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

pmid:36291567

Identification of the Thyrotropin-Releasing Hormone (TRH) as a Novel Biomarker in the Prognosis for Acute Myeloid Leukemia.

Yan Gao · Jia-Fan Zhou · Jia-Ying Mao · Lu Jiang · Xue-Ping Li

Biomolecules · 2022 doi:10.3390/biom12101359

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:36291567
kind
science-record
content_hash
sha256:e70e5407f5b566dc868ee9b4a7633b8021b76c369cbf3e8607b1510e9899f5fa
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T18:15:42Z
updated_at
2026-11-01T22:50:28Z
generator object · 2 fields
name
corpus-assay-engine
run_id
reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
Identification of the Thyrotropin-Releasing Hormone (TRH) as a Novel Biomarker in the Prognosis for Acute Myeloid Leukemia.
doi
10.3390/biom12101359
pmid
36291567
authors array · 5 items
[0]
Yan Gao
[1]
Jia-Fan Zhou
[2]
Jia-Ying Mao
[3]
Lu Jiang
[4]
Xue-Ping Li
journal
Biomolecules
year
2022
abstract
Acute myeloid leukemia (AML) is a biologically and genetically heterogeneous hematological malignance with an unsatisfactory risk stratification system. Recently, through the novel single-cell RNA sequencing technology, we revealed heterogeneous leukemia myeloblasts in RUNX1-RUNX1T1 AML. Thyrotropin-releasing hormone (TRH), as biomarkers of CD34+CD117bri myeloblasts, were found to be prognostic in RUNX1-RUNX1T1 AML. However, the clinical and genetic features of TRH in AML patients are poorly understood. Here, with data from TCGA AML, TRH was found to be downregulated in patients older than 60 years old, with DNMT3A and NPM1 mutations, while overexpressed in patients with KIT mutations. This was further validated in three other cohorts of primary AML including Beat AML (n = 223), GSE6891 (n = 461), and GSE17855 (n = 237). Furthermore, we demonstrated that the expression of TRH in AML could be used to improve the ELN 2017 risk stratification system. In conclusion, our preliminary analysis revealed that TRH, a novel biomarker for AML patients, could be used to evaluate the survival of AML.
claims array · 3 items
[0] object · 6 fields
id
claim-method
statement
The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value.
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:36291567
locator
sections[7] "2.5. Statistical Analysis" paragraph 2
quote
The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value.
state
complete
[1] object · 6 fields
id
claim-data-access
statement
Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:36291567
locator
sections[22] "Data Availability Statement" paragraph 2
quote
Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).
state
complete
[2] object · 6 fields
id
claim-target-result
statement
Higher TRH expression was independently associated with better overall survival in the TCGA AML cohort and could refine the ELN 2017 risk stratification system.
kind
quantitative
target object · 4 fields
value
95
unit
per cent
tolerance
null
source
The multivariate analysis showed that age (HR, 1.035; 95%CI, 1.019–1.051; p < 0.001), WBC count (HR, 1.007; 95%CI, 1.002–1.011; p = 0.008), TRH expression (HR, 0.910; 95%CI, 0.840–0.987; p = 0.022), and ELN 2017 risk (HR, 1.655; 95%CI, 1.254–2.185; p < 0.001) remained independent prognostic factors for OS.
evidence array · 2 items
[0] object · 3 fields
asset
source:pmid:36291567
locator
sections[14] "3.6. Improvement of Prognostic Stratification for the ELN Risk System" paragraph 2
quote
The multivariate analysis showed that age (HR, 1.035; 95%CI, 1.019–1.051; p < 0.001), WBC count (HR, 1.007; 95%CI, 1.002–1.011; p = 0.008), TRH expression (HR, 0.910; 95%CI, 0.840–0.987; p = 0.022), and ELN 2017 risk (HR, 1.655; 95%CI, 1.254–2.185; p < 0.001) remained independent prognostic factors for OS.
[1] object · 3 fields
asset
source:pmid:36291567
locator
sections[14] "3.6. Improvement of Prognostic Stratification for the ELN Risk System" paragraph 2
quote
Collectively, these data indicate that the expression of TRH could be used to further stratify AML patients on the basis of the ELN 2017 risk system.
state
complete
gaps array · 0 items
experiment object · 8 fields
state
complete
objective
Higher TRH expression was independently associated with better overall survival in the TCGA AML cohort and could refine the ELN 2017 risk stratification system.
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:36291567
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:GSE17855
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:GSE17855
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 · 3 items
[0] object · 15 fields
id
source:pmid:36291567
role
manuscript
format
xml
media_type
application/xml
uri
https://doi.org/10.3390/biom12101359
sha256
sha256:5a747b6ff07893db2de40fd5011e715b66f11ae4abcca5903b5c2bded42bbff5
bytes
38743
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
10.3390/biom12101359
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
PMC9599642
source
europe_pmc_fulltext
coverage
whole_body
text_hash_scope
rendered_section_body
[1] object · 15 fields
id
data:geo:GSE17855
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=GSE17855
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE17855
version
null
note
Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).
