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pmid:38457553

Construction of LncRNA-mediated CeRNA network for investigating the immune pathogenesis of myocardial infarction.

Dongmei Wei · Yuanting Meng · Hua Fan · Yang Sun · Rongtao Chen

Medicine · 2024 doi:10.1097/MD.0000000000037413

Paper

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Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:38457553
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2026-11-01T19:20:23Z
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paper object · 10 fields
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title
Construction of LncRNA-mediated CeRNA network for investigating the immune pathogenesis of myocardial infarction.
doi
10.1097/MD.0000000000037413
pmid
38457553
authors array · 5 items
[0]
Dongmei Wei
[1]
Yuanting Meng
[2]
Hua Fan
[3]
Yang Sun
[4]
Rongtao Chen
journal
Medicine
year
2024
abstract
BACKGROUND: Myocardial infarction (MI) is a cardiovascular disease that seriously threatens human health. However, an immune-related competitive endogenous RNA (ceRNA) network has not been reported in MI. METHODS: The GSE66360, GSE19339, GSE97320, GSE61741, and GSE168281 datasets were acquired from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) from MI patients and healthy controls were screened and an immune-related ceRNA network was constructed. Furthermore, the key long noncoding RNAs(lncRNAs) highly related to the immune mechanism of MI were identified utilizing the random walk with restart algorithm. Finally, the expression of the hub genes was further verified in the GSE66360, GSE19339, and GSE97320 datasets, and quantitativereal-time polymerase chain reaction (qRT-PCR) was performed for the MI patients and healthy controls. RESULTS: A total of 184 differentially expressed immune-related genes(DE-IRGs) and 432 DE-miRNAs were obtained, and an immune-related ceRNA network comprising 1421 lncRNAs, 61 DE-miRNAs, and 139 DE-IRGs was constructed. According to the order of stress, betweenness, and closeness, NEAT1, KCNQ1OT1, and XIST were identified as key lncRNAs. Moreover, random walk with restart analysis also suggested that NEAT1, KCNQ1OT1, and XIST are key lncRNAs. Subsequently, a ceRNA network of 10 hub genes and 3 lncRNAs was constructed. Finally, we found that the expression of FCER1G and TYROBP significantly differed between MI patients and control individuals in the GSE66360, GSE19339, and GSE97320 datasets. qRT-PCR revealed that the expression of NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP was significantly elevated in MI tissue samples compared to healthy control tissue samples. CONCLUSION: NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI. Furthermore, the immune system plays an essential role in the onset and progression of MI.
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The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control).
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sections[4] "2.2. Differential expression analysis" paragraph 2
quote
The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control).
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sections[24] "fn-group" paragraph 1
