Corpus Engine Towards a reproducible .science file.
← All .science files

pmid:41130017

Exploring the therapeutic role of thiabendazole in lung adenocarcinoma via network pharmacology and single-cell analysis.

Wanghong Qi · Guoqiu Xu · Lang Tang · Chunlin Ye · Xi Liu

Translational oncology · 2025 doi:10.1016/j.tranon.2025.102548

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:41130017
kind
science-record
content_hash
sha256:6e8c5ae03042be45691da39fb7a05c2b5292cf789e93a6e19556b5f9d908e595
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T20:31:11Z
updated_at
2026-11-01T22:57:21Z
generator object · 2 fields
name
corpus-assay-engine
run_id
reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
Exploring the therapeutic role of thiabendazole in lung adenocarcinoma via network pharmacology and single-cell analysis.
doi
10.1016/j.tranon.2025.102548
pmid
41130017
authors array · 5 items
[0]
Wanghong Qi
[1]
Guoqiu Xu
[2]
Lang Tang
[3]
Chunlin Ye
[4]
Xi Liu
journal
Translational oncology
year
2025
abstract
BACKGROUND: Lung adenocarcinoma (LUAD) is the leading cause of cancer-related deaths globally, with over 2.2 million new cases in 2020. Despite advances in targeted therapies, challenges such as drug resistance and severe side effects persist. Thiabendazole, an antiparasitic drug, has shown potential anticancer effects in LUAD. METHODS: This study used network pharmacology, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcriptome datasets (GSE10072, GSE19188, GSE19804, GSE30219, GSE40791), and bioinformatics tools to explore Thiabendazole's mechanisms in LUAD. Potential targets were predicted through PubChem and SwissTargetPrediction. scRNA-seq data were analyzed using Seurat, and key genes and pathways were identified via Weighted Gene Co-expression Network Analysis (WGCNA) and multi-omics integration. Diagnostic genes were further screened using LASSO regression, Support Vector Machine (SVM), and random forest (RF) models. RESULTS: Single-cell analysis revealed macrophages as key targets of Thiabendazole. Transcriptomic analysis identified 2034 downregulated and 2388 upregulated genes. WGCNA found a core gene module (MEred) strongly correlated with Thiabendazole (r = 0.75, p = 2e-07). Four diagnostic genes-ACE, ALDOA, MME, and PMP22-showed high accuracy (0.982). Thiabendazole also modulated immune cell infiltration, particularly affecting macrophage activity. Molecular docking confirmed stable binding to ACE, ALDOA, and MME. CONCLUSION: Thiabendazole demonstrates promising anticancer potential in LUAD, influencing key genes and immune pathways. It may serve as an effective therapeutic agent targeting both cancer cells and the tumor microenvironment.
claims array · 3 items
[0] object · 6 fields
id
claim-method
statement
The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes.
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:41130017
locator
sections[6] "Processing and analysis of transcriptome data" paragraph 2
quote
The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes.
state
complete
[1] object · 6 fields
id
claim-data-access
statement
All datasets utilized or generated during the study are fully available within this article.
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:41130017
locator
sections[36] "Data availability" paragraph 2
quote
All datasets utilized or generated during the study are fully available within this article.
state
complete
[2] object · 6 fields
id
claim-target-result
statement
Four diagnostic genes—ACE, ALDOA, MME, and PMP22—showed high accuracy (0.982).
kind
qualitative
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:41130017
locator
sections[0] "Abstract" paragraph 9
quote
Four diagnostic genes—ACE, ALDOA, MME, and PMP22—showed high accuracy (0.982).
state
complete
gaps array · 0 items
experiment object · 8 fields
state
complete
objective
Four diagnostic genes—ACE, ALDOA, MME, and PMP22—showed high accuracy (0.982).
steps array · 3 items
[0] object · 13 fields
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.
parameters object · 0 fields
inputs array · 1 item
[0]
source:pmid:41130017
outputs array · 1 item
[0]
the published estimate and its evidence
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
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.
parameters object · 0 fields
inputs array · 1 item
[0]
data:geo:GSE10072
outputs array · 1 item
[0]
the source data with its repository provenance
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
id
run_analysis
order
3
name
Run the published analysis
kind
analysis
state
complete
blocked_on
null
description
Apply the paper's statistical method to the resolved series and compare the result with the published target.
parameters object · 0 fields
inputs array · 1 item
[0]
data:geo:GSE10072
outputs array · 1 item
[0]
the replicated result and its comparison
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 0 items
data object · 3 fields
state
partial
assets array · 7 items
[0] object · 15 fields
id
source:pmid:41130017
role
manuscript
format
xml
media_type
application/xml
uri
https://doi.org/10.1016/j.tranon.2025.102548
sha256
sha256:1fd19a8f48e8384def6f3192a46eb01465c158215a3751e5e8b2e5a2b30a7bd5
bytes
66795
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
10.1016/j.tranon.2025.102548
version
null
note
Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.
structure object · 4 fields
pmcid
PMC12590012
source
europe_pmc_fulltext
coverage
whole_body
text_hash_scope
rendered_section_body
[1] object · 15 fields
id
data:geo:GSE10072
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=GSE10072
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE10072
version
null
note
All datasets utilized or generated during the study are fully available within this article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All datasets utilized or generated during the study are fully available within this article.
access_statement_kind
data_availability_statement
sample_accessions array · 107 items
[0]
GSM254625
[1]
GSM254626
[2]
GSM254627
[3]
GSM254628
[4]
GSM254629
[5]
GSM254630
[6]
GSM254631
[7]
GSM254632
[8]
GSM254633
[9]
GSM254634
[10]
GSM254635
[11]
GSM254636
[12]
GSM254637
[13]
GSM254638
[14]
GSM254639
[15]
GSM254640
[16]
GSM254641
[17]
GSM254642
[18]
GSM254643
[19]
GSM254644
[20]
GSM254645
[21]
GSM254646
[22]
GSM254647
[23]
GSM254648
[24]
GSM254649
[25]
GSM254650
[26]
GSM254651
[27]
GSM254652
[28]
GSM254653
[29]
GSM254654
[30]
GSM254655
[31]
GSM254656
[32]
GSM254657
[33]
GSM254658
[34]
GSM254659
[35]
GSM254660
[36]
GSM254661
[37]
GSM254662
[38]
GSM254663
[39]
GSM254664
[40]
GSM254665
[41]
GSM254666
[42]
GSM254667
[43]
GSM254668
[44]
GSM254669
[45]
GSM254670
[46]
GSM254671
[47]
GSM254672
[48]
GSM254673
[49]
GSM254674
[50]
GSM254675
[51]
GSM254676
[52]
GSM254677
[53]
GSM254678
[54]
GSM254679
[55]
GSM254680
[56]
GSM254681
[57]
GSM254682
[58]
GSM254683
[59]
GSM254684
[60]
GSM254685
[61]
GSM254686
[62]
GSM254687
[63]
GSM254688
[64]
GSM254689
[65]
GSM254690
[66]
GSM254691
[67]
GSM254692
[68]
GSM254693
[69]
GSM254694
[70]
GSM254695
[71]
GSM254696
[72]
GSM254697
[73]
GSM254698
[74]
GSM254699
[75]
GSM254700
[76]
GSM254701
[77]
GSM254702
[78]
GSM254703
[79]
GSM254704
[80]
GSM254705
[81]
GSM254706
[82]
GSM254707
[83]
GSM254708
[84]
GSM254709
[85]
GSM254710
[86]
GSM254711
[87]
GSM254712
[88]
GSM254713
[89]
GSM254714
[90]
GSM254715
[91]
GSM254716
[92]
GSM254717
[93]
GSM254718
[94]
GSM254719
[95]
GSM254720
[96]
GSM254721
[97]
GSM254722
[98]
GSM254723
[99]
GSM254724
[100]
GSM254725
[101]
GSM254726
[102]
GSM254727
[103]
GSM254728
[104]
GSM254729
[105]
GSM254730
[106]
GSM254731
sample_count
107
group_sizes
null
group_sizes_basis
null
platform
96
taxon
Homo sapiens
title
Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival
resolution_checked_at
2026-11-01T15:30:21Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[2] object · 15 fields
id
data:geo:GSE136103
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=GSE136103
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE136103
version
null
note
All datasets utilized or generated during the study are fully available within this article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All datasets utilized or generated during the study are fully available within this article.