access_statement_kind
data_availability_statement
sample_accessions array · 237 items
[0]
GSM445920
[1]
GSM445921
[2]
GSM445922
[3]
GSM445923
[4]
GSM445924
[5]
GSM445925
[6]
GSM445926
[7]
GSM445927
[8]
GSM445928
[9]
GSM445929
[10]
GSM445930
[11]
GSM445931
[12]
GSM445932
[13]
GSM445933
[14]
GSM445934
[15]
GSM445935
[16]
GSM445936
[17]
GSM445937
[18]
GSM445938
[19]
GSM445939
[20]
GSM445940
[21]
GSM445941
[22]
GSM445942
[23]
GSM445943
[24]
GSM445944
[25]
GSM445945
[26]
GSM445946
[27]
GSM445947
[28]
GSM445948
[29]
GSM445949
[30]
GSM445950
[31]
GSM445951
[32]
GSM445952
[33]
GSM445953
[34]
GSM445954
[35]
GSM445955
[36]
GSM445956
[37]
GSM445957
[38]
GSM445958
[39]
GSM445959
[40]
GSM445960
[41]
GSM445961
[42]
GSM445962
[43]
GSM445963
[44]
GSM445964
[45]
GSM445965
[46]
GSM445966
[47]
GSM445967
[48]
GSM445968
[49]
GSM445969
[50]
GSM445970
[51]
GSM445971
[52]
GSM445972
[53]
GSM445973
[54]
GSM445974
[55]
GSM445975
[56]
GSM445976
[57]
GSM445977
[58]
GSM445978
[59]
GSM445979
[60]
GSM445980
[61]
GSM445981
[62]
GSM445982
[63]
GSM445983
[64]
GSM445984
[65]
GSM445985
[66]
GSM445986
[67]
GSM445987
[68]
GSM445988
[69]
GSM445989
[70]
GSM445990
[71]
GSM445991
[72]
GSM445992
[73]
GSM445993
[74]
GSM445994
[75]
GSM445995
[76]
GSM445996
[77]
GSM445997
[78]
GSM445998
[79]
GSM445999
[80]
GSM446000
[81]
GSM446001
[82]
GSM446002
[83]
GSM446003
[84]
GSM446004
[85]
GSM446005
[86]
GSM446006
[87]
GSM446007
[88]
GSM446008
[89]
GSM446009
[90]
GSM446010
[91]
GSM446011
[92]
GSM446012
[93]
GSM446013
[94]
GSM446014
[95]
GSM446015
[96]
GSM446016
[97]
GSM446017
[98]
GSM446018
[99]
GSM446019
[100]
GSM446020
[101]
GSM446021
[102]
GSM446022
[103]
GSM446023
[104]
GSM446024
[105]
GSM446025
[106]
GSM446026
[107]
GSM446027
[108]
GSM446028
[109]
GSM446029
[110]
GSM446030
[111]
GSM446031
[112]
GSM446032
[113]
GSM446033
[114]
GSM446034
[115]
GSM446035
[116]
GSM446036
[117]
GSM446037
[118]
GSM446038
[119]
GSM446039
[120]
GSM446040
[121]
GSM446041
[122]
GSM446042
[123]
GSM446043
[124]
GSM446044
[125]
GSM446045
[126]
GSM446046
[127]
GSM446047
[128]
GSM446048
[129]
GSM446049
[130]
GSM446050
[131]
GSM446051
[132]
GSM446052
[133]
GSM446053
[134]
GSM446054
[135]
GSM446055
[136]
GSM446056
[137]
GSM446057
[138]
GSM446058
[139]
GSM446059
[140]
GSM446060
[141]
GSM446061
[142]
GSM446062
[143]
GSM446063
[144]
GSM446064
[145]
GSM446065
[146]
GSM446066
[147]
GSM446067
[148]
GSM446068
[149]
GSM446069
[150]
GSM446070
[151]
GSM446071
[152]
GSM446072
[153]
GSM446073
[154]
GSM446074
[155]
GSM446075
[156]
GSM446076
[157]
GSM446077
[158]
GSM446078
[159]
GSM446079
[160]
GSM446080
[161]
GSM446081
[162]
GSM446082
[163]
GSM446083
[164]
GSM446084
[165]
GSM446085
[166]
GSM446086
[167]
GSM446087
[168]
GSM446088
[169]
GSM446089
[170]
GSM446090
[171]
GSM446091
[172]
GSM446092
[173]
GSM446093
[174]
GSM446094
[175]
GSM446095
[176]
GSM446096
[177]
GSM446097
[178]
GSM446098
[179]
GSM446099
[180]
GSM446100
[181]
GSM446101
[182]
GSM446102
[183]
GSM446103
[184]
GSM446104
[185]
GSM446105
[186]
GSM446106
[187]
GSM446107
[188]
GSM446108
[189]
GSM446109
[190]
GSM446110
[191]
GSM446111
[192]
GSM446112
[193]
GSM446113
[194]
GSM446114
[195]
GSM446115
[196]
GSM446116
[197]
GSM446117
[198]
GSM446118
[199]
GSM446119
[200]
GSM446120
[201]
GSM446121
[202]
GSM446122
[203]
GSM446123
[204]
GSM446124
[205]
GSM446125
[206]
GSM446126
[207]
GSM446127
[208]
GSM446128
[209]
GSM446129
[210]
GSM446130
[211]
GSM446131
[212]
GSM446132
[213]
GSM446133
[214]
GSM446134
[215]
GSM446135
[216]
GSM446136
[217]
GSM446137
[218]
GSM446138
[219]
GSM446139
[220]
GSM446140
[221]
GSM446141
[222]
GSM446142
[223]
GSM446143
[224]
GSM446144
[225]
GSM446145
[226]
GSM446146
[227]
GSM446147
[228]
GSM446148
[229]
GSM446149
[230]
GSM446150
[231]
GSM446151
[232]
GSM446152
[233]
GSM446153
[234]
GSM446154
[235]
GSM446155
[236]
GSM446156
sample_count
237
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Expression data from pediatric AML patients
resolution_checked_at
2026-11-01T18:46:34Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[2] object · 15 fields
id
data:geo:GSE6891
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=GSE6891
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE6891
version
null
note
Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).