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI.
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sections[0] "Abstract" paragraph 6
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NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI.
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NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI.
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Uncovering potential lncRNAs and mRNAs in progression from acute myocardial infarction to myocardial fibrosis to heart failure
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GSM1512516
[379]
GSM1512517
[380]
GSM1512518
[381]
GSM1512519
[382]
GSM1512520
[383]
GSM1512521
[384]
GSM1512522
[385]
GSM1512523
[386]
GSM1512524
[387]
GSM1512525
[388]
GSM1512526
[389]
GSM1512527
[390]
GSM1512528
[391]
GSM1512529
[392]
GSM1512530
[393]
GSM1512531
[394]
GSM1512532
[395]
GSM1512533
[396]
GSM1512534
[397]
GSM1512535
[398]
GSM1512536
[399]
GSM1512537
[400]
GSM1512538
[401]
GSM1512539
[402]
GSM1512540
[403]
GSM1512541
[404]
GSM1512542
[405]
GSM1512543
[406]
GSM1512544
[407]
GSM1512545
[408]
GSM1512546
[409]
GSM1512547
[410]
GSM1512548
[411]
GSM1512549
[412]
GSM1512550
[413]
GSM1512551
[414]
GSM1512552
[415]
GSM1512553
[416]
GSM1512554
[417]
GSM1512555
[418]
GSM1512556
[419]
GSM1512557
[420]
GSM1512558
[421]
GSM1512559
[422]
GSM1512560
[423]
GSM1512561
[424]
GSM1512562
[425]
GSM1512563
[426]
GSM1512564
[427]
GSM1512565
[428]
GSM1512566
[429]
GSM1512567
[430]
GSM1512568
[431]
GSM1512569
[432]
GSM1512570
[433]
GSM1512571
[434]
GSM1512572
[435]
GSM1512573
[436]
GSM1512574
[437]
GSM1512575
[438]
GSM1512576
[439]
GSM1512577
[440]
GSM1512578
[441]
GSM1512579
[442]
GSM1512580
[443]
GSM1512581
[444]
GSM1512582
[445]
GSM1512583
[446]
GSM1512584
[447]
GSM1512585
[448]
GSM1512586
[449]
GSM1512587
[450]
GSM1512588
[451]
GSM1512589
[452]
GSM1512590
[453]
GSM1512591
[454]
GSM1512592
[455]
GSM1512593
[456]
GSM1512594
[457]
GSM1512595
[458]
GSM1512596
[459]
GSM1512597
[460]
GSM1512598
[461]
GSM1512599
[462]
GSM1512600
[463]
GSM1512601
[464]
GSM1512602
[465]
GSM1512603
[466]
GSM1512604
[467]
GSM1512605
[468]
GSM1512606
[469]
GSM1512607
[470]
GSM1512608
[471]
GSM1512609
[472]
GSM1512610
[473]
GSM1512611
[474]
GSM1512612
[475]
GSM1512613
[476]
GSM1512614
[477]
GSM1512615
[478]
GSM1512616
[479]
GSM1512617
[480]
GSM1512618
[481]
GSM1512619
[482]
GSM1512620
[483]
GSM1512621
[484]
GSM1512622
[485]
GSM1512623
[486]
GSM1512624
[487]
GSM1512625
[488]
GSM1512626
[489]
GSM1512627
[490]
GSM1512628
[491]
GSM1512629
[492]
GSM1512630
[493]
GSM1512631
[494]
GSM1512632
[495]
GSM1512633
[496]
GSM1512634
[497]
GSM1512635
[498]
GSM1512636
[499]
GSM1512637
[500]
GSM1512638
[501]
GSM1512639
[502]
GSM1512640
[503]
GSM1512641
[504]
GSM1512642
[505]
GSM1512643
[506]
GSM1512644
[507]
GSM1512645
[508]
GSM1512646
[509]
GSM1512647
[510]
GSM1512648
[511]
GSM1512649
[512]
GSM1512650
[513]
GSM1512651
[514]
GSM1512652
[515]
GSM1512653
[516]
GSM1512654
[517]
GSM1512655
[518]
GSM1512656
[519]
GSM1512657
[520]
GSM1512658
[521]
GSM1512659
[522]
GSM1512660
[523]
GSM1512661
[524]
GSM1512662
[525]
GSM1512663
[526]
GSM1512664
[527]
GSM1512665
[528]
GSM1512666
[529]
GSM1512667
[530]
GSM1512668
[531]
GSM1512669
