]
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[327]
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[328]
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[329]
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[330]
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[331]
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[332]
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[333]
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[334]
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[335]
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[336]
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[337]
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[338]
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[339]
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[340]
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[341]
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[342]
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[343]
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[344]
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[345]
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[346]
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[347]
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[348]
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[349]
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[350]
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[351]
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[352]
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[354]
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[355]
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[356]
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[357]
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[358]
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[359]
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[360]
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[361]
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[362]
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[363]
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[364]
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[365]
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[366]
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[367]
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[368]
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[369]
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[370]
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[371]
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[372]
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[373]
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[374]
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[375]
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[376]
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[377]
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[378]
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[379]
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[380]
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[381]
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[382]
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[383]
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[384]
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[385]
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[386]
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[387]
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[388]
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[389]
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[390]
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[391]
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[392]
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[393]
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[394]
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[395]
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[396]
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[397]
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[398]
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[399]
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[400]
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[401]
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[402]
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[403]
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[404]
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[405]
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[406]
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[407]
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[408]
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[409]
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[410]
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[411]
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[412]
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[413]
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[414]
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[415]
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[416]
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[417]
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[418]
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[419]
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[420]
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[421]
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[422]
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[423]
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[424]
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[425]
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[426]
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[427]
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[428]
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[429]
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[430]
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[431]
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[432]
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[433]
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[434]
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[435]
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[436]
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[437]
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[438]
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[439]
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[440]
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[441]
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[444]
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[445]
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[448]
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[449]
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[450]
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[451]
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[452]
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[453]
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[454]
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[455]
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[456]
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[457]
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[458]
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[459]
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[460]
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[461]
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[462]
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[463]
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[464]
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[465]
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[466]
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[467]
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[468]
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[469]
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[470]
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[471]
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[472]
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[473]
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[474]
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[475]
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[476]
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[477]
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[478]
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[479]
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[480]
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[481]
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[482]
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[483]
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[484]
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[485]
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[486]
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[487]
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[488]
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[489]
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[490]