access_statement_kind
data_availability_statement
sample_accessions array · 537 items
[0]
GSM158711
[1]
GSM158712
[2]
GSM158713
[3]
GSM158714
[4]
GSM158715
[5]
GSM158716
[6]
GSM158717
[7]
GSM158718
[8]
GSM158719
[9]
GSM158720
[10]
GSM158721
[11]
GSM158722
[12]
GSM158723
[13]
GSM158724
[14]
GSM158725
[15]
GSM158726
[16]
GSM158727
[17]
GSM158728
[18]
GSM158729
[19]
GSM158730
[20]
GSM158731
[21]
GSM158732
[22]
GSM158733
[23]
GSM158734
[24]
GSM158735
[25]
GSM158736
[26]
GSM158737
[27]
GSM158738
[28]
GSM158739
[29]
GSM158740
[30]
GSM158741
[31]
GSM158742
[32]
GSM158743
[33]
GSM158744
[34]
GSM158745
[35]
GSM158746
[36]
GSM158747
[37]
GSM158748
[38]
GSM158749
[39]
GSM158750
[40]
GSM158751
[41]
GSM158752
[42]
GSM158753
[43]
GSM158754
[44]
GSM158755
[45]
GSM158756
[46]
GSM158757
[47]
GSM158758
[48]
GSM158759
[49]
GSM158760
[50]
GSM158761
[51]
GSM158762
[52]
GSM158763
[53]
GSM158764
[54]
GSM158765
[55]
GSM158766
[56]
GSM158767
[57]
GSM158768
[58]
GSM158769
[59]
GSM158770
[60]
GSM158771
[61]
GSM158772
[62]
GSM158773
[63]
GSM158774
[64]
GSM158775
[65]
GSM158776
[66]
GSM158777
[67]
GSM158778
[68]
GSM158779
[69]
GSM158780
[70]
GSM158781
[71]
GSM158782
[72]
GSM158783
[73]
GSM158784
[74]
GSM158785
[75]
GSM158786
[76]
GSM158787
[77]
GSM158788
[78]
GSM158789
[79]
GSM158790
[80]
GSM158791
[81]
GSM158792
[82]
GSM158793
[83]
GSM158794
[84]
GSM158795
[85]
GSM158796
[86]
GSM158797
[87]
GSM158798
[88]
GSM158799
[89]
GSM158800
[90]
GSM158801
[91]
GSM158802
[92]
GSM158803
[93]
GSM158804
[94]
GSM158805
[95]
GSM158806
[96]
GSM158807
[97]
GSM158808
[98]
GSM158809
[99]
GSM158810
[100]
GSM158811
[101]
GSM158812
[102]
GSM158813
[103]
GSM158814
[104]
GSM158815
[105]
GSM158816
[106]
GSM158817
[107]
GSM158818
[108]
GSM158819
[109]
GSM158820
[110]
GSM158821
[111]
GSM158822
[112]
GSM158823
[113]
GSM158824
[114]
GSM158825
[115]
GSM158826
[116]
GSM158827
[117]
GSM158828
[118]
GSM158829
[119]
GSM158830
[120]
GSM158831
[121]
GSM158832
[122]
GSM158833
[123]
GSM158834
[124]
GSM158835
[125]
GSM158836
[126]
GSM158837
[127]
GSM158838
[128]
GSM158839
[129]
GSM158840
[130]
GSM158841
[131]
GSM158842
[132]
GSM158843
[133]
GSM158844
[134]
GSM158845
[135]
GSM158846
[136]
GSM158847
[137]
GSM158848
[138]
GSM158849
[139]
GSM158850
[140]
GSM158851
[141]
GSM158852
[142]
GSM158853
[143]
GSM158854
[144]
GSM158855
[145]
GSM158856
[146]
GSM158857
[147]
GSM158858
[148]
GSM158859
[149]
GSM158860
[150]
GSM158861
[151]
GSM158862
[152]
GSM158863
[153]
GSM158864
[154]
GSM158865
[155]
GSM158866
[156]
GSM158867
[157]
GSM158868
[158]
GSM158869
[159]
GSM158870
[160]
GSM158871
[161]
GSM158872
[162]
GSM158873
[163]
GSM158874
[164]
GSM158875
[165]
GSM158876
[166]
GSM158877
[167]
GSM158878
[168]
GSM158879
[169]
GSM158880
[170]
GSM158881
[171]
GSM158882
[172]
GSM158883
[173]
GSM158884
[174]
GSM158885
[175]
GSM158886
[176]
GSM158887
[177]
GSM158888
[178]
GSM158889
[179]
GSM158890
[180]
GSM158891
[181]
GSM158892
[182]
GSM158893
[183]
GSM158894
[184]
GSM158895
[185]
GSM158896
[186]
GSM158897
[187]
GSM158898
[188]
GSM158899
[189]
GSM158900
[190]
GSM158901
[191]
GSM158902
[192]
GSM158903
[193]
GSM158904
[194]
GSM158905
[195]
GSM158906
[196]
GSM158907
[197]
GSM158908
[198]
GSM158909
[199]
GSM158910
[200]
GSM158911
[201]
GSM158912
[202]
GSM158913
[203]
GSM158914
[204]
GSM158915
[205]
GSM158916
[206]
GSM158917
[207]
GSM158918
[208]
GSM158919
[209]
GSM158920
[210]
GSM158921
[211]
GSM158922
[212]
GSM158923
[213]
GSM158924
[214]
GSM158925
[215]
GSM158926
[216]
GSM158927
[217]
GSM158928
[218]
GSM158929
[219]
GSM158930
[220]
GSM158931
[221]
GSM158932
[222]
GSM158933
[223]
GSM158934
[224]
GSM158935
[225]
GSM158936
[226]
GSM158937
[227]
GSM158938
[228]
GSM158939
[229]
GSM158940
[230]
GSM158941
[231]
GSM158942
[232]
GSM158943
[233]
GSM158944
[234]
GSM158945
[235]
GSM158946
[236]
GSM158947
[237]
GSM158948
[238]
GSM158949
[239]
GSM158950
[240]
GSM158951
[241]
GSM158952
[242]
GSM158953
[243]
GSM158954
[244]
GSM158955
[245]
GSM158956
[246]
GSM158957
[247]
GSM158958
[248]
GSM158959
[249]
GSM158960
[250]
GSM158961
[251]
GSM158962
[252]
GSM158963
[253]
GSM158964
[254]
GSM158965
[255]
GSM158966
[256]
GSM158967
[257]
GSM158968
[258]
GSM158969
[259]
GSM158970
[260]
GSM158971
[261]
GSM158972
[262]
GSM158973
[263]
GSM158974
[264]
GSM158975
[265]
GSM158976
[266]
GSM158977
[267]
GSM158978
[268]
GSM158979
[269]
GSM158980
[270]
GSM158981
[271]
GSM158982
[272]
GSM158983
[273]
GSM158984
[274]
GSM158985
[275]
GSM158986
[276]
GSM158987
[277]
GSM158988
[278]
GSM158989
[279]
GSM158990
[280]
GSM158991
[281]
GSM158992
[282]
GSM158993
[283]
GSM158994
[284]
GSM158995