access_statement_kind
data_availability_statement
sample_accessions array · 26 items
[0]
GSM4041150
[1]
GSM4041151
[2]
GSM4041152
[3]
GSM4041153
[4]
GSM4041154
[5]
GSM4041155
[6]
GSM4041156
[7]
GSM4041157
[8]
GSM4041158
[9]
GSM4041159
[10]
GSM4041160
[11]
GSM4041161
[12]
GSM4041162
[13]
GSM4041163
[14]
GSM4041164
[15]
GSM4041165
[16]
GSM4041166
[17]
GSM4041167
[18]
GSM4041168
[19]
GSM4041169
[20]
GSM4041170
[21]
GSM4041171
[22]
GSM4041172
[23]
GSM4041173
[24]
GSM4041174
[25]
GSM4041175
sample_count
26
group_sizes
null
group_sizes_basis
null
platform
20301;21103
taxon
Homo sapiens; Mus musculus
title
Resolving the fibrotic niche of human liver cirrhosis using single-cell transcriptomics
resolution_checked_at
2026-11-01T18:46:34Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE19188
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=GSE19188
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE19188
version
null
note
All datasets utilized or generated during the study are fully available within this article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All datasets utilized or generated during the study are fully available within this article.
access_statement_kind
data_availability_statement
sample_accessions array · 156 items
[0]
GSM475656
[1]
GSM475657
[2]
GSM475658
[3]
GSM475659
[4]
GSM475660
[5]
GSM475661
[6]
GSM475662
[7]
GSM475663
[8]
GSM475664
[9]
GSM475665
[10]
GSM475666
[11]
GSM475667
[12]
GSM475668
[13]
GSM475669
[14]
GSM475670
[15]
GSM475671
[16]
GSM475672
[17]
GSM475673
[18]
GSM475674
[19]
GSM475675
[20]
GSM475676
[21]
GSM475677
[22]
GSM475678
[23]
GSM475679
[24]
GSM475680
[25]
GSM475681
[26]
GSM475682
[27]
GSM475683
[28]
GSM475684
[29]
GSM475685
[30]
GSM475686
[31]
GSM475687
[32]
GSM475688
[33]
GSM475689
[34]
GSM475690
[35]
GSM475691
[36]
GSM475692
[37]
GSM475693
[38]
GSM475694
[39]
GSM475695
[40]
GSM475696
[41]
GSM475697
[42]
GSM475698
[43]
GSM475699
[44]
GSM475700
[45]
GSM475701
[46]
GSM475702
[47]
GSM475703
[48]
GSM475704
[49]
GSM475705
[50]
GSM475706
[51]
GSM475707
[52]
GSM475708
[53]
GSM475709
[54]
GSM475710
[55]
GSM475711
[56]
GSM475712
[57]
GSM475713
[58]
GSM475714
[59]
GSM475715
[60]
GSM475716
[61]
GSM475717
[62]
GSM475718
[63]
GSM475719
[64]
GSM475720
[65]
GSM475721
[66]
GSM475722
[67]
GSM475723
[68]
GSM475724
[69]
GSM475725
[70]
GSM475726
[71]
GSM475727
[72]
GSM475728
[73]
GSM475729
[74]
GSM475730
[75]
GSM475731
[76]
GSM475732
[77]
GSM475733
[78]
GSM475734
[79]
GSM475735
[80]
GSM475736
[81]
GSM475737
[82]
GSM475738
[83]
GSM475739
[84]
GSM475740
[85]
GSM475741
[86]
GSM475742
[87]
GSM475743
[88]
GSM475744
[89]
GSM475745
[90]
GSM475746
[91]
GSM475747
[92]
GSM475748
[93]
GSM475749
[94]
GSM475750
[95]
GSM475751
[96]
GSM475752
[97]
GSM475753
[98]
GSM475754
[99]
GSM475755
[100]
GSM475756
[101]
GSM475757
[102]
GSM475758
[103]
GSM475759
[104]
GSM475760
[105]
GSM475761
[106]
GSM475762
[107]
GSM475763
[108]
GSM475764
[109]
GSM475765
[110]
GSM475766
[111]
GSM475767
[112]
GSM475768
[113]
GSM475769
[114]
GSM475770
[115]
GSM475771
[116]
GSM475772
[117]
GSM475773
[118]
GSM475774
[119]
GSM475775
[120]
GSM475776
[121]
GSM475777
[122]
GSM475778
[123]
GSM475779
[124]
GSM475780
[125]
GSM475781
[126]
GSM475782
[127]
GSM475783
[128]
GSM475784
[129]
GSM475785
[130]
GSM475786
[131]
GSM475787
[132]
GSM475788
[133]
GSM475789
[134]
GSM475790
[135]
GSM475791
[136]
GSM475792
[137]
GSM475793
[138]
GSM475794
[139]
GSM475795
[140]
GSM475796
[141]
GSM475797
[142]
GSM475798
[143]
GSM475799
[144]
GSM475800
[145]
GSM475801
[146]
GSM475802
[147]
GSM475803
[148]
GSM475804
[149]
GSM475805
[150]
GSM475806
[151]
GSM475807
[152]
GSM475808
[153]
GSM475809
[154]
GSM475810
[155]
GSM475811
sample_count
156
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Expression data for early stage NSCLC
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE19804
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=GSE19804
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE19804
version
null
note
All datasets utilized or generated during the study are fully available within this article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All datasets utilized or generated during the study are fully available within this article.