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[491]
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[492]
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[493]
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[494]
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[495]
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[496]
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[497]
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[498]
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[499]
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[500]
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[501]
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[502]
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[503]
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[504]
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[505]
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[506]
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[507]
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[508]
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[509]
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[510]
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[511]
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[512]
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[513]
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[514]
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[515]
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[516]
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[517]
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[518]
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[519]
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[520]
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[521]
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[522]
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[523]
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[524]
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[525]
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[526]
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[527]
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[528]
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[529]
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[530]
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[531]
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[532]
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[533]
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[534]
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[535]
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[536]
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[537]
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[538]
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[539]
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[540]
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[541]
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[542]
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[543]
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[544]
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[545]
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[546]
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[547]
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[548]
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[549]
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[550]
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[551]
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[552]
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[553]
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[554]
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[555]
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[556]
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[557]
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[558]
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[559]
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[560]
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[561]
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[562]
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[563]
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[564]
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[565]
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[566]
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[567]
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[568]
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[569]
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[570]
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[571]
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[572]
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[573]
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[574]
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[575]
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[576]
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[577]
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[578]
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[579]
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[580]
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[581]
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[582]
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[583]
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[584]
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[585]
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[586]
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[587]
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[588]
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[589]
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[590]
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[591]
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[592]
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[593]
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[594]
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[595]
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[596]
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[597]
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[598]
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[599]
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[600]
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[601]
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[602]
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[603]
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[604]
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[605]
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[606]
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[607]
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[608]
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[609]
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[610]
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[611]
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[612]
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[613]
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[614]
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[615]
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[616]
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[617]
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[618]
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[619]
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[620]
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[621]
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[622]
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[623]
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[624]
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[625]
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[626]
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[627]
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[628]
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[629]
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[630]
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[631]
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[632]
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[633]
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[636]
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[639]
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[640]
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[641]
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[642]
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[643]
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[644]
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[645]
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[646]
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[647]
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[648]
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[655]
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[656]
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[657]
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[658]
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[659]