[285]
GSM158996
[286]
GSM158997
[287]
GSM158998
[288]
GSM158999
[289]
GSM159000
[290]
GSM159001
[291]
GSM159002
[292]
GSM159003
[293]
GSM159004
[294]
GSM159005
[295]
GSM159006
[296]
GSM159007
[297]
GSM159008
[298]
GSM159009
[299]
GSM159010
[300]
GSM159011
[301]
GSM159012
[302]
GSM159013
[303]
GSM159014
[304]
GSM159015
[305]
GSM159016
[306]
GSM159017
[307]
GSM159018
[308]
GSM159019
[309]
GSM159020
[310]
GSM159021
[311]
GSM159022
[312]
GSM159023
[313]
GSM159024
[314]
GSM159025
[315]
GSM159026
[316]
GSM159027
[317]
GSM159028
[318]
GSM159029
[319]
GSM159030
[320]
GSM159031
[321]
GSM159032
[322]
GSM159033
[323]
GSM159034
[324]
GSM159035
[325]
GSM159036
[326]
GSM159037
[327]
GSM159038
[328]
GSM159039
[329]
GSM159040
[330]
GSM159041
[331]
GSM159042
[332]
GSM159043
[333]
GSM159044
[334]
GSM159045
[335]
GSM159046
[336]
GSM159047
[337]
GSM159048
[338]
GSM159049
[339]
GSM159050
[340]
GSM159051
[341]
GSM159052
[342]
GSM159053
[343]
GSM159054
[344]
GSM159055
[345]
GSM159056
[346]
GSM159057
[347]
GSM159058
[348]
GSM159059
[349]
GSM159060
[350]
GSM159061
[351]
GSM159062
[352]
GSM159063
[353]
GSM159064
[354]
GSM159065
[355]
GSM159066
[356]
GSM159067
[357]
GSM159068
[358]
GSM159069
[359]
GSM159070
[360]
GSM159071
[361]
GSM159072
[362]
GSM159073
[363]
GSM159074
[364]
GSM159075
[365]
GSM159076
[366]
GSM159077
[367]
GSM159078
[368]
GSM159079
[369]
GSM159080
[370]
GSM159081
[371]
GSM159082
[372]
GSM159083
[373]
GSM159084
[374]
GSM159085
[375]
GSM159086
[376]
GSM159087
[377]
GSM159088
[378]
GSM159089
[379]
GSM159090
[380]
GSM159091
[381]
GSM159092
[382]
GSM159093
[383]
GSM159094
[384]
GSM159095
[385]
GSM159096
[386]
GSM159097
[387]
GSM159098
[388]
GSM159099
[389]
GSM159100
[390]
GSM159101
[391]
GSM159102
[392]
GSM159103
[393]
GSM159104
[394]
GSM159105
[395]
GSM159106
[396]
GSM159107
[397]
GSM159108
[398]
GSM159109
[399]
GSM159110
[400]
GSM159111
[401]
GSM159112
[402]
GSM159113
[403]
GSM159114
[404]
GSM159115
[405]
GSM159116
[406]
GSM159117
[407]
GSM159118
[408]
GSM159119
[409]
GSM159120
[410]
GSM159121
[411]
GSM159122
[412]
GSM159123
[413]
GSM159124
[414]
GSM159125
[415]
GSM159126
[416]
GSM159127
[417]
GSM159128
[418]
GSM159129
[419]
GSM159130
[420]
GSM159131
[421]
GSM159132
[422]
GSM159133
[423]
GSM159134
[424]
GSM159135
[425]
GSM159136
[426]
GSM159137
[427]
GSM159138
[428]
GSM159139
[429]
GSM159140
[430]
GSM159141
[431]
GSM159142
[432]
GSM159143
[433]
GSM159144
[434]
GSM159145
[435]
GSM159146
[436]
GSM159147
[437]
GSM159148
[438]
GSM159149
[439]
GSM159150
[440]
GSM159151
[441]
GSM159152
[442]
GSM159153
[443]
GSM159154
[444]
GSM159155
[445]
GSM159156
[446]
GSM159157
[447]
GSM159158
[448]
GSM159159
[449]
GSM159160
[450]
GSM159161
[451]
GSM159162
[452]
GSM159163
[453]
GSM159164
[454]
GSM159165
[455]
GSM159166
[456]
GSM159167
[457]
GSM159168
[458]
GSM159169
[459]
GSM159170
[460]
GSM159171
[461]
GSM768679
[462]
GSM768680
[463]
GSM768681
[464]
GSM768682
[465]
GSM768683
[466]
GSM768684
[467]
GSM768685
[468]
GSM768686
[469]
GSM768687
[470]
GSM768688
[471]
GSM768689
[472]
GSM768690
[473]
GSM768691
[474]
GSM768692
[475]
GSM768693
[476]
GSM768694
[477]
GSM768695
[478]
GSM768696
[479]
GSM768697
[480]
GSM768698
[481]
GSM768699
[482]
GSM768700
[483]
GSM768701
[484]
GSM768702
[485]
GSM768703
[486]
GSM768704
[487]
GSM768705
[488]
GSM768706
[489]
GSM768707
[490]
GSM768708
[491]
GSM768709
[492]
GSM768710
[493]
GSM768711
[494]
GSM768712
[495]
GSM768713
[496]
GSM768714
[497]
GSM768715
[498]
GSM768716
[499]
GSM768717
[500]
GSM768718
[501]
GSM768719
[502]
GSM768720
[503]
GSM768721
[504]
GSM768722
[505]
GSM768723
[506]
GSM768724
[507]
GSM768725
[508]
GSM768726
[509]
GSM768727
[510]
GSM768728
[511]
GSM768729
[512]
GSM768730
[513]
GSM768731
[514]
GSM768732
[515]
GSM768733
[516]
GSM768734
[517]
GSM768735
[518]
GSM768736
[519]
GSM768737
[520]
GSM768738
[521]
GSM768739
[522]
GSM768740
[523]
GSM768741
[524]
GSM768742
[525]
GSM768743
[526]
GSM768744
[527]
GSM768745
[528]
GSM768746
[529]
GSM768747
[530]
GSM768748
[531]
GSM768749
[532]
GSM768750
[533]
GSM768751
[534]
GSM768752
[535]
GSM768753
[536]
GSM768754
sample_count
537
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Acute myeloid leukemia samples of samples =< 60yrs on HG-U133 plus 2
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 4 items
[0]
asset:data:geo:GSE17855 not downloaded
[1]
asset:data:geo:GSE17855 licence not read
[2]
asset:data:geo:GSE6891 not downloaded
[3]
asset:data:geo:GSE6891 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
band
verbatim
quote
The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value.