[532]
GSM1512670
[533]
GSM1512671
[534]
GSM1512672
[535]
GSM1512673
[536]
GSM1512674
[537]
GSM1512675
[538]
GSM1512676
[539]
GSM1512677
[540]
GSM1512678
[541]
GSM1512679
[542]
GSM1512680
[543]
GSM1512681
[544]
GSM1512682
[545]
GSM1512683
[546]
GSM1512684
[547]
GSM1512685
[548]
GSM1512686
[549]
GSM1512687
[550]
GSM1512688
[551]
GSM1512689
[552]
GSM1512690
[553]
GSM1512691
[554]
GSM1512692
[555]
GSM1512693
[556]
GSM1512694
[557]
GSM1512695
[558]
GSM1512696
[559]
GSM1512697
[560]
GSM1512698
[561]
GSM1512699
[562]
GSM1512700
[563]
GSM1512701
[564]
GSM1512702
[565]
GSM1512703
[566]
GSM1512704
[567]
GSM1512705
[568]
GSM1512706
[569]
GSM1512707
[570]
GSM1512708
[571]
GSM1512709
[572]
GSM1512710
[573]
GSM1512711
[574]
GSM1512712
[575]
GSM1512713
[576]
GSM1512714
[577]
GSM1512715
[578]
GSM1512716
[579]
GSM1512717
[580]
GSM1512718
[581]
GSM1512719
[582]
GSM1512720
[583]
GSM1512721
[584]
GSM1512722
[585]
GSM1512723
[586]
GSM1512724
[587]
GSM1512725
[588]
GSM1512726
[589]
GSM1512727
[590]
GSM1512728
[591]
GSM1512729
[592]
GSM1512730
[593]
GSM1512731
[594]
GSM1512732
[595]
GSM1512733
[596]
GSM1512734
[597]
GSM1512735
[598]
GSM1512736
[599]
GSM1512737
[600]
GSM1512738
[601]
GSM1512739
[602]
GSM1512740
[603]
GSM1512741
[604]
GSM1512742
[605]
GSM1512743
[606]
GSM1512744
[607]
GSM1512745
[608]
GSM1512746
[609]
GSM1512747
[610]
GSM1512748
[611]
GSM1512749
[612]
GSM1512750
[613]
GSM1512751
[614]
GSM1512752
[615]
GSM1512753
[616]
GSM1512754
[617]
GSM1512755
[618]
GSM1512756
[619]
GSM1512757
[620]
GSM1512758
[621]
GSM1512759
[622]
GSM1512760
[623]
GSM1512761
[624]
GSM1512762
[625]
GSM1512763
[626]
GSM1512764
[627]
GSM1512765
[628]
GSM1512766
[629]
GSM1512767
[630]
GSM1512768
[631]
GSM1512769
[632]
GSM1512770
[633]
GSM1512771
[634]
GSM1512772
[635]
GSM1512773
[636]
GSM1512774
[637]
GSM1512775
[638]
GSM1512776
[639]
GSM1512777
[640]
GSM1512778
[641]
GSM1512779
[642]
GSM1512780
[643]
GSM1512781
[644]
GSM1512782
[645]
GSM1512783
[646]
GSM1512784
[647]
GSM1512785
[648]
GSM1512786
[649]
GSM1512787
[650]
GSM1512788
[651]
GSM1512789
[652]
GSM1512790
[653]
GSM1512791
[654]
GSM1512792
[655]
GSM1512793
[656]
GSM1512794
[657]
GSM1512795
[658]
GSM1512796
[659]
GSM1512797
[660]
GSM1512798
[661]
GSM1512799
[662]
GSM1512800
[663]
GSM1512801
[664]
GSM1512802
[665]
GSM1512803
[666]
GSM1512804
[667]
GSM1512805
[668]
GSM1512806
[669]
GSM1512807
[670]
GSM1512808
[671]
GSM1512809
[672]
GSM1512810
[673]
GSM1512811
[674]
GSM1512812
[675]
GSM1512813
[676]
GSM1512814
[677]
GSM1512815
[678]
GSM1512816
[679]
GSM1512817
[680]
GSM1512818
[681]
GSM1512819
[682]
GSM1512820
[683]
GSM1512821
[684]
GSM1512822
[685]
GSM1512823
[686]
GSM1512824
[687]
GSM1512825
[688]
GSM1512826
[689]
GSM1512827
[690]
GSM1512828
[691]
GSM1512829
[692]
GSM1512830
[693]
GSM1512831
[694]
GSM1512832
[695]
GSM1512833
[696]
GSM1512834
[697]
GSM1512835
[698]
GSM1512836
[699]
GSM1512837
[700]
GSM1512838
[701]
GSM1512839
[702]
GSM1512840
[703]
GSM1512841
[704]
GSM1512842
[705]
GSM1512843
[706]
GSM1512844
[707]
GSM1512845
[708]
GSM1512846
[709]
GSM1512847
[710]
GSM1512848
[711]
GSM1512849
[712]
GSM1512850
[713]
GSM1512851
[714]
GSM1512852
[715]
GSM1512853
[716]
GSM1512854
[717]
GSM1512855
[718]
GSM1512856
[719]
GSM1512857
[720]
GSM1512858