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[660]
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[661]
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[662]
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[663]
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[664]
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[665]
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[666]
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[667]
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[668]
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[669]
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[670]
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[671]
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[672]
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[673]
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[674]
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[675]
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[677]
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[678]
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[679]
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[680]
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[682]
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[683]
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[684]
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[685]
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[688]
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[689]
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[690]
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[691]
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[699]
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[700]
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[701]
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[703]
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[705]
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[706]
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[707]
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[709]
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[710]
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[711]
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[712]
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[713]
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[714]
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[715]
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[716]
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[717]
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[718]
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[720]
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[722]
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[723]
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[724]
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[725]
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[726]
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[727]
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[728]
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[729]
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[730]
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[731]
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[732]
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[733]
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[734]
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[735]
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[736]
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[737]
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[738]
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[739]
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[740]
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[744]
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[745]
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[750]
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[751]
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[754]
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[755]
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[756]
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[757]
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[758]
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[759]
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[760]
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[761]
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[762]
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[763]
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[764]
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[765]
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[766]
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[767]
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[768]
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[769]
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[770]
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[771]
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[772]
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[773]
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[774]
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[775]
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[776]
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[777]
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[779]
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[780]
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[781]
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[782]
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[783]
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[784]
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[785]
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[786]
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[787]
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[788]
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[789]
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[790]
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[791]
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[792]
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[793]
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[794]
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[795]
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[796]
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[797]
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[798]
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[799]
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[800]
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[801]
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[802]
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[803]
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[804]
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[805]
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[806]
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[807]
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[808]
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[809]
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[810]
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[811]
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[812]
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[813]
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[814]
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[815]
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[816]
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[817]
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[818]
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[819]
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[820]
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[821]
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[822]
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[823]
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[824]
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[825]
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[826]
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[827]
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[828]
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[829]
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[830]
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[831]
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[832]
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[833]
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[834]
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[835]
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[836]
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[837]
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[838]
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[839]
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[840]
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[841]
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[842]
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[843]
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[844]