[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
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
missing_operations array · 0 items
parameters object · 1 field
p_value
ere used to compare the P value
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
band
high
quote
Log-rank
[3] object · 10 fields
id
method-4
family
differential_expression
specific
deseq2
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
0.8
band
high
quote
DESeq2
targets array · 1 item
[0] object · 8 fields
id
target-published-estimate
claim_id
claim-target-result
operation
differential_expression_fit
unit
per cent
tolerance
null
state
complete
note
The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none.
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 · 1 item
[0]
cox_ph
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: cox_proportional_hazards.
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 · 2 items
[0]
GSE6891
[1]
GSE17855
resolved_accessions array · 2 items
[0]
GSE6891
[1]
GSE17855
statements array · 1 item
[0]
Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).
basis
The paper names GSE6891, GSE17855 in Gene Expression Omnibus and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
[0]
cox_ph
assets array · 2 items
[0]
source:pmid:36291567
[1]
data:geo:GSE17855
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:GSE17855
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
2026-11-01T18:13:01Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
12668
completion_tokens
1827
cached_tokens
264
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:36291567
type
paper
label
pmid:36291567
[1] object · 3 fields
id
source:pmid:36291567
type
manuscript
label
PMID 36291567 full text
[2] object · 3 fields
id
data:geo:GSE17855
type
dataset
label
GEO GSE17855
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:36291567
type
paper
label
pmid:36291567
[1] object · 3 fields
id
source:pmid:36291567
type
manuscript
label
PMID 36291567 full text
[2] object · 3 fields
id
data:geo:GSE17855
type
dataset
label
GEO GSE17855
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-36291567
type
extraction
used array · 1 item
[0]
source:pmid:36291567
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE17855
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE17855
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:36291567
parent_hash
sha256:490c5b9988ffc1a37d6d887b5603b433a170a4ec7ec8d139493cdcba095c9051
fork_of
null
gaps array · 9 items
[0]
asset:data:geo:GSE17855 licence not read
[1]
asset:data:geo:GSE17855 not downloaded
[2]
asset:data:geo:GSE6891 licence not read
[3]
asset:data:geo:GSE6891 not downloaded
[4]
execution.not_run
[5]
method.reader_differs_from_extractor
[6]
review.human_critique
[7]
review.independent_reader
[8]
review.machine_critique
assays array · 3 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
0.93
evidence array · 1 item
[0]
fication system. Recently, through the novel single-cell RNA sequencing technology, we revealed heterogeneous leukem
order_basis
paper_text_order:260
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
0.93
evidence array · 1 item
[0]
tem. Recently, through the novel single-cell RNA sequencing technology, we revealed heterogeneous leukem
order_basis
paper_text_order:272
id
assay:2
[2] object · 11 fields
role
analysis
definition_id
survival_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
[0]
cox_ph
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value.
order_basis
consumes_earlier_output
id
assay:3
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36291567", "kind": "science-record", "revision": 5, "content_hash": "sha256:e70e5407f5b566dc868ee9b4a7633b8021b76c369cbf3e8607b1510e9899f5fa", "created_at": "2026-11-01T18:15:42Z", "updated_at": "2026-11-01T22:50:28Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of the Thyrotropin-Releasing Hormone (TRH) as a Novel Biomarker in the Prognosis for Acute Myeloid Leukemia.", "doi": "10.3390/biom12101359", "pmid": "36291567", "authors": ["Yan Gao", "Jia-Fan Zhou", "Jia-Ying Mao", "Lu Jiang", "Xue-Ping Li"], "journal": "Biomolecules", "year": 2022, "abstract": "Acute myeloid leukemia (AML) is a biologically and genetically heterogeneous hematological malignance with an unsatisfactory risk stratification system. Recently, through the novel single-cell RNA sequencing technology, we revealed heterogeneous leukemia myeloblasts in RUNX1-RUNX1T1 AML. Thyrotropin-releasing hormone (TRH), as biomarkers of CD34+CD117bri myeloblasts, were found to be prognostic in RUNX1-RUNX1T1 AML. However, the clinical and genetic features of TRH in AML patients are poorly understood. Here, with data from TCGA AML, TRH was found to be downregulated in patients older than 60 years old, with DNMT3A and NPM1 mutations, while overexpressed in patients with KIT mutations. This was further validated in three other cohorts of primary AML including Beat AML (n = 223), GSE6891 (n = 461), and GSE17855 (n = 237). Furthermore, we demonstrated that the expression of TRH in AML could be used to improve the ELN 2017 risk stratification system. In conclusion, our preliminary analysis revealed that TRH, a novel biomarker for AML patients, could be used to evaluate the survival of AML.", "claims": [{"id": "claim-method", "statement": "The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36291567", "locator": "sections[7] \"2.5. Statistical Analysis\" paragraph 2", "quote": "The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36291567", "locator": "sections[22] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021))."