[721]
GSM1512859
[722]
GSM1512860
[723]
GSM1512861
[724]
GSM1512862
[725]
GSM1512863
[726]
GSM1512864
[727]
GSM1512865
[728]
GSM1512866
[729]
GSM1512867
[730]
GSM1512868
[731]
GSM1512869
[732]
GSM1512870
[733]
GSM1512871
[734]
GSM1512872
[735]
GSM1512873
[736]
GSM1512874
[737]
GSM1512875
[738]
GSM1512876
[739]
GSM1512877
[740]
GSM1512878
[741]
GSM1512879
[742]
GSM1512880
[743]
GSM1512881
[744]
GSM1512882
[745]
GSM1512883
[746]
GSM1512884
[747]
GSM1512885
[748]
GSM1512886
[749]
GSM1512887
[750]
GSM1512888
[751]
GSM1512889
[752]
GSM1512890
[753]
GSM1512891
[754]
GSM1512892
[755]
GSM1512893
[756]
GSM1512894
[757]
GSM1512895
[758]
GSM1512896
[759]
GSM1512897
[760]
GSM1512898
[761]
GSM1512899
[762]
GSM1512900
[763]
GSM1512901
[764]
GSM1512902
[765]
GSM1512903
[766]
GSM1512904
[767]
GSM1512905
[768]
GSM1512906
[769]
GSM1512907
[770]
GSM1512908
[771]
GSM1512909
[772]
GSM1512910
[773]
GSM1512911
[774]
GSM1512912
[775]
GSM1512913
[776]
GSM1512914
[777]
GSM1512915
[778]
GSM1512916
[779]
GSM1512917
[780]
GSM1512918
[781]
GSM1512919
[782]
GSM1512920
[783]
GSM1512921
[784]
GSM1512922
[785]
GSM1512923
[786]
GSM1512924
[787]
GSM1512925
[788]
GSM1512926
[789]
GSM1512927
[790]
GSM1512928
[791]
GSM1512929
[792]
GSM1512930
[793]
GSM1512931
[794]
GSM1512932
[795]
GSM1512933
[796]
GSM1512934
[797]
GSM1512935
[798]
GSM1512936
[799]
GSM1512937
[800]
GSM1512938
[801]
GSM1512939
[802]
GSM1512940
[803]
GSM1512941
[804]
GSM1512942
[805]
GSM1512943
[806]
GSM1512944
[807]
GSM1512945
[808]
GSM1512946
[809]
GSM1512947
[810]
GSM1512948
[811]
GSM1512949
[812]
GSM1512950
[813]
GSM1512951
[814]
GSM1512952
[815]
GSM1512953
[816]
GSM1512954
[817]
GSM1512955
[818]
GSM1512956
[819]
GSM1512957
[820]
GSM1512958
[821]
GSM1512959
[822]
GSM1512960
[823]
GSM1512961
[824]
GSM1512962
[825]
GSM1512963
[826]
GSM1512964
[827]
GSM1512965
[828]
GSM1512966
[829]
GSM1512967
[830]
GSM1512968
[831]
GSM1512969
[832]
GSM1512970
[833]
GSM1512971
[834]
GSM1512972
[835]
GSM1512973
[836]
GSM1512974
[837]
GSM1512975
[838]
GSM1512976
[839]
GSM1512977
[840]
GSM1512978
[841]
GSM1512979
[842]
GSM1512980
[843]
GSM1512981
[844]
GSM1512982
[845]
GSM1512983
[846]
GSM1512984
[847]
GSM1512985
[848]
GSM1512986
[849]
GSM1512987
[850]
GSM1512988
[851]
GSM1512989
[852]
GSM1512990
[853]
GSM1512991
[854]
GSM1512992
[855]
GSM1512993
[856]
GSM1512994
[857]
GSM1512995
[858]
GSM1512996
[859]
GSM1512997
[860]
GSM1512998
[861]
GSM1512999
[862]
GSM1513000
[863]
GSM1513001
[864]
GSM1513002
[865]
GSM1513003
[866]
GSM1513004
[867]
GSM1513005
[868]
GSM1513006
[869]
GSM1513007
[870]
GSM1513008
[871]
GSM1513009
[872]
GSM1513010
[873]
GSM1513011
[874]
GSM1513012
[875]
GSM1513013
[876]
GSM1513014
[877]
GSM1513015
[878]
GSM1513016
[879]
GSM1513017
[880]
GSM1513018
[881]
GSM1513019
[882]
GSM1513020
[883]
GSM1513021
[884]
GSM1513022
[885]
GSM1513023
[886]
GSM1513024
[887]
GSM1513025
[888]
GSM1513026
[889]
GSM1513027
[890]
GSM1513028
[891]
GSM1513029
[892]
GSM1513030
[893]
GSM1513031
[894]
GSM1513032
[895]
GSM1513033
[896]
GSM1513034
[897]
GSM1513035
[898]
GSM1513036
[899]
GSM1513037
[900]
GSM1513038
[901]
GSM1513039
[902]
GSM1513040
[903]
GSM1513041
[904]
GSM1513042
[905]
GSM1513043
[906]
GSM1513044
[907]
GSM1513045
[908]
GSM1513046
[909]
GSM1513047
[910]