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[845]
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[846]
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[847]
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[848]
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[849]
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[850]
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[851]
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[852]
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[853]
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[854]
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[855]
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[856]
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[857]
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[858]
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[859]
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[860]
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[861]
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[862]
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[863]
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[864]
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[865]
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[866]
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[867]
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[868]
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[869]
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[870]
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[871]
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[872]
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[873]
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[874]
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[875]
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[876]
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[877]
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[878]
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[879]
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[880]
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[881]
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[882]
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[883]
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[884]
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[885]
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[886]
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[887]
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[888]
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[889]
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[890]
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[891]
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[892]
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[893]
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[894]
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[895]
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[896]
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[897]
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[898]
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[899]
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[900]
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[901]
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[902]
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[903]
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[904]
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[905]
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[906]
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[907]
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[908]
GSM1352910
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sample_count
1202
group_sizes
null
group_sizes_basis
null
platform
10558
taxon
Homo sapiens
title
Transcriptomics and methylomics of human monocytes [transcriptome]
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 15 fields
id
data:geo:GSE59867
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=GSE59867
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE59867
version
null
note
We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
access_statement_kind
repository_route_statement
sample_accessions array · 436 items
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[324]
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[325]
GSM1448660
[326]
GSM1448661
[327]
GSM1448662
[328]
GSM1448663
[329]
GSM1448664
[330]
GSM1448665
[331]
GSM1448666
[332]
GSM1448667
[333]
GSM1448668
[334]
GSM1448669
[335]
GSM1448670
[336]
GSM1448671
[337]
GSM1448672
[338]
GSM1448673
[339]
GSM1448674
[340]
GSM1448675
[341]
GSM1448676
[342]
GSM1448677
[343]
GSM1448678
[344]
GSM1448679
[345]
GSM1448680
[346]
GSM1448681
[347]
GSM1448682
[348]
GSM1448683
[349]
GSM1448684
[350]
GSM1448685
[351]
GSM1448686
[352]
GSM1448687
[353]
GSM1448688
[354]
GSM1448689
[355]
GSM1448690
[356]
GSM1448691
[357]
GSM1448692
[358]
GSM1448693
[359]
GSM1448694
[360]
GSM1448695
[361]
GSM1448696
[362]
GSM1448697
[363]
GSM1448698
[364]
GSM1448699
[365]
GSM1448700
[366]
GSM1448701
[367]
GSM1448702
[368]
GSM1448703
[369]
GSM1448704
[370]
GSM1448705
[371]
GSM1448706
[372]
GSM1448707
[373]
GSM1448708
[374]
GSM1448709
[375]
GSM1448710
[376]
GSM1448711
[377]
GSM1448712
[378]
GSM1448713
[379]
GSM1448714
[380]
GSM1448715
[381]
GSM1448716
[382]
GSM1448717
[383]
GSM1448718
[384]
GSM1448719
[385]
GSM1448720
[386]
GSM1448721
[387]
GSM1448722
[388]
GSM1448723
[389]
GSM1448724
[390]
GSM1620759
[391]
GSM1620760
[392]
GSM1620761
[393]
GSM1620762
[394]
GSM1620763
[395]
GSM1620764
[396]
GSM1620765
[397]
GSM1620766
[398]
GSM1620767
[399]
GSM1620768
[400]
GSM1620769
[401]
GSM1620770
[402]
GSM1620771
[403]
GSM1620772
[404]
GSM1620773
[405]
GSM1620774
[406]
GSM1620775
[407]
GSM1620776
[408]
GSM1620777
[409]
GSM1620778
[410]
GSM1620779
[411]
GSM1620780
[412]
GSM1620781
[413]
GSM1620782
[414]
GSM1620783
[415]
GSM1620784
[416]
GSM1620785
[417]
GSM1620786
[418]
GSM1620787
[419]
GSM1620788
[420]
GSM1620789
[421]
GSM1620790
[422]
GSM1620791
[423]
GSM1620792
[424]
GSM1620793
[425]
GSM1620794
[426]
GSM1620795
[427]
GSM1620796
[428]
GSM1620797
[429]
GSM1620798
[430]
GSM1620799
[431]
GSM1620800
[432]
GSM1620801
[433]
GSM1620802
[434]
GSM1620803
[435]
GSM1620804
sample_count
436
group_sizes
null
group_sizes_basis
null
platform
6244
taxon
Homo sapiens
title
Gene expression profiling reveals potential prognostic biomarkers associated with the progression of heart failure
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[6] object · 15 fields
id
data:geo:GSE60993
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=GSE60993
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE60993
version
null
note
We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
access_statement_kind
repository_route_statement
sample_accessions array · 33 items
[0]
GSM1495313
[1]
GSM1495314
[2]
GSM1495315
[3]
GSM1495316
[4]
GSM1495317
[5]
GSM1495318
[6]
GSM1495319
[7]
GSM1495320
[8]
GSM1495321
[9]
GSM1495322
[10]
GSM1495323
[11]
GSM1495324
[12]
GSM1495325
[13]
GSM1495326
[14]
GSM1495327
[15]
GSM1495328
[16]
GSM1495329
[17]
GSM1495330
[18]
GSM1495331
[19]
GSM1495332
[20]
GSM1495333
[21]
GSM1495334
[22]
GSM1495335
[23]
GSM1495336
[24]
GSM1495337
[25]
GSM1495338
[26]
GSM1495339
[27]
GSM1495340
[28]
GSM1495341
[29]
GSM1495342
[30]
GSM1495343
[31]
GSM1495344
[32]
GSM1495345
sample_count
33
group_sizes
null
group_sizes_basis
null
platform
6884
taxon
Homo sapiens
title
Assessment and Diagnostic Relevance of Novel Serum Biomarkers for Early Decision of ST-elevation Myocardial Infarction
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[7] object · 16 fields
id
asset:table:pmid:33052139:1
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:4f03c09541ec5a80ce8eaa425a7d4030251d52dad532aef2fbc8d2a0c171d329
bytes
2600
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[8]/table-wrap[1]#t1
version
null
note
Comparison of demographic, lifestyle characteristics and serum lipid levels among different groups.
structure object · 5 fields
pmcid
PMC7732301
section_index
8
section_title
Subject validation
row_count
27
column_count
6
table object · 8 fields
label
Table 1
caption
Comparison of demographic, lifestyle characteristics and serum lipid levels among different groups.
rows array · 27 items
[0] array · 6 items
[0]
Parameter
[1]
Control
[2]
CAD
[3]
UA
[4]
NSTEMI
[5]
STEMI
[1] array · 6 items
[0]
Number
[1]
312
[2]
320
[3]
304
[4]
290
[5]
302
[2] array · 6 items
[0]
Male/female
[1]
94/220
[2]
89/231
[3]
92/210
[4]
84/202
[5]
98/202
[3] array · 6 items
[0]
Age (years)1
[1]
55.32±8.31
[2]
54.16±9.05
[3]
55.59±8.54
[4]
56.43±9.83
[5]
55.94±9.17
[4] array · 6 items
[0]
Height (cm)
[1]
166.24±6.82
[2]
168.59±7.29
[3]
167.55±7.28
[4]
166.52±6.94
[5]
167.23±9.13
[5] array · 6 items
[0]
Weight (kg)
[1]
52.46±6.84
[2]
54.74±10.82
[3]
57.63±9.11a
[4]
57.92±8.77a
[5]
57.52±9.23a
[6] array · 6 items
[0]
Body mass index (kg/m2)
[1]
29.29±5.13
[2]
30.44±6.47a
[3]
30.67±7.12a
[4]
30.79±6.74a
[5]
30.77±6.09a
[7] array · 6 items
[0]
Waist circumference (cm)
[1]
74.49±6.74
[2]
73.55±9.48
[3]
76.03±8.15
[4]
76.24±7.17
[5]
76.15±6.27
[8] array · 6 items
[0]
Smoking status [n (%)]
[1]
81(26.0)
[2]
114(35.6) a
[3]
142(46.7) a
[4]
138(47.6) a
[5]
144(47.6) a