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Higher TRH expression was independently associated with better overall survival in the TCGA AML cohort and could refine the ELN 2017 risk stratification system.", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "The multivariate analysis showed that age (HR, 1.035; 95%CI, 1.019–1.051; p < 0.001), WBC count (HR, 1.007; 95%CI, 1.002–1.011; p = 0.008), TRH expression (HR, 0.910; 95%CI, 0.840–0.987; p = 0.022), and ELN 2017 risk (HR, 1.655; 95%CI, 1.254–2.185; p < 0.001) remained independent prognostic factors for OS."}, "evidence": [{"asset": "source:pmid:36291567", "locator": "sections[14] \"3.6. Improvement of Prognostic Stratification for the ELN Risk System\" paragraph 2", "quote": "The multivariate analysis showed that age (HR, 1.035; 95%CI, 1.019–1.051; p < 0.001), WBC count (HR, 1.007; 95%CI, 1.002–1.011; p = 0.008), TRH expression (HR, 0.910; 95%CI, 0.840–0.987; p = 0.022), and ELN 2017 risk (HR, 1.655; 95%CI, 1.254–2.185; p < 0.001) remained independent prognostic factors for OS."}, {"asset": "source:pmid:36291567", "locator": "sections[14] \"3.6. Improvement of Prognostic Stratification for the ELN Risk System\" paragraph 2", "quote": "Collectively, these data indicate that the expression of TRH could be used to further stratify AML patients on the basis of the ELN 2017 risk system."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Higher TRH expression was independently associated with better overall survival in the TCGA AML cohort and could refine the ELN 2017 risk stratification system.", "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:36291567"], "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:GSE17855"], "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:GSE17855"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36291567", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/biom12101359", "sha256": "sha256:5a747b6ff07893db2de40fd5011e715b66f11ae4abcca5903b5c2bded42bbff5", "bytes": 38743, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3390/biom12101359", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9599642", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17855", "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=GSE17855", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17855", "version": null, "note": "Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM445920", "GSM445921", "GSM445922", "GSM445923", "GSM445924", "GSM445925", "GSM445926", "GSM445927", "GSM445928", "GSM445929", "GSM445930", "GSM445931", "GSM445932", "GSM445933", "GSM445934", "GSM445935", "GSM445936", "GSM445937", "GSM445938", "GSM445939", "GSM445940", "GSM445941", "GSM445942", "GSM445943", "GSM445944", "GSM445945", "GSM445946", "GSM445947", "GSM445948", "GSM445949", "GSM445950", "GSM445951", "GSM445952", "GSM445953", "GSM445954", "GSM445955", "GSM445956", "GSM445957", "GSM445958", "GSM445959", "GSM445960", "GSM445961", "GSM445962", "GSM445963", "GSM445964", "GSM445965", "GSM445966", "GSM445967", "GSM445968", "GSM445969", "GSM445970", "GSM445971", "GSM445972", "GSM445973", "GSM445974", "GSM445975", "GSM445976", "GSM445977", "GSM445978", "GSM445979", "GSM445980", "GSM445981", "GSM445982", "GSM445983", "GSM445984", "GSM445985", "GSM445986", "GSM445987", "GSM445988", "GSM445989", "GSM445990", "GSM445991", "GSM445992", "GSM445993", "GSM445994", "GSM445995", "GSM445996", "GSM445997", "GSM445998", "GSM445999", "GSM446000", "GSM446001", "GSM446002", "GSM446003", "GSM446004", "GSM446005", "GSM446006", "GSM446007", "GSM446008", "GSM446009", "GSM446010", "GSM446011", "GSM446012", "GSM446013", "GSM446014", "GSM446015", "GSM446016", "GSM446017", "GSM446018", "GSM446019", "GSM446020", "GSM446021", "GSM446022", "GSM446023", "GSM446024", "GSM446025", "GSM446026", "GSM446027", "GSM446028", "GSM446029", "GSM446030", "GSM446031", "GSM446032", "GSM446033", "GSM446034", "GSM446035", "GSM446036", "GSM446037", "GSM446038", "GSM446039", "GSM446040", "GSM446041", "GSM446042", "GSM446043", "GSM446044", "GSM446045", "GSM446046", "GSM446047", "GSM446048", "GSM446049", "GSM446050", "GSM446051", "GSM446052", "GSM446053", "GSM446054", "GSM446055", "GSM446056", "GSM446057", "GSM446058", "GSM446059", "GSM446060", "GSM446061", "GSM446062", "GSM446063", "GSM446064", "GSM446065", "GSM446066", "GSM446067", "GSM446068", "GSM446069", "GSM446070", "GSM446071", "GSM446072", "GSM446073", "GSM446074", "GSM446075", "GSM446076", "GSM446077", "GSM446078", "GSM446079", "GSM446080", "GSM446081", "GSM446082", "GSM446083", "GSM446084", "GSM446085", "GSM446086", "GSM446087", "GSM446088", "GSM446089", "GSM446090", "GSM446091", "GSM446092", "GSM446093", "GSM446094", "GSM446095", "GSM446096", "GSM446097", "GSM446098", "GSM446099", "GSM446100", "GSM446101", "GSM446102", "GSM446103", "GSM446104", "GSM446105", "GSM446106", "GSM446107", "GSM446108", "GSM446109", "GSM446110", "GSM446111", "GSM446112", "GSM446113", "GSM446114", "GSM446115", "GSM446116", "GSM446117", "GSM446118", "GSM446119", "GSM446120", "GSM446121", "GSM446122", "GSM446123", "GSM446124", "GSM446125", "GSM446126", "GSM446127", "GSM446128", "GSM446129", "GSM446130", "GSM446131", "GSM446132", "GSM446133", "GSM446134", "GSM446135", "GSM446136", "GSM446137", "GSM446138", "GSM446139", "GSM446140", "GSM446141", "GSM446142", "GSM446143", "GSM446144", "GSM446145", "GSM446146", "GSM446147", "GSM446148", "GSM446149", "GSM446150", "GSM446151", "GSM446152", "GSM446153", "GSM446154", "GSM446155", "GSM446156"], "sample_count": 237, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Expression data from pediatric AML patients", "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:GSE6891", "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=GSE6891", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE6891", "version": null, "note": "Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021)).