access_statement_kind
data_availability_statement
sample_accessions array · 120 items
[0]
GSM494556
[1]
GSM494557
[2]
GSM494558
[3]
GSM494559
[4]
GSM494560
[5]
GSM494561
[6]
GSM494562
[7]
GSM494563
[8]
GSM494564
[9]
GSM494565
[10]
GSM494566
[11]
GSM494567
[12]
GSM494568
[13]
GSM494569
[14]
GSM494570
[15]
GSM494571
[16]
GSM494572
[17]
GSM494573
[18]
GSM494574
[19]
GSM494575
[20]
GSM494576
[21]
GSM494577
[22]
GSM494578
[23]
GSM494579
[24]
GSM494580
[25]
GSM494581
[26]
GSM494582
[27]
GSM494583
[28]
GSM494584
[29]
GSM494585
[30]
GSM494586
[31]
GSM494587
[32]
GSM494588
[33]
GSM494589
[34]
GSM494590
[35]
GSM494591
[36]
GSM494592
[37]
GSM494593
[38]
GSM494594
[39]
GSM494595
[40]
GSM494596
[41]
GSM494597
[42]
GSM494598
[43]
GSM494599
[44]
GSM494600
[45]
GSM494601
[46]
GSM494602
[47]
GSM494603
[48]
GSM494604
[49]
GSM494605
[50]
GSM494606
[51]
GSM494607
[52]
GSM494608
[53]
GSM494609
[54]
GSM494610
[55]
GSM494611
[56]
GSM494612
[57]
GSM494613
[58]
GSM494614
[59]
GSM494615
[60]
GSM494616
[61]
GSM494617
[62]
GSM494618
[63]
GSM494619
[64]
GSM494620
[65]
GSM494621
[66]
GSM494622
[67]
GSM494623
[68]
GSM494624
[69]
GSM494625
[70]
GSM494626
[71]
GSM494627
[72]
GSM494628
[73]
GSM494629
[74]
GSM494630
[75]
GSM494631
[76]
GSM494632
[77]
GSM494633
[78]
GSM494634
[79]
GSM494635
[80]
GSM494636
[81]
GSM494637
[82]
GSM494638
[83]
GSM494639
[84]
GSM494640
[85]
GSM494641
[86]
GSM494642
[87]
GSM494643
[88]
GSM494644
[89]
GSM494645
[90]
GSM494646
[91]
GSM494647
[92]
GSM494648
[93]
GSM494649
[94]
GSM494650
[95]
GSM494651
[96]
GSM494652
[97]
GSM494653
[98]
GSM494654
[99]
GSM494655
[100]
GSM494656
[101]
GSM494657
[102]
GSM494658
[103]
GSM494659
[104]
GSM494660
[105]
GSM494661
[106]
GSM494662
[107]
GSM494663
[108]
GSM494664
[109]
GSM494665
[110]
GSM494666
[111]
GSM494667
[112]
GSM494668
[113]
GSM494669
[114]
GSM494670
[115]
GSM494671
[116]
GSM494672
[117]
GSM494673
[118]
GSM494674
[119]
GSM494675
sample_count
120
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Genome-wide screening of transcriptional modulation in non-smoking female lung cancer in Taiwan
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:GSE30219
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=GSE30219
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE30219
version
null
note
All datasets utilized or generated during the study are fully available within this article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All datasets utilized or generated during the study are fully available within this article.
access_statement_kind
data_availability_statement
sample_accessions array · 307 items
[0]
GSM1465989
[1]
GSM1465990
[2]
GSM1465991
[3]
GSM1465992
[4]
GSM1465993
[5]
GSM1465994
[6]
GSM1465995
[7]
GSM1465996
[8]
GSM1465997
[9]
GSM1465998
[10]
GSM1465999
[11]
GSM748053
[12]
GSM748054
[13]
GSM748055
[14]
GSM748056
[15]
GSM748057
[16]
GSM748058
[17]
GSM748059
[18]
GSM748060
[19]
GSM748061
[20]
GSM748062
[21]
GSM748063
[22]
GSM748064
[23]
GSM748065
[24]
GSM748066
[25]
GSM748067
[26]
GSM748068
[27]
GSM748069
[28]
GSM748070
[29]
GSM748071
[30]
GSM748072
[31]
GSM748073
[32]
GSM748074
[33]
GSM748075
[34]
GSM748076
[35]
GSM748077
[36]
GSM748078
[37]
GSM748079
[38]
GSM748080
[39]
GSM748081
[40]
GSM748083
[41]
GSM748084
[42]
GSM748085
[43]
GSM748086
[44]
GSM748087
[45]
GSM748088
[46]
GSM748089
[47]
GSM748090
[48]
GSM748091
[49]
GSM748092
[50]
GSM748093
[51]
GSM748094
[52]
GSM748095
[53]
GSM748096
[54]
GSM748097
[55]
GSM748098
[56]
GSM748099
[57]
GSM748100
[58]
GSM748101
[59]
GSM748102
[60]
GSM748103
[61]
GSM748104
[62]
GSM748105
[63]
GSM748106
[64]
GSM748107
[65]
GSM748108
[66]
GSM748109
[67]
GSM748110
[68]
GSM748111
[69]
GSM748112
[70]
GSM748113
[71]
GSM748115
[72]
GSM748116
[73]
GSM748117
[74]
GSM748118
[75]
GSM748119
[76]
GSM748120
[77]
GSM748121
[78]
GSM748122
[79]
GSM748123
[80]
GSM748124
[81]
GSM748125
[82]
GSM748126
[83]
GSM748127
[84]
GSM748128
[85]
GSM748129
[86]
GSM748130
[87]
GSM748131
[88]
GSM748132
[89]
GSM748133
[90]
GSM748134
[91]
GSM748135
[92]
GSM748136
[93]
GSM748137
[94]
GSM748138
[95]
GSM748139
[96]
GSM748140
[97]
GSM748141
[98]
GSM748142
[99]
GSM748143
[100]
GSM748144
[101]
GSM748145
[102]
GSM748146
[103]
GSM748147
[104]
GSM748148
[105]
GSM748149
[106]
GSM748150
[107]
GSM748151
[108]
GSM748152
[109]
GSM748153
[110]
GSM748154
[111]
GSM748155
[112]
GSM748156
[113]
GSM748157
[114]
GSM748158
[115]
GSM748159
[116]
GSM748160
[117]
GSM748161
[118]
GSM748162
[119]
GSM748163
[120]
GSM748164
[121]
GSM748165
[122]
GSM748166
[123]
GSM748167
[124]
GSM748168
[125]
GSM748169
[126]
GSM748170
[127]
GSM748171
[128]
GSM748172
[129]
GSM748173
[130]
GSM748174
[131]
GSM748175
[132]
GSM748176
[133]
GSM748177
[134]
GSM748178
[135]
GSM748179
[136]
GSM748180
[137]
GSM748181
[138]
GSM748182
[139]
GSM748183
[140]
GSM748184
[141]
GSM748185
[142]
GSM748186
[143]
GSM748187
[144]
GSM748188
[145]
GSM748189
[146]
GSM748191
[147]
GSM748192
[148]
GSM748193
[149]
GSM748195
[150]
GSM748196
[151]
GSM748197
[152]
GSM748198
[153]
GSM748199
[154]
GSM748200
[155]
GSM748201
[156]
GSM748202
[157]
GSM748203
[158]
GSM748206
[159]
GSM748207
[160]
GSM748209
[161]
GSM748210
[162]
GSM748211
[163]
GSM748212
[164]
GSM748213
[165]
GSM748214
[166]
GSM748215
[167]
GSM748216
[168]
GSM748217
[169]
GSM748218
[170]
GSM748219
[171]
GSM748220
[172]
GSM748221
[173]
GSM748222
[174]
GSM748223
[175]
GSM748224
[176]
GSM748225
[177]
GSM748226
[178]
GSM748227
[179]
GSM748228
[180]
GSM748229
[181]
GSM748232
[182]
GSM748233
[183]
GSM748234
[184]
GSM748235
[185]
GSM748239
[186]
GSM748240
[187]
GSM748242
[188]
GSM748243
[189]
GSM748244
[190]
GSM748245
[191]
GSM748246
[192]
GSM748247
[193]
GSM748248
[194]
GSM748249
[195]
GSM748250
[196]
GSM748251
[197]
GSM748252
[198]
GSM748253
[199]
GSM748254
[200]
GSM748255
[201]
GSM748256
[202]
GSM748257
[203]
GSM748258
[204]
GSM748259
[205]
GSM748260
[206]
GSM748261
[207]
GSM748262
[208]
GSM748263
[209]
GSM748264
[210]
GSM748265
[211]
GSM748266
[212]
GSM748267
[213]
GSM748268
[214]
GSM748269
[215]
GSM748270
[216]
GSM748271
[217]
GSM748272
[218]
GSM748273
[219]
GSM748274
[220]
GSM748275
[221]
GSM748276
[222]
GSM748277
[223]
GSM748278
[224]
GSM748279
[225]
GSM748280
[226]
GSM748281
[227]
GSM748282
[228]
GSM748283
[229]
GSM748284
[230]
GSM748285
[231]
GSM748286
[232]
GSM748287
[233]
GSM748288
[234]
GSM748291
[235]
GSM748292
[236]
GSM748294
[237]
GSM748295
[238]
GSM748296
[239]
GSM748297
[240]
GSM748298
[241]
GSM748299
[242]
GSM748300
[243]
GSM748301
[244]
GSM748302
[245]
GSM748303
[246]
GSM748304
[247]
GSM748305
[248]
GSM748306
[249]
GSM748307
[250]
GSM748308
[251]
GSM748309
[252]
GSM748310
[253]
GSM748311
[254]
GSM748312
[255]
GSM748313
[256]
GSM748314
[257]
GSM748315
[258]
GSM748316
[259]
GSM748317
[260]
GSM748318
[261]
GSM748319
[262]
GSM748320
[263]
GSM748321
[264]
GSM748323
[265]
GSM748324
[266]
GSM748325
[267]
GSM748326
[268]
GSM748327
[269]
GSM748328
[270]
GSM748329
[271]
GSM748330
[272]
GSM748331
[273]
GSM748332
[274]
GSM748333
[275]
GSM748334
[276]
GSM748335
[277]
GSM748336
[278]
GSM748337
[279]
GSM748338
[280]
GSM748339
[281]
GSM748341
[282]
GSM748342
[283]
GSM748343
[284]
GSM748344
[285]
GSM748345
[286]
GSM748346
[287]
GSM748347
[288]
GSM748348
[289]
GSM748349
[290]
GSM748350
[291]
GSM748351
[292]
GSM748352
[293]
GSM748353
[294]
GSM748354
[295]
GSM748355
[296]
GSM748356
[297]
GSM748357
[298]
GSM748358
[299]
GSM748359
[300]
GSM748360
[301]
GSM748361
[302]
GSM748362
[303]
GSM748363
[304]
GSM748364
[305]
GSM748365
[306]
GSM748366
sample_count
307
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
"Off-context" gene expression in lung cancer identifies a group of metastatic-prone tumors
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:GSE40791
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=GSE40791
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE40791
version
null
note
All datasets utilized or generated during the study are fully available within this article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All datasets utilized or generated during the study are fully available within this article.