[9] array · 6 items
[0]
Alcohol consumption [n (%)]
[1]
75(24.0)
[2]
84(26.2)
[3]
70(23.0)
[4]
81(27.9) a
[5]
71(23.5)
[10] array · 6 items
[0]
SBP (mmHg)
[1]
124.14±17.14
[2]
129.21±21.11a
[3]
147.15±23.96c
[4]
139.47±22.14b
[5]
103.45±17.16c
[11] array · 6 items
[0]
DBP (mmHg)
[1]
80.52±11.16
[2]
81.33±11.25
[3]
88.54±14.23a
[4]
84.43±11.21
[5]
68.54±12.15c
[12] array · 6 items
[0]
PP (mmHg)
[1]
49.64±14.13
[2]
51.42±13.59
[3]
51.66±15.24
[4]
50.84±15.22
[5]
50.22±14.21
[13] array · 6 items
[0]
Glucose (mmol/L)
[1]
5.91±1.83
[2]
6.13±2.22
[3]
7.79±2.43b
[4]
8.46±2.79c
[5]
8.69±2.78c
[14] array · 6 items
[0]
TC (mmol/L)
[1]
4.93±1.21
[2]
5.21±1.17a
[3]
5.63±1.12a
[4]
5.99±1.18a
[5]
5.83±1.43a
[15] array · 6 items
[0]
TG (mmol/L)2
[1]
1.49(0.51)
[2]
1.53(1.22)
[3]
1.52(1.21)
[4]
1.44(1.32)
[5]
1.51(1.26)
[16] array · 6 items
[0]
HDL-C (mmol/L)
[1]
1.52±0.44
[2]
1.32±0.26a
[3]
1.35±0.34a
[4]
1.44±0.28a
[5]
1.48±0.32
[17] array · 6 items
[0]
LDL-C (mmol/L)
[1]
2.86±0.81
[2]
3.23±0.74a
[3]
3.98±0.79a
[4]
3.79±0.88a
[5]
3.92±0.84a
[18] array · 6 items
[0]
ApoA1 (g/L)
[1]
1.24±0.24
[2]
1.17±0.22
[3]
1.18±0.26
[4]
1.18±0.26
[5]
1.14±0.28
[19] array · 6 items
[0]
ApoB (g/L)
[1]
0.84±0.19
[2]
0.82±0.32
[3]
0.81±0.31
[4]
0.94±0.31
[5]
0.88±0.28
[20] array · 6 items
[0]
ApoA1/ApoB
[1]
1.67±0.50
[2]
1.66±0.57
[3]
1.64±0.58
[4]
1.65±0.61
[5]
1.67±0.54
[21] array · 6 items
[0]
Heart rate (beats/minutes)
[1]
72.41±10.19
[2]
72.33±10.32
[3]
76.28±10.61a
[4]
76.43±9.31a
[5]
79.76±10.14a
[22] array · 6 items
[0]
Creatinine, (μmol/L)
[1]
72.34±12.22
[2]
71.36±11.34
[3]
74.53±11.62
[4]
76.55±10.23
[5]
76.58±12.74
[23] array · 6 items
[0]
Uric acid, (μmol/L)
[1]
283.83±76.19
[2]
286.89±74.32
[3]
279.88±81.31
[4]
285.91±81.31
[5]
283.86±75.28
[24] array · 6 items
[0]
Troponin T, (μg/L)
[1]
0.01±0.02
[2]
0.02±0.02
[3]
0.02±0.01
[4]
2.74±3.93c
[5]
2.86±6.28c
[25] array · 6 items
[0]
CK, (U/L)
[1]
88.84±45.28
[2]
87.84±48.31
[3]
91.88±50.33
[4]
1111.92±683.31c
[5]
1124.88±783.28c
[26] array · 6 items
[0]
CKMB, (U/L)
[1]
12.44±3.63
[2]
13.11±2.78
[3]
13.22±3.32
[4]
129.88±61.45c
[5]
132.76±59.17c
locator
section[8]/table-wrap[1]#t1
gaps array · 12 items
[0]
asset:data:geo:GSE129935 not downloaded
[1]
asset:data:geo:GSE129935 licence not read
[2]
asset:data:geo:GSE23561 not downloaded
[3]
asset:data:geo:GSE23561 licence not read
[4]
asset:data:geo:GSE34822 not downloaded
[5]
asset:data:geo:GSE34822 licence not read
[6]
asset:data:geo:GSE56045 not downloaded
[7]
asset:data:geo:GSE56045 licence not read
[8]
asset:data:geo:GSE59867 not downloaded
[9]
asset:data:geo:GSE59867 licence not read
[10]
asset:data:geo:GSE60993 not downloaded
[11]
asset:data:geo:GSE60993 licence not read
analysis object · 4 fields
state
partial
methods array · 5 items
[0] object · 10 fields
id
method-1
family
group_comparison
specific
wilcoxon
label
Group comparison
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
band
high
quote
Wilcoxon
[1] object · 10 fields
id
method-2
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
protein-protein interaction
[2] object · 10 fields
id
method-3
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
pathway enrichment
[3] object · 10 fields
id
method-4
family
contingency_analysis
specific
chi_square
label
Categorical (contingency table) analysis
dsl_operations array · 1 item
[0]
chi_square_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
categorical_cross_tabulation
evidence object · 3 fields
score
0.8
band
high
quote
Chi-square
[4] object · 10 fields
id
method-5
family
null
specific
null
label
Linear correlation
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
First, we analyzed the relationship between the expression level of these 24 genes and the coronary artery calcification score by linear correlation in GSE56045.
targets array · 0 items
gaps array · 2 items
[0]
method.reader_named_unmapped
[1]
method.group_comparison_wilcoxon
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
false
required_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon.
capability object · 4 fields
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 object · 6 fields
tier
R1
reachable
true
accessions array · 6 items
[0]
GSE56045
[1]
GSE23561
[2]
GSE34822
[3]
GSE59867
[4]
GSE60993
[5]
GSE129935
resolved_accessions array · 6 items
[0]
GSE56045
[1]
GSE23561
[2]
GSE34822
[3]
GSE59867
[4]
GSE60993
[5]
GSE129935
statements array · 1 item
[0]
We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.
basis
The paper names GSE56045, GSE23561, GSE34822, GSE59867, GSE60993, GSE129935 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 0 items
assets array · 3 items
[0]
source:pmid:33052139
[1]
data:geo:GSE129935
[2]
asset:table:pmid:33052139:1
steps array · 0 items
must_build object · 5 fields
dsl_operations array · 1 item
[0] object · 3 fields
operation
group_comparison_wilcoxon
priority
null
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE129935
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:23:23Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
3
usage object · 3 fields
prompt_tokens
30399
completion_tokens
2333
cached_tokens
784
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:33052139
type
paper
label
pmid:33052139
[1] object · 3 fields
id
source:pmid:33052139
type
manuscript
label
PMID 33052139 full text
[2] object · 3 fields
id
data:geo:GSE129935
type
dataset
label
GEO GSE129935
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:33052139
type
paper
label
pmid:33052139
[1] object · 3 fields
id
source:pmid:33052139
type
manuscript
label
PMID 33052139 full text
[2] object · 3 fields
id
data:geo:GSE129935
type
dataset
label
GEO GSE129935
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-33052139
type
extraction
used array · 1 item
[0]
source:pmid:33052139
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE129935
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE129935
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
[1] object · 3 fields
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 object · 4 fields
parent_id
pmid:33052139
parent_hash
sha256:e59475fb228aa1f6d29a9c46a60b8c0003d8217f0b049b144c5573ddfdf70b47
fork_of
null
gaps array · 19 items
[0]
asset:data:geo:GSE129935 licence not read
[1]
asset:data:geo:GSE129935 not downloaded
[2]
asset:data:geo:GSE23561 licence not read
[3]
asset:data:geo:GSE23561 not downloaded
[4]
asset:data:geo:GSE34822 licence not read
[5]
asset:data:geo:GSE34822 not downloaded
[6]
asset:data:geo:GSE56045 licence not read
[7]
asset:data:geo:GSE56045 not downloaded
[8]
asset:data:geo:GSE59867 licence not read
[9]
asset:data:geo:GSE59867 not downloaded
[10]
asset:data:geo:GSE60993 licence not read
[11]
asset:data:geo:GSE60993 not downloaded
[12]
execution.not_run
[13]
method.group_comparison_wilcoxon
[14]
method.reader_named_unmapped
[15]
review.human_critique
[16]
review.independent_reader
[17]
review.machine_critique
[18]
step:run_analysis blocked on method:group_comparison_wilcoxon
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evidence array · 2 items
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MATERIALS AND METHODS RT–qPCR and statistical analysis The procedures of b
[1]
isolation, reverse transcription cDNA and RT–qPCR are the same as those in our previous studie
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paper_text_order:1727
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33052139", "kind": "science-record", "revision": 8, "content_hash": "sha256:ddac97a272989b5d2ef92179a1354ab331f43d3fd91a636e16b107e66dfb5a55", "created_at": "2026-11-01T15:41:13Z", "updated_at": "2026-11-01T22:02:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Weighted gene coexpression network analysis identifies the key role associated with acute coronary syndrome.", "doi": "10.18632/aging.103859", "pmid": "33052139", "authors": ["Yong Wang", "Liu Miao", "Lin Tao", "Jian-Hong Chen", "Chuan-Meng Zhu", "Ye Li", "Bin Qi", "Fei Liao", "Rong-Shan Li"], "journal": "Aging", "year": 2020, "abstract": "The present study sought to identify potential hub genes and pathways of acute coronary syndrome (ACS). We downloaded the dataset (GSE56045) from the Gene Expression Omnibus (GEO) database and analyzed weighted gene coexpression networks (WGCNA). Gene Ontology annotation, Disease Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software. The protein-protein interaction (PPI) network was constructed using Cytoscape, and the Molecular Complex Detection app was employed to identify significant modules and hub genes. The hub genes were then validated in other microarrays and patients by RT-PCR. Two modules were identified and associated with coronary artery disease (CAD) and included 219 genes. After function and PPI analyses, 24 genes were identified to be potentially associated with CAD. Linear correlation was performed to calculate the relationship between the gene expression levels and coronary artery calcification score and found that CCR7 (R = -0.081, P = 0.0065), CD2 (R = -0.075, P = 0.0012), CXCR5 (R = -0.065, P = 0.029) and IL7R (R = -0.06, P = 0.043) should be validated in other dataset. By comparing the gene expression levels in different groups in GSE23561, GSE34822, GSE59867, GSE60993 and GSE129935, only two genes (CCR7 and CXCR5) showed significance. The nomogram showed that CXCR5 showed the risk of ACS. Further analysis in chest patients found CXCR5 played a key role resulting in ACS. Our WGCNA analysis identified CXCR5 as a risk factor for ACS, and the potential pathogenesis may be associated with immune inflammation.", "claims": [{"id": "claim-method", "statement": "First, we analyzed the relationship between the expression level of these 24 genes and the coronary artery calcification score by linear correlation in GSE56045.