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM158711", "GSM158712", "GSM158713", "GSM158714", "GSM158715", "GSM158716", "GSM158717", "GSM158718", "GSM158719", "GSM158720", "GSM158721", "GSM158722", "GSM158723", "GSM158724", "GSM158725", "GSM158726", "GSM158727", "GSM158728", "GSM158729", "GSM158730", "GSM158731", "GSM158732", "GSM158733", "GSM158734", "GSM158735", "GSM158736", "GSM158737", "GSM158738", "GSM158739", "GSM158740", "GSM158741", "GSM158742", "GSM158743", "GSM158744", "GSM158745", "GSM158746", "GSM158747", "GSM158748", "GSM158749", "GSM158750", "GSM158751", "GSM158752", "GSM158753", "GSM158754", "GSM158755", "GSM158756", "GSM158757", "GSM158758", "GSM158759", "GSM158760", "GSM158761", "GSM158762", "GSM158763", "GSM158764", "GSM158765", "GSM158766", "GSM158767", "GSM158768", "GSM158769", "GSM158770", "GSM158771", "GSM158772", "GSM158773", "GSM158774", "GSM158775", "GSM158776", "GSM158777", "GSM158778", "GSM158779", "GSM158780", "GSM158781", "GSM158782", "GSM158783", "GSM158784", "GSM158785", "GSM158786", "GSM158787", "GSM158788", "GSM158789", "GSM158790", "GSM158791", "GSM158792", "GSM158793", "GSM158794", "GSM158795", "GSM158796", "GSM158797", "GSM158798", "GSM158799", "GSM158800", "GSM158801", "GSM158802", "GSM158803", "GSM158804", "GSM158805", "GSM158806", "GSM158807", "GSM158808", "GSM158809", "GSM158810", "GSM158811", "GSM158812", "GSM158813", "GSM158814", "GSM158815", "GSM158816", "GSM158817", "GSM158818", "GSM158819", "GSM158820", "GSM158821", "GSM158822", "GSM158823", "GSM158824", "GSM158825", "GSM158826", "GSM158827", "GSM158828", "GSM158829", "GSM158830", "GSM158831", "GSM158832", "GSM158833", "GSM158834", "GSM158835", "GSM158836", "GSM158837", "GSM158838", "GSM158839", "GSM158840", "GSM158841", "GSM158842", "GSM158843", "GSM158844", "GSM158845", "GSM158846", "GSM158847", "GSM158848", "GSM158849", "GSM158850", "GSM158851", "GSM158852", "GSM158853", "GSM158854", "GSM158855", "GSM158856", "GSM158857", "GSM158858", "GSM158859", "GSM158860", "GSM158861", "GSM158862", "GSM158863", "GSM158864", "GSM158865", "GSM158866", "GSM158867", "GSM158868", "GSM158869", "GSM158870", "GSM158871", "GSM158872", "GSM158873", "GSM158874", "GSM158875", "GSM158876", "GSM158877", "GSM158878", "GSM158879", "GSM158880", "GSM158881", "GSM158882", "GSM158883", "GSM158884", "GSM158885", "GSM158886", "GSM158887", "GSM158888", "GSM158889", "GSM158890", "GSM158891", "GSM158892", "GSM158893", "GSM158894", "GSM158895", "GSM158896", "GSM158897", "GSM158898", "GSM158899", "GSM158900", "GSM158901", "GSM158902", "GSM158903", "GSM158904", "GSM158905", "GSM158906", "GSM158907", "GSM158908", "GSM158909", "GSM158910", "GSM158911", "GSM158912", "GSM158913", "GSM158914", "GSM158915", "GSM158916", "GSM158917", "GSM158918", "GSM158919", "GSM158920", "GSM158921", "GSM158922", "GSM158923", "GSM158924", "GSM158925", "GSM158926", "GSM158927", "GSM158928", "GSM158929", "GSM158930", "GSM158931", "GSM158932", "GSM158933", "GSM158934", "GSM158935", "GSM158936", "GSM158937", "GSM158938", "GSM158939", "GSM158940", "GSM158941", "GSM158942", "GSM158943", "GSM158944", "GSM158945", "GSM158946", "GSM158947", "GSM158948", "GSM158949", "GSM158950", "GSM158951", "GSM158952", "GSM158953", "GSM158954", "GSM158955", "GSM158956", "GSM158957", "GSM158958", "GSM158959", "GSM158960", "GSM158961", "GSM158962", "GSM158963", "GSM158964", "GSM158965", "GSM158966", "GSM158967", "GSM158968", "GSM158969", "GSM158970", "GSM158971", "GSM158972", "GSM158973", "GSM158974", "GSM158975", "GSM158976", "GSM158977", "GSM158978", "GSM158979", "GSM158980", "GSM158981", "GSM158982", "GSM158983", "GSM158984", "GSM158985", "GSM158986", "GSM158987", "GSM158988", "GSM158989", "GSM158990", "GSM158991", "GSM158992", "GSM158993", "GSM158994", "GSM158995", "GSM158996", "GSM158997", "GSM158998", "GSM158999", "GSM159000", "GSM159001", "GSM159002", "GSM159003", "GSM159004", "GSM159005", "GSM159006", "GSM159007", "GSM159008", "GSM159009", "GSM159010", "GSM159011", "GSM159012", "GSM159013", "GSM159014", "GSM159015", "GSM159016", "GSM159017", "GSM159018", "GSM159019", "GSM159020", "GSM159021", "GSM159022", "GSM159023", "GSM159024", "GSM159025", "GSM159026", "GSM159027", "GSM159028", "GSM159029", "GSM159030", "GSM159031", "GSM159032", "GSM159033", "GSM159034", "GSM159035", "GSM159036", "GSM159037", "GSM159038", "GSM159039", "GSM159040", "GSM159041", "GSM159042", "GSM159043", "GSM159044", "GSM159045", "GSM159046", "GSM159047", "GSM159048", "GSM159049", "GSM159050", "GSM159051", "GSM159052", "GSM159053", "GSM159054", "GSM159055", "GSM159056", "GSM159057", "GSM159058", "GSM159059", "GSM159060", "GSM159061", "GSM159062", "GSM159063", "GSM159064", "GSM159065", "GSM159066", "GSM159067", "GSM159068", "GSM159069", "GSM159070", "GSM159071", "GSM159072", "GSM159073", "GSM159074", "GSM159075", "GSM159076", "GSM159077", "GSM159078", "GSM159079", "GSM159080", "GSM159081", "GSM159082", "GSM159083", "GSM159084", "GSM159085", "GSM159086", "GSM159087", "GSM159088", "GSM159089", "GSM159090", "GSM159091", "GSM159092", "GSM159093", "GSM159094", "GSM159095", "GSM159096", "GSM159097", "GSM159098", "GSM159099", "GSM159100", "GSM159101", "GSM159102", "GSM159103", "GSM159104", "GSM159105", "GSM159106", "GSM159107