access_statement_kind
data_availability_statement
sample_accessions array · 194 items
[0]
GSM1001510
[1]
GSM1001511
[2]
GSM1001512
[3]
GSM1001513
[4]
GSM1001514
[5]
GSM1001515
[6]
GSM1001516
[7]
GSM1001517
[8]
GSM1001518
[9]
GSM1001519
[10]
GSM1001520
[11]
GSM1001521
[12]
GSM1001522
[13]
GSM1001523
[14]
GSM1001524
[15]
GSM1001525
[16]
GSM1001526
[17]
GSM1001527
[18]
GSM1001528
[19]
GSM1001529
[20]
GSM1001530
[21]
GSM1001531
[22]
GSM1001532
[23]
GSM1001533
[24]
GSM1001534
[25]
GSM1001535
[26]
GSM1001536
[27]
GSM1001537
[28]
GSM1001538
[29]
GSM1001539
[30]
GSM1001540
[31]
GSM1001541
[32]
GSM1001542
[33]
GSM1001543
[34]
GSM1001544
[35]
GSM1001545
[36]
GSM1001546
[37]
GSM1001547
[38]
GSM1001548
[39]
GSM1001549
[40]
GSM1001550
[41]
GSM1001551
[42]
GSM1001552
[43]
GSM1001553
[44]
GSM1001554
[45]
GSM1001555
[46]
GSM1001556
[47]
GSM1001557
[48]
GSM1001558
[49]
GSM1001559
[50]
GSM1001560
[51]
GSM1001561
[52]
GSM1001562
[53]
GSM1001563
[54]
GSM1001564
[55]
GSM1001565
[56]
GSM1001566
[57]
GSM1001567
[58]
GSM1001568
[59]
GSM1001569
[60]
GSM1001570
[61]
GSM1001571
[62]
GSM1001572
[63]
GSM1001573
[64]
GSM1001574
[65]
GSM1001575
[66]
GSM1001576
[67]
GSM1001577
[68]
GSM1001578
[69]
GSM1001579
[70]
GSM1001580
[71]
GSM1001581
[72]
GSM1001582
[73]
GSM1001583
[74]
GSM1001584
[75]
GSM1001585
[76]
GSM1001586
[77]
GSM1001587
[78]
GSM1001588
[79]
GSM1001589
[80]
GSM1001590
[81]
GSM1001591
[82]
GSM1001592
[83]
GSM1001593
[84]
GSM1001594
[85]
GSM1001595
[86]
GSM1001596
[87]
GSM1001597
[88]
GSM1001598
[89]
GSM1001599
[90]
GSM1001600
[91]
GSM1001601
[92]
GSM1001602
[93]
GSM1001603
[94]
GSM1001604
[95]
GSM1001605
[96]
GSM1001606
[97]
GSM1001607
[98]
GSM1001608
[99]
GSM1001609
[100]
GSM1001610
[101]
GSM1001611
[102]
GSM1001612
[103]
GSM1001613
[104]
GSM1001614
[105]
GSM1001615
[106]
GSM1001616
[107]
GSM1001617
[108]
GSM1001618
[109]
GSM1001619
[110]
GSM1001620
[111]
GSM1001621
[112]
GSM1001622
[113]
GSM1001623
[114]
GSM1001624
[115]
GSM1001625
[116]
GSM1001626
[117]
GSM1001627
[118]
GSM1001628
[119]
GSM1001629
[120]
GSM1001630
[121]
GSM1001631
[122]
GSM1001632
[123]
GSM1001633
[124]
GSM1001634
[125]
GSM1001635
[126]
GSM1001636
[127]
GSM1001637
[128]
GSM1001638
[129]
GSM1001639
[130]
GSM1001640
[131]
GSM1001641
[132]
GSM1001642
[133]
GSM1001643
[134]
GSM1001644
[135]
GSM1001645
[136]
GSM1001646
[137]
GSM1001647
[138]
GSM1001648
[139]
GSM1001649
[140]
GSM1001650
[141]
GSM1001651
[142]
GSM1001652
[143]
GSM1001653
[144]
GSM1001654
[145]
GSM1001655
[146]
GSM1001656
[147]
GSM1001657
[148]
GSM1001658
[149]
GSM1001659
[150]
GSM1001660
[151]
GSM1001661
[152]
GSM1001662
[153]
GSM1001663
[154]
GSM1001664
[155]
GSM1001665
[156]
GSM1001666
[157]
GSM1001667
[158]
GSM1001668
[159]
GSM1001669
[160]
GSM1001670
[161]
GSM1001671
[162]
GSM1001672
[163]
GSM1001673
[164]
GSM1001674
[165]
GSM1001675
[166]
GSM1001676
[167]
GSM1001677
[168]
GSM1001678
[169]
GSM1001679
[170]
GSM1001680
[171]
GSM1001681
[172]
GSM1001682
[173]
GSM1001683
[174]
GSM1001684
[175]
GSM1001685
[176]
GSM1001686
[177]
GSM1001687
[178]
GSM1001688
[179]
GSM1001689
[180]
GSM1001690
[181]
GSM1001691
[182]
GSM1001692
[183]
GSM1001693
[184]
GSM1001694
[185]
GSM1001695
[186]
GSM1001696
[187]
GSM1001697
[188]
GSM1001698
[189]
GSM1001699
[190]
GSM1001700
[191]
GSM1001701
[192]
GSM1001702
[193]
GSM1001703
sample_count
194
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Usp44 binds centrin to regulate centrosome positioning and suppress tumorigenesis
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 12 items
[0]
asset:data:geo:GSE10072 not downloaded
[1]
asset:data:geo:GSE10072 licence not read
[2]
asset:data:geo:GSE136103 not downloaded
[3]
asset:data:geo:GSE136103 licence not read
[4]
asset:data:geo:GSE19188 not downloaded
[5]
asset:data:geo:GSE19188 licence not read
[6]
asset:data:geo:GSE19804 not downloaded
[7]
asset:data:geo:GSE19804 licence not read
[8]
asset:data:geo:GSE30219 not downloaded
[9]
asset:data:geo:GSE30219 licence not read
[10]
asset:data:geo:GSE40791 not downloaded
[11]
asset:data:geo:GSE40791 licence not read
analysis object · 4 fields
state
partial
methods array · 5 items
[0] object · 10 fields
id
method-1
family
differential_expression
specific
limma_voom
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes.