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33052139", "locator": "sections[7] \"Dataset validation\" paragraph 2", "quote": "First, we analyzed the relationship between the expression level of these 24 genes and the coronary artery calcification score by linear correlation in GSE56045."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. 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GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "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:33052139"], "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:GSE129935"], "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:group_comparison_wilcoxon", "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:GSE129935"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33052139", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.103859", "sha256": "sha256:76a402c7d1e26548d6dce2148953719857160a198fb8eb4d42dbf4f6ed879db8", "bytes": 38333, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.18632/aging.103859", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7732301", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE129935", "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=GSE129935", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE129935", "version": null, "note": "We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). 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"GSM1352268", "GSM1352269", "GSM1352270", "GSM1352271", "GSM1352272", "GSM1352273", "GSM1352274", "GSM1352275", "GSM1352276", "GSM1352277", "GSM1352278", "GSM1352279", "GSM1352280", "GSM1352281", "GSM1352282", "GSM1352283", "GSM1352284", "GSM1352285", "GSM1352286", "GSM1352287", "GSM1352288", "GSM1352289", "GSM1352290", "GSM1352291", "GSM1352292", "GSM1352293", "GSM1352294", "GSM1352295", "GSM1352296", "GSM1352297", "GSM1352298", "GSM1352299", "GSM1352300", "GSM1352301", "GSM1352302", "GSM1352303", "GSM1352304", "GSM1352305", "GSM1352306", "GSM1352307", "GSM1352308", "GSM1352309", "GSM1352310", "GSM1352311", "GSM1352312", "GSM1352313", "GSM1352314", "GSM1352315", "GSM1352316", "GSM1352317", "GSM1352318", "GSM1352319", "GSM1352320", "GSM1352321", "GSM1352322", "GSM1352323", "GSM1352324", "GSM1352325", "GSM1352326", "GSM1352327", "GSM1352328", "GSM1352329", "GSM1352330", "GSM1352331", "GSM1352332", "GSM1352333", "GSM1352334", "GSM1352335", "GSM1352336", "GSM1352337", "GSM1352338", "GSM1352339", "GSM1352340", "GSM1352341", "GSM1352342", "GSM1352343", "GSM1352344", "GSM1352345", "GSM1352346", "GSM1352347", "GSM1352348", "GSM1352349", "GSM1352350", "GSM1352351", "GSM1352352", "GSM1352353", "GSM1352354", "GSM1352355", "GSM1352356", "GSM1352357", "GSM1352358", "GSM1352359", "GSM1352360", "GSM1352361", "GSM1352362", "GSM1352363", "GSM1352364", "GSM1352365", "GSM1352366", "GSM1352367", "GSM1352368", "GSM1352369", "GSM1352370", "GSM1352371", "GSM1352372", "GSM1352373", "GSM1352374", "GSM1352375", "GSM1352376", "GSM1352377", "GSM1352378", "GSM1352379", "GSM1352380", "GSM1352381", "GSM1352382", "GSM1352383", "GSM1352384", "GSM1352385", "GSM1352386", "GSM1352387", "GSM1352388", "GSM1352389", "GSM1352390", "GSM1352391", "GSM1352392", "GSM1352393", "GSM1352394", "GSM1352395", "GSM1352396", "GSM1352397", "GSM1352398", "GSM1352399", "GSM1352400", "GSM1352401", "GSM1352402", "GSM1352403", "GSM1352404", "GSM1352405", "GSM1352406", "GSM1352407", "GSM1352408", "GSM1352409", "GSM1352410", "GSM1352411", "GSM1352412", "GSM1352413", "GSM1352414", "GSM1352415", "GSM1352416", "GSM1352417", "GSM1352418", "GSM1352419", "GSM1352420", "GSM1352421", "GSM1352422", "GSM1352423", "GSM1352424", "GSM1352425", "GSM1352426", "GSM1352427", "GSM1352428", "GSM1352429", "GSM1352430", "GSM1352431", "GSM1352432", "GSM1352433", "GSM1352434", "GSM1352435", "GSM1352436", "GSM1352437", "GSM1352438", "GSM1352439", "GSM1352440", "GSM1352441", "GSM1352442", "GSM1352443", "GSM1352444", "GSM1352445", "GSM1352446", "GSM1352447", "GSM1352448", "GSM1352449", "GSM1352450", "GSM1352451", "GSM1352452", "GSM1352453", "GSM1352454", "GSM1352455", "GSM1352456", "GSM1352457", "GSM1352458", "GSM1352459", "GSM1352460", "GSM1352461", "GSM1352462", "GSM1352463", "GSM1352464", "GSM1352465", "GSM1352466", "GSM1352467", "GSM1352468", "GSM1352469", "GSM1352470", "GSM1352471", "GSM1352472", "GSM1352473", "GSM1352474", "GSM1352475", "GSM1352476", "GSM1352477", "GSM1352478", "GSM1352479", "GSM1352480", "GSM1352481", "GSM1352482", "GSM1352483", "GSM1352484", "GSM1352485", "GSM1352486", "GSM1352487", "GSM1352488", "GSM1352489", "GSM1352490", "GSM1352491", "GSM1352492", "GSM1352493", "GSM1352494", "GSM1352495", "GSM1352496", "GSM1352497", "GSM1352498", "GSM1352499", "GSM1352500", "GSM1352501", "GSM1352502", "GSM1352503", "GSM1352504", "GSM1352505", "GSM1352506", "GSM1352507", "GSM1352508", "GSM1352509", "GSM1352510", "GSM1352511", "GSM1352512", "GSM1352513", "GSM1352514", "GSM1352515", "GSM1352516", "GSM1352517", "GSM1352518", "GSM1352519", "GSM1352520", "GSM1352521", "GSM1352522", "GSM1352523", "GSM1352524", "GSM1352525", "GSM1352526", "GSM1352527", "GSM1352528", "GSM1352529", "GSM1352530", "GSM1352531", "GSM1352532", "GSM1352533", "GSM1352534", "GSM1352535", "GSM1352536", "GSM1352537", "GSM1352538", "GSM1352539", "GSM1352540", "GSM1352541", "GSM1352542", "GSM1352543", "GSM1352544", "GSM1352545", "GSM1352546", "GSM1352547", "GSM1352548", "GSM1352549", "GSM1352550", "GSM1352551", "GSM1352552", "GSM1352553", "GSM1352554", "GSM1352555", "GSM1352556", "GSM1352557", "GSM1352558", "GSM1352559", "GSM1352560", "GSM1352561", "GSM1352562", "GSM1352563", "GSM1352564", "GSM1352565", "GSM1352566", "GSM1352567", "GSM1352568", "GSM1352569", "GSM1352570", "GSM1352571", "GSM1352572", "GSM1352573", "GSM1352574", "GSM1352575", "GSM1352576", "GSM1352577", "GSM1352578", "GSM1352579", "GSM1352580", "GSM1352581", "GSM1352582", "GSM1352583", "GSM1352584", "GSM1352585", "GSM1352586", "GSM1352587", "GSM1352588", "GSM1352589", "GSM1352590", "GSM1352591", "GSM1352592", "GSM1352593", "GSM1352594", "GSM1352595", "GSM1352596", "GSM1352597", "GSM1352598", "GSM1352599", "GSM1352600", "GSM1352601", "GSM1352602", "GSM1352603", "GSM1352604", "GSM1352605", "GSM1352606", "GSM1352607", "GSM1352608", "GSM1352609", "GSM1352610", "GSM1352611", "GSM1352612", "GSM1352613", "GSM1352614", "GSM1352615", "GSM1352616", "GSM1352617", "GSM1352618", "GSM1352619", "GSM1352620", "GSM1352621", "GSM1352622", "GSM1352623", "GSM1352624", "GSM1352625", "GSM1352626", "GSM1352627", "GSM1352628", "GSM1352629", "GSM1352630", "GSM1352631", "GSM1352632", "GSM1352633", "GSM1352634", "GSM1352635", "GSM1352636", "GSM1352637", "GSM1352638", "GSM1352639", "GSM1352640", "GSM1352641", "GSM1352642", "GSM1352643", "GSM1352644", "GSM1352645", "GSM1352646", "GSM1352647", "GSM1352648", "GSM1352649", "GSM1352650", "GSM1352651", "GSM1352652", "GSM1352653", "GSM1352654", "GSM1352655", "GSM1352656", "GSM1352657", "GSM1352658", "GSM1352659", "GSM1352660", "GSM1352661", "GSM1352662", "GSM1352663", "GSM1352664", "GSM1352665", "GSM1352666", "GSM1352667", "GSM1352668", "GSM1352669", "GSM1352670", "GSM1352671", "GSM1352672", "GSM1352673", "GSM1352674", "GSM1352675", "GSM1352676", "GSM1352677", "GSM1352678", "GSM1352679", "GSM1352680", "GSM1352681", "GSM1352682", "GSM1352683", "GSM1352684", "GSM1352685", "GSM1352686", "GSM1352687", "GSM1352688", "GSM1352689", "GSM1352690", "GSM1352691", "GSM1352692", "GSM1352693", "GSM1352694", "GSM1352695", "GSM1352696", "GSM1352697", "GSM1352698", "GSM1352699", "GSM1352700", "GSM1352701", "GSM1352702", "GSM1352703", "GSM1352704", "GSM1352705", "GSM1352706", "GSM1352707", "GSM1352708", "GSM1352709", "GSM1352710", "GSM1352711", "GSM1352712", "GSM1352713", "GSM1352714", "GSM1352715", "GSM1352716", "GSM1352717", "GSM1352718", "GSM1352719", "GSM1352720", "GSM1352721", "GSM1352722", "GSM1352723", "GSM1352724", "GSM1352725", "GSM1352726", "GSM1352727", "GSM1352728", "GSM1352729", "GSM1352730", "GSM1352731", "GSM1352732", "GSM1352733", "GSM1352734", "GSM1352735", "GSM1352736", "GSM1352737", "GSM1352738", "GSM1352739", "GSM1352740", "GSM1352741", "GSM1352742", "GSM1352743", "GSM1352744", "GSM1352745", "GSM1352746", "GSM1352747", "GSM1352748", "GSM1352749", "GSM1352750", "GSM1352751", "GSM1352752", "GSM1352753", "GSM1352754", "GSM1352755", "GSM1352756", "GSM1352757", "GSM1352758", "GSM1352759", "GSM1352760", "GSM1352761", "GSM1352762", "GSM1352763", "GSM1352764", "GSM1352765", "GSM1352766", "GSM1352767", "GSM1352768", "GSM1352769", "GSM1352770", "GSM1352771", "GSM1352772", "GSM1352773", "GSM1352774", "GSM1352775", "GSM1352776", "GSM1352777", "GSM1352778", "GSM1352779", "GSM1352780", "GSM1352781", "GSM1352782", "GSM1352783", "GSM1352784", "GSM1352785", "GSM1352786", "GSM1352787", "GSM1352788", "GSM1352789", "GSM1352790", "GSM1352791", "GSM1352792", "GSM1352793", "GSM1352794", "GSM1352795", "GSM1352796", "GSM1352797", "GSM1352798", "GSM1352799", "GSM1352800", "GSM1352801", "GSM1352802", "GSM1352803", "GSM1352804", "GSM1352805", "GSM1352806", "GSM