GSM1513048
[911]
GSM1513049
[912]
GSM1513050
[913]
GSM1513051
[914]
GSM1513052
[915]
GSM1513053
[916]
GSM1513054
[917]
GSM1513055
[918]
GSM1513056
[919]
GSM1513057
[920]
GSM1513058
[921]
GSM1513059
[922]
GSM1513060
[923]
GSM1513061
[924]
GSM1513062
[925]
GSM1513063
[926]
GSM1513064
[927]
GSM1513065
[928]
GSM1513066
[929]
GSM1513067
[930]
GSM1513068
[931]
GSM1513069
[932]
GSM1513070
[933]
GSM1513071
[934]
GSM1513072
[935]
GSM1513073
[936]
GSM1513074
[937]
GSM1513075
[938]
GSM1513076
[939]
GSM1513077
[940]
GSM1513078
[941]
GSM1513079
[942]
GSM1513080
[943]
GSM1513081
[944]
GSM1513082
[945]
GSM1513083
[946]
GSM1513084
[947]
GSM1513085
[948]
GSM1513086
[949]
GSM1513087
[950]
GSM1513088
[951]
GSM1513089
[952]
GSM1513090
[953]
GSM1513091
[954]
GSM1513092
[955]
GSM1513093
[956]
GSM1513094
[957]
GSM1513095
[958]
GSM1513096
[959]
GSM1513097
[960]
GSM1513098
[961]
GSM1513099
[962]
GSM1513100
[963]
GSM1513101
[964]
GSM1513102
[965]
GSM1513103
[966]
GSM1513104
[967]
GSM1513105
[968]
GSM1513106
[969]
GSM1513107
[970]
GSM1513108
[971]
GSM1513109
[972]
GSM1513110
[973]
GSM1513111
[974]
GSM1513112
[975]
GSM1513113
[976]
GSM1513114
[977]
GSM1513115
[978]
GSM1513116
[979]
GSM1513117
[980]
GSM1513118
[981]
GSM1513119
[982]
GSM1513120
[983]
GSM1513121
[984]
GSM1513122
[985]
GSM1513123
[986]
GSM1513124
[987]
GSM1513125
[988]
GSM1513126
[989]
GSM1513127
[990]
GSM1513128
[991]
GSM1513129
[992]
GSM1513130
[993]
GSM1513131
[994]
GSM1513132
[995]
GSM1513133
[996]
GSM1513134
[997]
GSM1513135
[998]
GSM1513136
[999]
GSM1513137
[1000]
GSM1513138
[1001]
GSM1513139
[1002]
GSM1513140
[1003]
GSM1513141
[1004]
GSM1513142
[1005]
GSM1513143
[1006]
GSM1513144
[1007]
GSM1513145
[1008]
GSM1513146
[1009]
GSM1513147
[1010]
GSM1513148
[1011]
GSM1513149
[1012]
GSM1513150
[1013]
GSM1513151
[1014]
GSM1513152
[1015]
GSM1513153
[1016]
GSM1513154
[1017]
GSM1513155
[1018]
GSM1513156
[1019]
GSM1513157
[1020]
GSM1513158
[1021]
GSM1513159
[1022]
GSM1513160
[1023]
GSM1513161
[1024]
GSM1513162
[1025]
GSM1513163
[1026]
GSM1513164
[1027]
GSM1513165
[1028]
GSM1513166
[1029]
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[1030]
GSM1513168
[1031]
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[1032]
GSM1513170
[1033]
GSM1513171
[1034]
GSM1513172
[1035]
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[1036]
GSM1513174
[1037]
GSM1513175
[1038]
GSM1513176
[1039]
GSM1513177
[1040]
GSM1513178
[1041]
GSM1513179
[1042]
GSM1513180
[1043]
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[1044]
GSM1513182
[1045]
GSM1513183
[1046]
GSM1513184
[1047]
GSM1513185
[1048]
GSM1513186
sample_count
1049
group_sizes
null
group_sizes_basis
null
platform
9040
taxon
Homo sapiens
title
miRNA Profiles in patients and controls
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE66360
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=GSE66360
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE66360
version
null
note
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
access_statement_kind
data_availability_statement
sample_accessions array · 99 items
[0]
GSM1620819
[1]
GSM1620820
[2]
GSM1620821
[3]
GSM1620822
[4]
GSM1620823
[5]
GSM1620824
[6]
GSM1620825
[7]
GSM1620826
[8]
GSM1620827
[9]
GSM1620828
[10]
GSM1620829