[1] object · 10 fields
id
method-2
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
[2] object · 10 fields
id
method-3
family
machine_learning
specific
random_forest
label
Machine learning
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
machine_learning_random_forest
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
random forest
[3] object · 10 fields
id
method-4
family
machine_learning
specific
support_vector_machine
label
Machine learning
dsl_operations array · 3 items
[0]
train_classifier
[1]
cross_validate
[2]
roc_auc
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
Support Vector Machine
[4] object · 10 fields
id
method-5
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
0.8
band
high
quote
GO enrichment
targets array · 0 items
gaps array · 1 item
[0]
method.reader_differs_from_extractor
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
true
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom.
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]
GSE10072
[1]
GSE19188
[2]
GSE19804
[3]
GSE30219
[4]
GSE40791
[5]
GSE136103
resolved_accessions array · 6 items
[0]
GSE10072
[1]
GSE19188
[2]
GSE19804
[3]
GSE30219
[4]
GSE40791
[5]
GSE136103
statements array · 1 item
[0]
All datasets utilized or generated during the study are fully available within this article.
basis
The paper names GSE10072, GSE19188, GSE19804, GSE30219, GSE40791, GSE136103 in 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 · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 2 items
[0]
source:pmid:41130017
[1]
data:geo:GSE10072
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE10072
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
2026-11-01T20:03:49Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
17681
completion_tokens
1724
cached_tokens
256
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:41130017
type
paper
label
pmid:41130017
[1] object · 3 fields
id
source:pmid:41130017
type
manuscript
label
PMID 41130017 full text
[2] object · 3 fields
id
data:geo:GSE10072
type
dataset
label
GEO GSE10072
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:41130017
type
paper
label
pmid:41130017
[1] object · 3 fields
id
source:pmid:41130017
type
manuscript
label
PMID 41130017 full text
[2] object · 3 fields
id
data:geo:GSE10072
type
dataset
label
GEO GSE10072
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-41130017
type
extraction
used array · 1 item
[0]
source:pmid:41130017
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE10072
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE10072
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:41130017
parent_hash
sha256:a7b8b8a37c1109d89f94912da257c4379aa0be736e3cf18e74c3b9728e9c2eba
fork_of
null
gaps array · 17 items
[0]
asset:data:geo:GSE10072 licence not read
[1]
asset:data:geo:GSE10072 not downloaded
[2]
asset:data:geo:GSE136103 licence not read
[3]
asset:data:geo:GSE136103 not downloaded
[4]
asset:data:geo:GSE19188 licence not read
[5]
asset:data:geo:GSE19188 not downloaded
[6]
asset:data:geo:GSE19804 licence not read
[7]
asset:data:geo:GSE19804 not downloaded
[8]
asset:data:geo:GSE30219 licence not read
[9]
asset:data:geo:GSE30219 not downloaded
[10]
asset:data:geo:GSE40791 licence not read
[11]
asset:data:geo:GSE40791 not downloaded
[12]
execution.not_run
[13]
method.reader_differs_from_extractor
[14]
review.human_critique
[15]
review.independent_reader
[16]
review.machine_critique
assays array · 4 items
[0] object · 11 fields
role
data_generation
definition_id
scrna_seq
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
unsupported
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 4 items
[0]
study used network pharmacology, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcript
[1]
ogy, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcriptome dataset
[2]
d through PubChem and SwissTargetPrediction. scRNA-seq data were analyzed using Seurat, and key gen
[3]
of lung adenocarcinoma single-cell data The single-cell RNA sequencing data for lung adenocarcinoma were obtained f
order_basis
paper_text_order:466
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
rna_seq
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 4 items
[0]
etwork pharmacology, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcript
[1]
nocarcinoma single-cell data The single-cell RNA sequencing data for lung adenocarcinoma were obtained f
[2]
ol tissues (PMID: 34663877). The single-cell RNA sequencing data were analyzed using R software (version
[3]
EO differential genes (GEOdiff), single-cell RNA sequencing differential genes (scRNA), WGCNA module gen
order_basis
paper_text_order:478
id
assay:2
[2] object · 11 fields
role
data_generation
definition_id
cell_culture
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 2 items
[0]
ive for mycoplasma contamination. Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM; Gibc
[1]
aracterization Human lung cancer cell lines (A549, HCC827, Calu-3, NCI-H2228, NCI-H1975) and t
order_basis
paper_text_order:5504
id
assay:3
[3] object · 11 fields
role
analysis
definition_id
differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes.
order_basis
consumes_earlier_output
id
assay:4
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41130017", "kind": "science-record", "revision": 4, "content_hash": "sha256:6e8c5ae03042be45691da39fb7a05c2b5292cf789e93a6e19556b5f9d908e595", "created_at": "2026-11-01T20:31:11Z", "updated_at": "2026-11-01T22:57:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploring the therapeutic role of thiabendazole in lung adenocarcinoma via network pharmacology and single-cell analysis.", "doi": "10.1016/j.tranon.2025.102548", "pmid": "41130017", "authors": ["Wanghong Qi", "Guoqiu Xu", "Lang Tang", "Chunlin Ye", "Xi Liu"], "journal": "Translational oncology", "year": 2025, "abstract": "BACKGROUND: Lung adenocarcinoma (LUAD) is the leading cause of cancer-related deaths globally, with over 2.2 million new cases in 2020. Despite advances in targeted therapies, challenges such as drug resistance and severe side effects persist. Thiabendazole, an antiparasitic drug, has shown potential anticancer effects in LUAD.\nMETHODS: This study used network pharmacology, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcriptome datasets (GSE10072, GSE19188, GSE19804, GSE30219, GSE40791), and bioinformatics tools to explore Thiabendazole's mechanisms in LUAD. Potential targets were predicted through PubChem and SwissTargetPrediction. scRNA-seq data were analyzed using Seurat, and key genes and pathways were identified via Weighted Gene Co-expression Network Analysis (WGCNA) and multi-omics integration. Diagnostic genes were further screened using LASSO regression, Support Vector Machine (SVM), and random forest (RF) models.\nRESULTS: Single-cell analysis revealed macrophages as key targets of Thiabendazole. Transcriptomic analysis identified 2034 downregulated and 2388 upregulated genes. WGCNA found a core gene module (MEred) strongly correlated with Thiabendazole (r = 0.75, p = 2e-07). Four diagnostic genes-ACE, ALDOA, MME, and PMP22-showed high accuracy (0.982). Thiabendazole also modulated immune cell infiltration, particularly affecting macrophage activity. Molecular docking confirmed stable binding to ACE, ALDOA, and MME.