1352807", "GSM1352808", "GSM1352809", "GSM1352810", "GSM1352811", "GSM1352812", "GSM1352813", "GSM1352814", "GSM1352815", "GSM1352816", "GSM1352817", "GSM1352818", "GSM1352819", "GSM1352820", "GSM1352821", "GSM1352822", "GSM1352823", "GSM1352824", "GSM1352825", "GSM1352826", "GSM1352827", "GSM1352828", "GSM1352829", "GSM1352830", "GSM1352831", "GSM1352832", "GSM1352833", "GSM1352834", "GSM1352835", "GSM1352836", "GSM1352837", "GSM1352838", "GSM1352839", "GSM1352840", "GSM1352841", "GSM1352842", "GSM1352843", "GSM1352844", "GSM1352845", "GSM1352846", "GSM1352847", "GSM1352848", "GSM1352849", "GSM1352850", "GSM1352851", "GSM1352852", "GSM1352853", "GSM1352854", "GSM1352855", "GSM1352856", "GSM1352857", "GSM1352858", "GSM1352859", "GSM1352860", "GSM1352861", "GSM1352862", "GSM1352863", "GSM1352864", "GSM1352865", "GSM1352866", "GSM1352867", "GSM1352868", "GSM1352869", "GSM1352870", "GSM1352871", "GSM1352872", "GSM1352873", "GSM1352874", "GSM1352875", "GSM1352876", "GSM1352877", "GSM1352878", "GSM1352879", "GSM1352880", "GSM1352881", "GSM1352882", "GSM1352883", "GSM1352884", "GSM1352885", "GSM1352886", "GSM1352887", "GSM1352888", "GSM1352889", "GSM1352890", "GSM1352891", "GSM1352892", "GSM1352893", "GSM1352894", "GSM1352895", "GSM1352896", "GSM1352897", "GSM1352898", "GSM1352899", "GSM1352900", "GSM1352901", "GSM1352902", "GSM1352903", "GSM1352904", "GSM1352905", "GSM1352906", "GSM1352907", "GSM1352908", "GSM1352909", "GSM1352910", "GSM1352911", "GSM1352912", "GSM1352913", "GSM1352914", "GSM1352915", "GSM1352916", "GSM1352917", "GSM1352918", "GSM1352919", "GSM1352920", "GSM1352921", "GSM1352922", "GSM1352923", "GSM1352924", "GSM1352925", "GSM1352926", "GSM1352927", "GSM1352928", "GSM1352929", "GSM1352930", "GSM1352931", "GSM1352932", "GSM1352933", "GSM1352934", "GSM1352935", "GSM1352936", "GSM1352937", "GSM1352938", "GSM1352939", "GSM1352940", "GSM1352941", "GSM1352942", "GSM1352943", "GSM1352944", "GSM1352945", "GSM1352946", "GSM1352947", "GSM1352948", "GSM1352949", "GSM1352950", "GSM1352951", "GSM1352952", "GSM1352953", "GSM1352954", "GSM1352955", "GSM1352956", "GSM1352957", "GSM1352958", "GSM1352959", "GSM1352960", "GSM1352961", "GSM1352962", "GSM1352963", "GSM1352964", "GSM1352965", "GSM1352966", "GSM1352967", "GSM1352968", "GSM1352969", "GSM1352970", "GSM1352971", "GSM1352972", "GSM1352973", "GSM1352974", "GSM1352975", "GSM1352976", "GSM1352977", "GSM1352978", "GSM1352979", "GSM1352980", "GSM1352981", "GSM1352982", "GSM1352983", "GSM1352984", "GSM1352985", "GSM1352986", "GSM1352987", "GSM1352988", "GSM1352989", "GSM1352990", "GSM1352991", "GSM1352992", "GSM1352993", "GSM1352994", "GSM1352995", "GSM1352996", "GSM1352997", "GSM1352998", "GSM1352999", "GSM1353000", "GSM1353001", "GSM1353002", "GSM1353003", "GSM1353004", "GSM1353005", "GSM1353006", "GSM1353007", "GSM1353008", "GSM1353009", "GSM1353010", "GSM1353011", "GSM1353012", "GSM1353013", "GSM1353014", "GSM1353015", "GSM1353016", "GSM1353017", "GSM1353018", "GSM1353019", "GSM1353020", "GSM1353021", "GSM1353022", "GSM1353023", "GSM1353024", "GSM1353025", "GSM1353026", "GSM1353027", "GSM1353028", "GSM1353029", "GSM1353030", "GSM1353031", "GSM1353032", "GSM1353033", "GSM1353034", "GSM1353035", "GSM1353036", "GSM1353037", "GSM1353038", "GSM1353039", "GSM1353040", "GSM1353041", "GSM1353042", "GSM1353043", "GSM1353044", "GSM1353045", "GSM1353046", "GSM1353047", "GSM1353048", "GSM1353049", "GSM1353050", "GSM1353051", "GSM1353052", "GSM1353053", "GSM1353054", "GSM1353055", "GSM1353056", "GSM1353057", "GSM1353058", "GSM1353059", "GSM1353060", "GSM1353061", "GSM1353062", "GSM1353063", "GSM1353064", "GSM1353065", "GSM1353066", "GSM1353067", "GSM1353068", "GSM1353069", "GSM1353070", "GSM1353071", "GSM1353072", "GSM1353073", "GSM1353074", "GSM1353075", "GSM1353076", "GSM1353077", "GSM1353078", "GSM1353079", "GSM1353080", "GSM1353081", "GSM1353082", "GSM1353083", "GSM1353084", "GSM1353085", "GSM1353086", "GSM1353087", "GSM1353088", "GSM1353089", "GSM1353090", "GSM1353091", "GSM1353092", "GSM1353093", "GSM1353094", "GSM1353095", "GSM1353096", "GSM1353097", "GSM1353098", "GSM1353099", "GSM1353100", "GSM1353101", "GSM1353102", "GSM1353103", "GSM1353104", "GSM1353105", "GSM1353106", "GSM1353107", "GSM1353108", "GSM1353109", "GSM1353110", "GSM1353111", "GSM1353112", "GSM1353113", "GSM1353114", "GSM1353115", "GSM1353116", "GSM1353117", "GSM1353118", "GSM1353119", "GSM1353120", "GSM1353121", "GSM1353122", "GSM1353123", "GSM1353124", "GSM1353125", "GSM1353126", "GSM1353127", "GSM1353128", "GSM1353129", "GSM1353130", "GSM1353131", "GSM1353132", "GSM1353133", "GSM1353134", "GSM1353135", "GSM1353136", "GSM1353137", "GSM1353138", "GSM1353139", "GSM1353140", "GSM1353141", "GSM1353142", "GSM1353143", "GSM1353144", "GSM1353145", "GSM1353146", "GSM1353147", "GSM1353148", "GSM1353149", "GSM1353150", "GSM1353151", "GSM1353152", "GSM1353153", "GSM1353154", "GSM1353155", "GSM1353156", "GSM1353157", "GSM1353158", "GSM1353159", "GSM1353160", "GSM1353161", "GSM1353162", "GSM1353163", "GSM1353164", "GSM1353165", "GSM1353166", "GSM1353167", "GSM1353168", "GSM1353169", "GSM1353170", "GSM1353171", "GSM1353172", "GSM1353173", "GSM1353174", "GSM1353175", "GSM1353176", "GSM1353177", "GSM1353178", "GSM1353179", "GSM1353180", "GSM1353181", "GSM1353182", "GSM1353183", "GSM1353184", "GSM1353185", "GSM1353186", "GSM1353187", "GSM1353188", "GSM1353189", "GSM1353190", "GSM1353191", "GSM1353192", "GSM1353193", "GSM1353194", "GSM1353195", "GSM1353196", "GSM1353197", "GSM1353198", "GSM1353199", "GSM1353200", "GSM1353201", "GSM1353202", "GSM1353203"], "sample_count": 1202, "group_sizes": null, "group_sizes_basis": null, "platform": "10558", "taxon": "Homo sapiens", "title": "Transcriptomics and methylomics of human monocytes [transcriptome]", "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:GSE59867", "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=GSE59867", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE59867", "version": null, "note": "We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1448335", "GSM1448336", "GSM1448337", "GSM1448338", "GSM1448339", "GSM1448340", "GSM1448341", "GSM1448342", "GSM1448343", "GSM1448344", "GSM1448345", "GSM1448346", "GSM1448347", "GSM1448348", "GSM1448349", "GSM1448350", "GSM1448351", "GSM1448352", "GSM1448353", "GSM1448354", "GSM1448355", "GSM1448356", "GSM1448357", "GSM1448358", "GSM1448359", "GSM1448360", "GSM1448361", "GSM1448362", "GSM1448363", "GSM1448364", "GSM1448365", "GSM1448366", "GSM1448367", "GSM1448368", "GSM1448369", "GSM1448370", "GSM1448371", "GSM1448372", "GSM1448373", "GSM1448374", "GSM1448375", "GSM1448376", "GSM1448377", "GSM1448378", "GSM1448379", "GSM1448380", "GSM1448381", "GSM1448382", "GSM1448383", "GSM1448384", "GSM1448385", "GSM1448386", "GSM1448387", "GSM1448388", "GSM1448389", "GSM1448390", "GSM1448391", "GSM1448392", "GSM1448393", "GSM1448394", "GSM1448395", "GSM1448396", "GSM1448397", "GSM1448398", "GSM1448399", "GSM1448400", "GSM1448401", "GSM1448402", "GSM1448403", "GSM1448404", "GSM1448405", "GSM1448406", "GSM1448407", "GSM1448408", "GSM1448409", "GSM1448410", "GSM1448411", "GSM1448412", "GSM1448413", "GSM1448414", "GSM1448415", "GSM1448416", "GSM1448417", "GSM1448418", "GSM1448419", "GSM1448420", "GSM1448421", "GSM1448422", "GSM1448423", "GSM1448424", "GSM1448425", "GSM1448426", "GSM1448427", "GSM1448428", "GSM1448429", "GSM1448430", "GSM1448431", "GSM1448432", "GSM1448433", "GSM1448434", "GSM1448435", "GSM1448436", "GSM1448437", "GSM1448438", "GSM1448439", "GSM1448440", "GSM1448441", "GSM1448442", "GSM1448443", "GSM1448444", "GSM1448445", "GSM1448446", "GSM1448447", "GSM1448448", "GSM1448449", "GSM1448450", "GSM1448451", "GSM1448452", "GSM1448453", "GSM1448454", "GSM1448455", "GSM1448456", "GSM1448457", "GSM1448458", "GSM1448459", "GSM1448460", "GSM1448461", "GSM1448462", "GSM1448463", "GSM1448464", "GSM1448465", "GSM1448466", "GSM1448467", "GSM1448468", "GSM1448469", "GSM1448470", "GSM1448471", "GSM1448472", "GSM1448473", "GSM1448474", "GSM1448475", "GSM1448476", "GSM1448477", "GSM1448478", "GSM1448479", "GSM1448480", "GSM1448481", "GSM1448482", "GSM1448483", "GSM1448484", "GSM1448485", "GSM1448486", "GSM1448487", "GSM1448488", "GSM1448489", "GSM1448490", "GSM1448491", "GSM1448492", "GSM1448493", "GSM1448494", "GSM1448495", "GSM1448496", "GSM1448497", "GSM1448498", "GSM1448499", "GSM1448500", "GSM1448501", "GSM1448502", "GSM1448503", "GSM1448504", "GSM1448505", "GSM1448506", "GSM1448507", "GSM1448508", "GSM1448509", "GSM1448510", "GSM1448511", "GSM1448512", "GSM1448513", "GSM1448514", "GSM1448515", "GSM1448516", "GSM1448517", "GSM1448518", "GSM1448519", "GSM1448520", "GSM1448521", "GSM1448522", "GSM1448523", "GSM1448524", "GSM1448525", "GSM1448526", "GSM1448527", "GSM1448528", "GSM1448529", "GSM1448530", "GSM1448531", "GSM1448532", "GSM1448533", "GSM1448534", "GSM1448535", "GSM1448536", "GSM1448537", "GSM1448538", "GSM1448539", "GSM1448540", "GSM1448541", "GSM1448542", "GSM1448543", "GSM1448544", "GSM1448545", "GSM1448546", "GSM1448547", "GSM1448548", "GSM1448549", "GSM1448550", "GSM1448551", "GSM1448552", "GSM1448553", "GSM1448554", "GSM1448555", "GSM1448556", "GSM1448557", "GSM1448558", "GSM1448559", "GSM1448560", "GSM1448561", "GSM1448562", "GSM1448563", "GSM1448564", "GSM1448565", "GSM1448566", "GSM1448567", "GSM1448568", "GSM1448569", "GSM1448570", "GSM1448571", "GSM1448572", "GSM1448573", "GSM1448574", "GSM1448575", "GSM1448576", "GSM1448577", "GSM1448578", "GSM1448579", "GSM1448580", "GSM1448581", "GSM1448582", "GSM1448583", "GSM1448584", "GSM1448585", "GSM1448586", "GSM1448587", "GSM1448588", "GSM1448589", "GSM1448590", "GSM1448591", "GSM1448592", "GSM1448593", "GSM1448594", "GSM1448595", "GSM1448596", "GSM1448597", "GSM1448598", "GSM1448599", "GSM1448600", "GSM1448601", "GSM1448602", "GSM1448603", "GSM1448604", "GSM1448605", "GSM1448606", "GSM1448607", "GSM1448608", "GSM1448609", "GSM1448610", "GSM1448611", "GSM1448612", "GSM1448613", "GSM1448614", "GSM1448615", "GSM1448616", "GSM1448617", "GSM1448618", "GSM1448619", "GSM1448620", "GSM1448621", "GSM1448622", "GSM1448623", "GSM1448624", "GSM1448625", "GSM1448626", "GSM1448627", "GSM1448628", "GSM1448629", "GSM1448630", "GSM1448631", "GSM1448632", "GSM1448633", "GSM1448634", "GSM1448635", "GSM1448636", "GSM1448637", "GSM1448638", "GSM1448639", "GSM1448640", "GSM1448641", "GSM1448642", "GSM1448643", "GSM1448644", "GSM1448645", "GSM1448646", "GSM1448647", "GSM1448648", "GSM1448649", "GSM1448650", "GSM1448651", "GSM1448652", "GSM1448653", "GSM1448654", "GSM1448655", "GSM1448656", "GSM1448657", "GSM1448658", "GSM1448659", "GSM1448660", "GSM1448661", "GSM1448662", "GSM1448663", "GSM1448664", "GSM1448665", "GSM1448666", "GSM1448667", "GSM1448668", "GSM1448669", "GSM1448670", "GSM1448671", "GSM1448672", "GSM1448673", "GSM1448674", "GSM1448675", "GSM1448676", "GSM1448677", "GSM1448678", "GSM1448679", "GSM1448680", "GSM1448681", "GSM1448682", "GSM1448683", "GSM1448684", "GSM1448685", "GSM1448686", "GSM1448687", "GSM1448688", "GSM1448689", "GSM1448690", "GSM1448691", "GSM1448692", "GSM1448693", "GSM1448694", "GSM1448695", "GSM1448696", "GSM1448697", "GSM1448698", "GSM1448699", "GSM1448700", "GSM1448701", "GSM1448702", "GSM1448703", "GSM1448704", "GSM1448705", "GSM1448706", "GSM1448707", "GSM1448708", "GSM1448709", "GSM1448710", "GSM1448711", "GSM1448712", "GSM1448713", "GSM1448714", "GSM1448715", "GSM1448716", "GSM1448717", "GSM1448718", "GSM1448719", "GSM1448720", "GSM1448721", "GSM1448722", "GSM1448723", "GSM1448724", "GSM1620759", "GSM1620760", "GSM1620761", "GSM1620762", "GSM1620763", "GSM1620764", "GSM1620765", "GSM1620766", "GSM1620767", "GSM1620768", "GSM1620769", "GSM1620770", "GSM1620771", "GSM1620772", "GSM1620773", "GSM1620774", "GSM1620775", "GSM1620776", "GSM1620777", "GSM1620778", "GSM1620779", "GSM1620780", "GSM1620781", "GSM1620782", "GSM1620783", "GSM1620784", "GSM1620785", "GSM1620786", "GSM1620787", "GSM1620788", "GSM1620789", "GSM1620790", "GSM1620791", "GSM1620792", "GSM1620793", "GSM1620794", "GSM1620795", "GSM1620796", "GSM1620797", "GSM1620798", "GSM1620799", "GSM1620800", "GSM1620801", "GSM1620802", "GSM1620803", "GSM1620804"], "sample_count": 436, "group_sizes": null, "group_sizes_basis": null, "platform": "6244", "taxon": "Homo sapiens", "title": "Gene expression profiling reveals potential prognostic biomarkers associated with the progression of heart failure", "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:GSE60993", "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=GSE60993", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE60993", "version": null, "note": "We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1495313", "GSM1495314", "GSM1495315", "GSM1495316", "GSM1495317", "GSM1495318", "GSM1495319", "GSM1495320", "GSM1495321", "GSM1495322", "GSM1495323", "GSM1495324", "GSM1495325", "GSM1495326", "GSM1495327", "GSM1495328", "GSM1495329", "GSM1495330", "GSM1495331", "GSM1495332", "GSM1495333", "GSM1495334", "GSM1495335", "GSM1495336", "GSM1495337", "GSM1495338", "GSM1495339", "GSM1495340", "GSM1495341", "GSM1495342", "GSM1495343", "GSM1495344", "GSM1495345"], "sample_count": 33, "group_sizes": null, "group_sizes_basis": null, "platform": "6884", "taxon": "Homo sapiens", "title": "Assessment and Diagnostic Relevance of Novel Serum Biomarkers for Early Decision of ST-elevation Myocardial Infarction", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33052139:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:4f03c09541ec5a80ce8eaa425a7d4030251d52dad532aef2fbc8d2a0c171d329", "bytes": 2600, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[8]/table-wrap[1]#t1", "version": null, "note": "Comparison of demographic, lifestyle characteristics and serum lipid levels among different groups.", "structure": {"pmcid": "PMC7732301", "section_index": 8, "section_title": "Subject validation", "row_count": 27, "column_count": 6}, "table": {"label": "Table 1", "caption": "Comparison of demographic, lifestyle characteristics and serum lipid levels among different groups.", "rows": [["Parameter", "Control", "CAD", "UA", "NSTEMI", "STEMI"], ["Number", "312", "320", "304", "290", "302"], ["Male/female", "94/220", "89/231", "92/210", "84/202", "98/202"], ["Age (years)1", "55.32±8.31", "54.16±9.05", "55.59±8.54", "56.43±9.83", "55.94±9.17"], ["Height (cm)", "166.24±6.82", "168.59±7.29", "167.55±7.28", "166.52±6.94", "167.23±9.13"], ["Weight (kg)", "52.46±6.84", "54.74±10.82", "57.63±9.11a", "57.92±8.77a", "57.52±9.23a"], ["Body mass index (kg/m2)", "29.29±5.13", "30.44±6.47a", "30.67±7.12a", "30.79±6.74a", "30.77±6.09a"], ["Waist circumference (cm)", "74.49±6.74", "73.55±9.48", "76.03±8.15", "76.24±7.17", "76.15±6.27"], ["Smoking status [n (%)]", "81(26.0)", "114(35.6) a", "142(46.7) a", "138(47.6) a", "144(47.6) a"], ["Alcohol consumption [n (%)]", "75(24.0)", "84(26.2)", "70(23.0)", "81(27.9) a", "71(23.5)"], ["SBP (mmHg)", "124.14±17.14", "129.21±21.11a", "147.15±23.96c", "139.47±22.14b", "103.45±17.16c"], ["DBP (mmHg)", "80.52±11.16", "81.33±11.25", "88.54±14.23a", "84.43±11.21", "68.54±12.15c"], ["PP (mmHg)", "49.64±14.13", "51.42±13.59", "51.66±15.24", "50.84±15.22", "50.22±14.21"], ["Glucose (mmol/L)", "5.91±1.83", "6.13±2.22", "7.79±2.43b", "8.46±2.79c", "8.69±2.78c"], ["TC (mmol/L)", "4.93±1.21", "5.21±1.17a", "5.63±1.12a", "5.99±1.18a", "5.83±1.43a"], ["TG (mmol/L)2", "1.49(0.51)", "1.53(1.22)", "1.52(1.21)", "1.44(1.32)", "1.51(1.26)"], ["HDL-C (mmol/L)", "1.52±0.44", "1.32±0.26a", "1.35±0.34a", "1.44±0.28a", "1.48±0.32"], ["LDL-C (mmol/L)", "2.86±0.81", "3.23±0.74a", "3.98±0.79a", "3.79±0.88a", "3.92±0.84a"], ["ApoA1 (g/L)", "1.24±0.24", "1.17±0.22", "1.18±0.26", "1.18±0.26", "1.14±0.28"], ["ApoB (g/L)", "0.84±0.19", "0.82±0.32", "0.81±0.31", "0.94±0.31", "0.88±0.28"], ["ApoA1/ApoB", "1.67±0.50", "1.66±0.57", "1.64±0.58", "1.65±0.61", "1.67±0.54"], ["Heart rate (beats/minutes)", "72.41±10.19", "72.33±10.32", "76.28±10.61a", "76.43±9.31a", "79.76±10.14a"], ["Creatinine, (μmol/L)", "72.34±12.22", "71.36±11.34", "74.53±11.62", "76.55±10.23", "76.58±12.74"], ["Uric acid, (μmol/L)", "283.83±76.19", "286.89±74.32", "279.88±81.31", "285.91±81.31", "283.86±75.28"], ["Troponin T, (μg/L)", "0.01±0.02", "0.02±0.02", "0.02±0.01", "2.74±3.93c", "2.86±6.28c"], ["CK, (U/L)", "88.84±45.28", "87.84±48.31", "91.88±50.33", "1111.92±683.31c", "1124.88±783.28c"], ["CKMB, (U/L)", "12.44±3.63", "13.11±2.78", "13.22±3.32", "129.88±61.45c", "132.76±59.17c"]], "row_count": 27, "column_count": 6, "numeric_cells": 132, "header_rows": 0, "locator": "section[8]/table-wrap[1]#t1"}}], "gaps": ["asset:data:geo:GSE129935 not downloaded", "asset:data:geo:GSE129935 licence not read", "asset:data:geo:GSE23561 not downloaded", "asset:data:geo:GSE23561 licence not read", "asset:data:geo:GSE34822 not downloaded", "asset:data:geo:GSE34822 licence not read", "asset:data:geo:GSE56045 not downloaded", "asset:data:geo:GSE56045 licence not read", "asset:data:geo:GSE59867 not downloaded", "asset:data:geo:GSE59867 licence not read", "asset:data:geo:GSE60993 not downloaded", "asset:data:geo:GSE60993 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "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-2", "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": "protein-protein interaction"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}, {"id": "method-4", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "Chi-square"}}, {"id": "method-5", "family": null, "specific": null, "label": "Linear correlation", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "First, we analyzed the relationship between the expression level of these 24 genes and the coronary artery calcification score by linear correlation in GSE56045."}}], "targets": [], "gaps": ["method.reader_named_unmapped", "method.group_comparison_wilcoxon"]}, "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": false, "required_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon."}, "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": ["GSE56045", "GSE23561", "GSE34822", "GSE59867", "GSE60993", "GSE129935"], "resolved_accessions": ["GSE56045", "GSE23561", "GSE34822", "GSE59867", "GSE60993", "GSE129935"], "statements": ["We downloaded GSE56045 [21] microarray data from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/). These datasets were based on the platform of the GPL10558 Illumina HumanHT-12 V4.0 expression BeadChip. GSE56045 contains 1,202 peripheral blood samples, as well as clinical information, such as age, whole-blood cell count, and the coronary artery calcification plaque score."], "basis": "The paper names GSE56045, GSE23561, GSE34822, GSE59867, GSE60993, GSE129935 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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