", "GSM159108", "GSM159109", "GSM159110", "GSM159111", "GSM159112", "GSM159113", "GSM159114", "GSM159115", "GSM159116", "GSM159117", "GSM159118", "GSM159119", "GSM159120", "GSM159121", "GSM159122", "GSM159123", "GSM159124", "GSM159125", "GSM159126", "GSM159127", "GSM159128", "GSM159129", "GSM159130", "GSM159131", "GSM159132", "GSM159133", "GSM159134", "GSM159135", "GSM159136", "GSM159137", "GSM159138", "GSM159139", "GSM159140", "GSM159141", "GSM159142", "GSM159143", "GSM159144", "GSM159145", "GSM159146", "GSM159147", "GSM159148", "GSM159149", "GSM159150", "GSM159151", "GSM159152", "GSM159153", "GSM159154", "GSM159155", "GSM159156", "GSM159157", "GSM159158", "GSM159159", "GSM159160", "GSM159161", "GSM159162", "GSM159163", "GSM159164", "GSM159165", "GSM159166", "GSM159167", "GSM159168", "GSM159169", "GSM159170", "GSM159171", "GSM768679", "GSM768680", "GSM768681", "GSM768682", "GSM768683", "GSM768684", "GSM768685", "GSM768686", "GSM768687", "GSM768688", "GSM768689", "GSM768690", "GSM768691", "GSM768692", "GSM768693", "GSM768694", "GSM768695", "GSM768696", "GSM768697", "GSM768698", "GSM768699", "GSM768700", "GSM768701", "GSM768702", "GSM768703", "GSM768704", "GSM768705", "GSM768706", "GSM768707", "GSM768708", "GSM768709", "GSM768710", "GSM768711", "GSM768712", "GSM768713", "GSM768714", "GSM768715", "GSM768716", "GSM768717", "GSM768718", "GSM768719", "GSM768720", "GSM768721", "GSM768722", "GSM768723", "GSM768724", "GSM768725", "GSM768726", "GSM768727", "GSM768728", "GSM768729", "GSM768730", "GSM768731", "GSM768732", "GSM768733", "GSM768734", "GSM768735", "GSM768736", "GSM768737", "GSM768738", "GSM768739", "GSM768740", "GSM768741", "GSM768742", "GSM768743", "GSM768744", "GSM768745", "GSM768746", "GSM768747", "GSM768748", "GSM768749", "GSM768750", "GSM768751", "GSM768752", "GSM768753", "GSM768754"], "sample_count": 537, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Acute myeloid leukemia samples of samples =< 60yrs on HG-U133 plus 2", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE17855 not downloaded", "asset:data:geo:GSE17855 licence not read", "asset:data:geo:GSE6891 not downloaded", "asset:data:geo:GSE6891 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value."}}, {"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": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {"p_value": "ere used to compare the P value"}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Log-rank"}}, {"id": "method-4", "family": "differential_expression", "specific": "deseq2", "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": 0.8, "band": "high", "quote": "DESeq2"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "differential_expression_fit", "expected_value": 95.0, "unit": "per cent", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}], "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": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "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": ["GSE6891", "GSE17855"], "resolved_accessions": ["GSE6891", "GSE17855"], "statements": ["Publicly available datasets including TCGA, Beat AML, GSE6891, and GSE17855 can be downloaded from online. Data of AML with RUNX1-RUNX1T1 can be accessed on the National Omics Data Encyclopedia (http://www.biosino.org/node/project/detail/OEP000629 (accessed on 12 December 2021))."], "basis": "The paper names GSE6891, GSE17855 in Gene Expression Omnibus and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:36291567", "data:geo:GSE17855"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE17855"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:13:01Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12668, "completion_tokens": 1827, "cached_tokens": 264}}, "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:36291567", "type": "paper", "label": "pmid:36291567"}, {"id": "source:pmid:36291567", "type": "manuscript", "label": "PMID 36291567 full text"}, {"id": "data:geo:GSE17855", "type": "dataset", "label": "GEO GSE17855"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36291567", "type": "paper", "label": "pmid:36291567"}, {"id": "source:pmid:36291567", "type": "manuscript", "label": "PMID 36291567 full text"}, {"id": "data:geo:GSE17855", "type": "dataset", "label": "GEO GSE17855"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36291567", "type": "extraction", "used": ["source:pmid:36291567"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE17855", "type": "accession_resolution", "used": ["data:geo:GSE17855"], "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:36291567", "parent_hash": "sha256:490c5b9988ffc1a37d6d887b5603b433a170a4ec7ec8d139493cdcba095c9051", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE17855 licence not read", "asset:data:geo:GSE17855 not downloaded", "asset:data:geo:GSE6891 licence not read", "asset:data:geo:GSE6891 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": 0.93, "evidence": ["fication system. Recently, through the novel single-cell RNA sequencing technology, we revealed heterogeneous leukem"], "order_basis": "paper_text_order:260", "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": 0.93, "evidence": ["tem. Recently, through the novel single-cell RNA sequencing technology, we revealed heterogeneous leukem"], "order_basis": "paper_text_order:272", "id": "assay:2"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The Kaplan–Meier method was used to estimate the probability of overall survival (OS). Log-rank tests were used to compare the P value."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}