\nCONCLUSION: Thiabendazole demonstrates promising anticancer potential in LUAD, influencing key genes and immune pathways. It may serve as an effective therapeutic agent targeting both cancer cells and the tumor microenvironment.", "claims": [{"id": "claim-method", "statement": "The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41130017", "locator": "sections[6] \"Processing and analysis of transcriptome data\" paragraph 2", "quote": "The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All datasets utilized or generated during the study are fully available within this article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41130017", "locator": "sections[36] \"Data availability\" paragraph 2", "quote": "All datasets utilized or generated during the study are fully available within this article."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Four diagnostic genes—ACE, ALDOA, MME, and PMP22—showed high accuracy (0.982).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41130017", "locator": "sections[0] \"Abstract\" paragraph 9", "quote": "Four diagnostic genes—ACE, ALDOA, MME, and PMP22—showed high accuracy (0.982)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Four diagnostic genes—ACE, ALDOA, MME, and PMP22—showed high accuracy (0.982).", "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:41130017"], "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:GSE10072"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE10072"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41130017", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.tranon.2025.102548", "sha256": "sha256:1fd19a8f48e8384def6f3192a46eb01465c158215a3751e5e8b2e5a2b30a7bd5", "bytes": 66795, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.tranon.2025.102548", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12590012", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE10072", "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=GSE10072", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE10072", "version": null, "note": "All datasets utilized or generated during the study are fully available within this article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All datasets utilized or generated during the study are fully available within this article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM254625", "GSM254626", "GSM254627", "GSM254628", "GSM254629", "GSM254630", "GSM254631", "GSM254632", "GSM254633", "GSM254634", "GSM254635", "GSM254636", "GSM254637", "GSM254638", "GSM254639", "GSM254640", "GSM254641", "GSM254642", "GSM254643", "GSM254644", "GSM254645", "GSM254646", "GSM254647", "GSM254648", "GSM254649", "GSM254650", "GSM254651", "GSM254652", "GSM254653", "GSM254654", "GSM254655", "GSM254656", "GSM254657", "GSM254658", "GSM254659", "GSM254660", "GSM254661", "GSM254662", "GSM254663", "GSM254664", "GSM254665", "GSM254666", "GSM254667", "GSM254668", "GSM254669", "GSM254670", "GSM254671", "GSM254672", "GSM254673", "GSM254674", "GSM254675", "GSM254676", "GSM254677", "GSM254678", "GSM254679", "GSM254680", "GSM254681", "GSM254682", "GSM254683", "GSM254684", "GSM254685", "GSM254686", "GSM254687", "GSM254688", "GSM254689", "GSM254690", "GSM254691", "GSM254692", "GSM254693", "GSM254694", "GSM254695", "GSM254696", "GSM254697", "GSM254698", "GSM254699", "GSM254700", "GSM254701", "GSM254702", "GSM254703", "GSM254704", "GSM254705", "GSM254706", "GSM254707", "GSM254708", "GSM254709", "GSM254710", "GSM254711", "GSM254712", "GSM254713", "GSM254714", "GSM254715", "GSM254716", "GSM254717", "GSM254718", "GSM254719", "GSM254720", "GSM254721", "GSM254722", "GSM254723", "GSM254724", "GSM254725", "GSM254726", "GSM254727", "GSM254728", "GSM254729", "GSM254730", "GSM254731"], "sample_count": 107, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival", "resolution_checked_at": "2026-11-01T15:30:21Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE136103", "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=GSE136103", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE136103", "version": null, "note": "All datasets utilized or generated during the study are fully available within this article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All datasets utilized or generated during the study are fully available within this article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4041150", "GSM4041151", "GSM4041152", "GSM4041153", "GSM4041154", "GSM4041155", "GSM4041156", "GSM4041157", "GSM4041158", "GSM4041159", "GSM4041160", "GSM4041161", "GSM4041162", "GSM4041163", "GSM4041164", "GSM4041165", "GSM4041166", "GSM4041167", "GSM4041168", "GSM4041169", "GSM4041170", "GSM4041171", "GSM4041172", "GSM4041173", "GSM4041174", "GSM4041175"], "sample_count": 26, "group_sizes": null, "group_sizes_basis": null, "platform": "20301;21103", "taxon": "Homo sapiens; Mus musculus", "title": "Resolving the fibrotic niche of human liver cirrhosis using single-cell transcriptomics", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE19188", "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=GSE19188", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE19188", "version": null, "note": "All datasets utilized or generated during the study are fully available within this article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All datasets utilized or generated during the study are fully available within this article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM475656", "GSM475657", "GSM475658", "GSM475659", "GSM475660", "GSM475661", "GSM475662", "GSM475663", "GSM475664", "GSM475665", "GSM475666", "GSM475667", "GSM475668", "GSM475669", "GSM475670", "GSM475671", "GSM475672", "GSM475673", "GSM475674", "GSM475675", "GSM475676", "GSM475677", "GSM475678", "GSM475679", "GSM475680", "GSM475681", "GSM475682", "GSM475683", "GSM475684", "GSM475685", "GSM475686", "GSM475687", "GSM475688", "GSM475689", "GSM475690", "GSM475691", "GSM475692", "GSM475693", "GSM475694", "GSM475695", "GSM475696", "GSM475697", "GSM475698", "GSM475699", "GSM475700", "GSM475701", "GSM475702", "GSM475703", "GSM475704", "GSM475705", "GSM475706", "GSM475707", "GSM475708", "GSM475709", "GSM475710", "GSM475711", "GSM475712", "GSM475713", "GSM475714", "GSM475715", "GSM475716", "GSM475717", "GSM475718", "GSM475719", "GSM475720", "GSM475721", "GSM475722", "GSM475723", "GSM475724", "GSM475725", "GSM475726", "GSM475727", "GSM475728", "GSM475729", "GSM475730", "GSM475731", "GSM475732", "GSM475733", "GSM475734", "GSM475735", "GSM475736", "GSM475737", "GSM475738", "GSM475739", "GSM475740", "GSM475741", "GSM475742", "GSM475743", "GSM475744", "GSM475745", "GSM475746", "GSM475747", "GSM475748", "GSM475749", "GSM475750", "GSM475751", "GSM475752", "GSM475753", "GSM475754", "GSM475755", "GSM475756", "GSM475757", "GSM475758", "GSM475759", "GSM475760", "GSM475761", "GSM475762", "GSM475763", "GSM475764", "GSM475765", "GSM475766", "GSM475767", "GSM475768", "GSM475769", "GSM475770", "GSM475771", "GSM475772", "GSM475773", "GSM475774", "GSM475775", "GSM475776", "GSM475777", "GSM475778", "GSM475779", "GSM475780", "GSM475781", "GSM475782", "GSM475783", "GSM475784", "GSM475785", "GSM475786", "GSM475787", "GSM475788", "GSM475789", "GSM475790", "GSM475791", "GSM475792", "GSM475793", "GSM475794", "GSM475795", "GSM475796", "GSM475797", "GSM475798", "GSM475799", "GSM475800", "GSM475801", "GSM475802", "GSM475803", "GSM475804", "GSM475805", "GSM475806", "GSM475807", "GSM475808", "GSM475809", "GSM475810", "GSM475811"], "sample_count": 156, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Expression data for early stage NSCLC", "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:GSE19804", "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=GSE19804", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE19804", "version": null, "note": "All datasets utilized or generated during the study are fully available within this article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All datasets utilized or generated during the study are fully available within this article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM494556", "GSM494557", "GSM494558", "GSM494559", "GSM494560", "GSM494561", "GSM494562", "GSM494563", "GSM494564", "GSM494565", "GSM494566", "GSM494567", "GSM494568", "GSM494569", "GSM494570", "GSM494571", "GSM494572", "GSM494573", "GSM494574", "GSM494575", "GSM494576", "GSM494577", "GSM494578", "GSM494579", "GSM494580", "GSM494581", "GSM494582", "GSM494583", "GSM494584", "GSM494585", "GSM494586", "GSM494587", "GSM494588", "GSM494589", "GSM494590", "GSM494591", "GSM494592", "GSM494593", "GSM494594", "GSM494595", "GSM494596", "GSM494597", "GSM494598", "GSM494599", "GSM494600", "GSM494601", "GSM494602", "GSM494603", "GSM494604", "GSM494605", "GSM494606", "GSM494607", "GSM494608", "GSM494609", "GSM494610", "GSM494611", "GSM494612", "GSM494613", "GSM494614", "GSM494615", "GSM494616", "GSM494617", "GSM494618", "GSM494619", "GSM494620", "GSM494621", "GSM494622", "GSM494623", "GSM494624", "GSM494625", "GSM494626", "GSM494627", "GSM494628", "GSM494629", "GSM494630", "GSM494631", "GSM494632", "GSM494633", "GSM494634", "GSM494635", "GSM494636", "GSM494637", "GSM494638", "GSM494639", "GSM494640", "GSM494641", "GSM494642", "GSM494643", "GSM494644", "GSM494645", "GSM494646", "GSM494647", "GSM494648", "GSM494649", "GSM494650", "GSM494651", "GSM494652", "GSM494653", "GSM494654", "GSM494655", "GSM494656", "GSM494657", "GSM494658", "GSM494659", "GSM494660", "GSM494661", "GSM494662", "GSM494663", "GSM494664", "GSM494665", "GSM494666", "GSM494667", "GSM494668", "GSM494669", "GSM494670", "GSM494671", "GSM494672", "GSM494673", "GSM494674", "GSM494675"], "sample_count": 120, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Genome-wide screening of transcriptional modulation in non-smoking female lung cancer in Taiwan", "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:GSE30219", "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=GSE30219", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE30219", "version": null, "note": "All datasets utilized or generated during the study are fully available within this article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All datasets utilized or generated during the study are fully available within this article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1465989", "GSM1465990", "GSM1465991", "GSM1465992", "GSM1465993", "GSM1465994", "GSM1465995", "GSM1465996", "GSM1465997", "GSM1465998", "GSM1465999", "GSM748053", "GSM748054", "GSM748055", "GSM748056", "GSM748057", "GSM748058", "GSM748059", "GSM748060", "GSM748061", "GSM748062", "GSM748063", "GSM748064", "GSM748065", "GSM748066", "GSM748067", "GSM748068", "GSM748069", "GSM748070", "GSM748071", "GSM748072", "GSM748073", "GSM748074", "GSM748075", "GSM748076", "GSM748077", "GSM748078", "GSM748079", "GSM748080", "GSM748081", "GSM748083", "GSM748084", "GSM748085", "GSM748086", "GSM748087", "GSM748088", "GSM748089", "GSM748090", "GSM748091", "GSM748092", "GSM748093", "GSM748094", "GSM748095", "GSM748096", "GSM748097", "GSM748098", "GSM748099", "GSM748100", "GSM748101", "GSM748102", "GSM748103", "GSM748104", "GSM748105", "GSM748106", "GSM748107", "GSM748108", "GSM748109", "GSM748110", "GSM748111", "GSM748112", "GSM748113", "GSM748115", "GSM748116", "GSM748117", "GSM748118", "GSM748119", "GSM748120", "GSM748121", "GSM748122", "GSM748123", "GSM748124", "GSM748125", "GSM748126", "GSM748127", "GSM748128", "GSM748129", "GSM748130", "GSM748131", "GSM748132", "GSM748133", "GSM748134", "GSM748135", "GSM748136", "GSM748137", "GSM748138", "GSM748139", "GSM748140", "GSM748141", "GSM748142", "GSM748143", "GSM748144", "GSM748145", "GSM748146", "GSM748147", "GSM748148", "GSM748149", "GSM748150", "GSM748151", "GSM748152", "GSM748153", "GSM748154", "GSM748155", "GSM748156", "GSM748157", "GSM748158", "GSM748159", "GSM748160", "GSM748161", "GSM748162", "GSM748163", "GSM748164", "GSM748165", "GSM748166", "GSM748167", "GSM748168", "GSM748169", "GSM748170", "GSM748171", "GSM748172", "GSM748173", "GSM748174", "GSM748175", "GSM748176", "GSM748177", "GSM748178", "GSM748179", "GSM748180", "GSM748181", "GSM748182", "GSM748183", "GSM748184", "GSM748185", "GSM748186", "GSM748187", "GSM748188", "GSM748189", "GSM748191", "GSM748192", "GSM748193", "GSM748195", "GSM748196", "GSM748197", "GSM748198", "GSM748199", "GSM748200", "GSM748201", "GSM748202", "GSM748203", "GSM748206", "GSM748207", "GSM748209", "GSM748210", "GSM748211", "GSM748212", "GSM748213", "GSM748214", "GSM748215", "GSM748216", "GSM748217", "GSM748218", "GSM748219", "GSM748220", "GSM748221", "GSM748222", "GSM748223", "GSM748224", "GSM748225", "GSM748226", "GSM748227", "GSM748228", "GSM748229", "GSM748232", "GSM748233", "GSM748234", "GSM748235", "GSM748239", "GSM748240", "GSM748242", "GSM748243", "GSM748244", "GSM748245", "GSM748246", "GSM748247", "GSM748248", "GSM748249", "GSM748250", "GSM748251", "GSM748252", "GSM748253", "GSM748254", "GSM748255", "GSM748256", "GSM748257", "GSM748258", "GSM748259", "GSM748260", "GSM748261", "GSM748262", "GSM748263", "GSM748264", "GSM748265", "GSM748266", "GSM748267", "GSM748268", "GSM748269", "GSM748270", "GSM748271", "GSM748272", "GSM748273", "GSM748274", "GSM748275", "GSM748276", "GSM748277", "GSM748278", "GSM748279", "GSM748280", "GSM748281", "GSM748282", "GSM748283", "GSM748284", "GSM748285", "GSM748286", "GSM748287", "GSM748288", "GSM748291", "GSM748292", "GSM748294", "GSM748295", "GSM748296", "GSM748297", "GSM748298", "GSM748299", "GSM748300", "GSM748301", "GSM748302", "GSM748303", "GSM748304", "GSM748305", "GSM748306", "GSM748307", "GSM748308", "GSM748309", "GSM748310", "GSM748311", "GSM748312", "GSM748313", "GSM748314", "GSM748315", "GSM748316", "GSM748317", "GSM748318", "GSM748319", "GSM748320", "GSM748321", "GSM748323", "GSM748324", "GSM748325", "GSM748326", "GSM748327", "GSM748328", "GSM748329", "GSM748330", "GSM748331", "GSM748332", "GSM748333", "GSM748334", "GSM748335", "GSM748336", "GSM748337", "GSM748338", "GSM748339", "GSM748341", "GSM748342", "GSM748343", "GSM748344", "GSM748345", "GSM748346", "GSM748347", "GSM748348", "GSM748349", "GSM748350", "GSM748351", "GSM748352", "GSM748353", "GSM748354", "GSM748355", "GSM748356", "GSM748357", "GSM748358", "GSM748359", "GSM748360", "GSM748361", "GSM748362", "GSM748363", "GSM748364", "GSM748365", "GSM748366"], "sample_count": 307, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "\"Off-context\" gene expression in lung cancer identifies a group of metastatic-prone tumors", "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:GSE40791", "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=GSE40791", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE40791", "version": null, "note": "All datasets utilized or generated during the study are fully available within this article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All datasets utilized or generated during the study are fully available within this article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1001510", "GSM1001511", "GSM1001512", "GSM1001513", "GSM1001514", "GSM1001515", "GSM1001516", "GSM1001517", "GSM1001518", "GSM1001519", "GSM1001520", "GSM1001521", "GSM1001522", "GSM1001523", "GSM1001524", "GSM1001525", "GSM1001526", "GSM1001527", "GSM1001528", "GSM1001529", "GSM1001530", "GSM1001531", "GSM1001532", "GSM1001533", "GSM1001534", "GSM1001535", "GSM1001536", "GSM1001537", "GSM1001538", "GSM1001539", "GSM1001540", "GSM1001541", "GSM1001542", "GSM1001543", "GSM1001544", "GSM1001545", "GSM1001546", "GSM1001547", "GSM1001548", "GSM1001549", "GSM1001550", "GSM1001551", "GSM1001552", "GSM1001553", "GSM1001554", "GSM1001555", "GSM1001556", "GSM1001557", "GSM1001558", "GSM1001559", "GSM1001560", "GSM1001561", "GSM1001562", "GSM1001563", "GSM1001564", "GSM1001565", "GSM1001566", "GSM1001567", "GSM1001568", "GSM1001569", "GSM1001570", "GSM1001571", "GSM1001572", "GSM1001573", "GSM1001574", "GSM1001575", "GSM1001576", "GSM1001577", "GSM1001578", "GSM1001579", "GSM1001580", "GSM1001581", "GSM1001582", "GSM1001583", "GSM1001584", "GSM1001585", "GSM1001586", "GSM1001587", "GSM1001588", "GSM1001589", "GSM1001590", "GSM1001591", "GSM1001592", "GSM1001593", "GSM1001594", "GSM1001595", "GSM1001596", "GSM1001597", "GSM1001598", "GSM1001599", "GSM1001600", "GSM1001601", "GSM1001602", "GSM1001603", "GSM1001604", "GSM1001605", "GSM1001606", "GSM1001607", "GSM1001608", "GSM1001609", "GSM1001610", "GSM1001611", "GSM1001612", "GSM1001613", "GSM1001614", "GSM1001615", "GSM1001616", "GSM1001617", "GSM1001618", "GSM1001619", "GSM1001620", "GSM1001621", "GSM1001622", "GSM1001623", "GSM1001624", "GSM1001625", "GSM1001626", "GSM1001627", "GSM1001628", "GSM1001629", "GSM1001630", "GSM1001631", "GSM1001632", "GSM1001633", "GSM1001634", "GSM1001635", "GSM1001636", "GSM1001637", "GSM1001638", "GSM1001639", "GSM1001640", "GSM1001641", "GSM1001642", "GSM1001643", "GSM1001644", "GSM1001645", "GSM1001646", "GSM1001647", "GSM1001648", "GSM1001649", "GSM1001650", "GSM1001651", "GSM1001652", "GSM1001653", "GSM1001654", "GSM1001655", "GSM1001656", "GSM1001657", "GSM1001658", "GSM1001659", "GSM1001660", "GSM1001661", "GSM1001662", "GSM1001663", "GSM1001664", "GSM1001665", "GSM1001666", "GSM1001667", "GSM1001668", "GSM1001669", "GSM1001670", "GSM1001671", "GSM1001672", "GSM1001673", "GSM1001674", "GSM1001675", "GSM1001676", "GSM1001677", "GSM1001678", "GSM1001679", "GSM1001680", "GSM1001681", "GSM1001682", "GSM1001683", "GSM1001684", "GSM1001685", "GSM1001686", "GSM1001687", "GSM1001688", "GSM1001689", "GSM1001690", "GSM1001691", "GSM1001692", "GSM1001693", "GSM1001694", "GSM1001695", "GSM1001696", "GSM1001697", "GSM1001698", "GSM1001699", "GSM1001700", "GSM1001701", "GSM1001702", "GSM1001703"], "sample_count": 194, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Usp44 binds centrin to regulate centrosome positioning and suppress tumorigenesis", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE10072 not downloaded", "asset:data:geo:GSE10072 licence not read", "asset:data:geo:GSE136103 not downloaded", "asset:data:geo:GSE136103 licence not read", "asset:data:geo:GSE19188 not downloaded", "asset:data:geo:GSE19188 licence not read", "asset:data:geo:GSE19804 not downloaded", "asset:data:geo:GSE19804 licence not read", "asset:data:geo:GSE30219 not downloaded", "asset:data:geo:GSE30219 licence not read", "asset:data:geo:GSE40791 not downloaded", "asset:data:geo:GSE40791 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-4", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "Support Vector Machine"}}, {"id": "method-5", "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": 0.8, "band": "high", "quote": "GO enrichment"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "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": ["GSE10072", "GSE19188", "GSE19804", "GSE30219", "GSE40791", "GSE136103"], "resolved_accessions": ["GSE10072", "GSE19188", "GSE19804", "GSE30219", "GSE40791", "GSE136103"], "statements": ["All datasets utilized or generated during the study are fully available within this article."], "basis": "The paper names GSE10072, GSE19188, GSE19804, GSE30219, GSE40791, GSE136103 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:41130017", "data:geo:GSE10072"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE10072"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T20:03:49Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 17681, "completion_tokens": 1724, "cached_tokens": 256}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:41130017", "type": "paper", "label": "pmid:41130017"}, {"id": "source:pmid:41130017", "type": "manuscript", "label": "PMID 41130017 full text"}, {"id": "data:geo:GSE10072", "type": "dataset", "label": "GEO GSE10072"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:41130017", "type": "paper", "label": "pmid:41130017"}, {"id": "source:pmid:41130017", "type": "manuscript", "label": "PMID 41130017 full text"}, {"id": "data:geo:GSE10072", "type": "dataset", "label": "GEO GSE10072"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-41130017", "type": "extraction", "used": ["source:pmid:41130017"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE10072", "type": "accession_resolution", "used": ["data:geo:GSE10072"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:41130017", "parent_hash": "sha256:a7b8b8a37c1109d89f94912da257c4379aa0be736e3cf18e74c3b9728e9c2eba", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE10072 licence not read", "asset:data:geo:GSE10072 not downloaded", "asset:data:geo:GSE136103 licence not read", "asset:data:geo:GSE136103 not downloaded", "asset:data:geo:GSE19188 licence not read", "asset:data:geo:GSE19188 not downloaded", "asset:data:geo:GSE19804 licence not read", "asset:data:geo:GSE19804 not downloaded", "asset:data:geo:GSE30219 licence not read", "asset:data:geo:GSE30219 not downloaded", "asset:data:geo:GSE40791 licence not read", "asset:data:geo:GSE40791 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["study used network pharmacology, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcript", "ogy, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcriptome dataset", "d through PubChem and SwissTargetPrediction. scRNA-seq data were analyzed using Seurat, and key gen", "of lung adenocarcinoma single-cell data The single-cell RNA sequencing data for lung adenocarcinoma were obtained f"], "order_basis": "paper_text_order:466", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["etwork pharmacology, integrating single-cell RNA sequencing (scRNA-seq) data (GSE136103), GEO transcript", "nocarcinoma single-cell data The single-cell RNA sequencing data for lung adenocarcinoma were obtained f", "ol tissues (PMID: 34663877). The single-cell RNA sequencing data were analyzed using R software (version", "EO differential genes (GEOdiff), single-cell RNA sequencing differential genes (scRNA), WGCNA module gen"], "order_basis": "paper_text_order:478", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ive for mycoplasma contamination. Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM; Gibc", "aracterization Human lung cancer cell lines (A549, HCC827, Calu-3, NCI-H2228, NCI-H1975) and t"], "order_basis": "paper_text_order:5504", "id": "assay:3"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The limma package was used to analyze the differentially expressed genes between lung adenocarcinoma patients and control patients in the GEO database, and a volcano plot was drawn to show the distribution of differentially expressed genes."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}