[11]
GSM1620830
[12]
GSM1620831
[13]
GSM1620832
[14]
GSM1620833
[15]
GSM1620834
[16]
GSM1620835
[17]
GSM1620836
[18]
GSM1620837
[19]
GSM1620838
[20]
GSM1620839
[21]
GSM1620840
[22]
GSM1620841
[23]
GSM1620842
[24]
GSM1620843
[25]
GSM1620844
[26]
GSM1620845
[27]
GSM1620846
[28]
GSM1620847
[29]
GSM1620848
[30]
GSM1620849
[31]
GSM1620850
[32]
GSM1620851
[33]
GSM1620852
[34]
GSM1620853
[35]
GSM1620854
[36]
GSM1620855
[37]
GSM1620856
[38]
GSM1620857
[39]
GSM1620858
[40]
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[41]
GSM1620860
[42]
GSM1620861
[43]
GSM1620862
[44]
GSM1620863
[45]
GSM1620864
[46]
GSM1620865
[47]
GSM1620866
[48]
GSM1620867
[49]
GSM1620868
[50]
GSM1620869
[51]
GSM1620870
[52]
GSM1620871
[53]
GSM1620872
[54]
GSM1620873
[55]
GSM1620874
[56]
GSM1620875
[57]
GSM1620876
[58]
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[59]
GSM1620878
[60]
GSM1620879
[61]
GSM1620880
[62]
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[63]
GSM1620882
[64]
GSM1620883
[65]
GSM1620884
[66]
GSM1620885
[67]
GSM1620886
[68]
GSM1620887
[69]
GSM1620888
[70]
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[71]
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[72]
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[73]
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[74]
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[75]
GSM1620894
[76]
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[77]
GSM1620896
[78]
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[79]
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[80]
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[81]
GSM1620900
[82]
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[83]
GSM1620902
[84]
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[85]
GSM1620904
[86]
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[87]
GSM1620906
[88]
GSM1620907
[89]
GSM1620908
[90]
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[91]
GSM1620910
[92]
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[93]
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[94]
GSM1620913
[95]
GSM1620914
[96]
GSM1620915
[97]
GSM1620916
[98]
GSM1620917
sample_count
99
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
A Whole Blood Molecular Signature for the Identification of Acute Myocardial Infarction Without Relying Upon Myonecrosis (microarray)
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 15 fields
id
data:geo:GSE97320
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=GSE97320
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE97320
version
null
note
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
access_statement_kind
data_availability_statement
sample_accessions array · 6 items
[0]
GSM2561549
[1]
GSM2561550
[2]
GSM2561551
[3]
GSM2561552
[4]
GSM2561553
[5]
GSM2561554
sample_count
6
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Differential gene expression profiles in peripheral blood in Northeast Chinese Han people with acute myocardial infarction
resolution_checked_at
2026-11-01T18:06:44Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 10 items
[0]
asset:data:geo:GSE168281 not downloaded
[1]
asset:data:geo:GSE168281 licence not read
[2]
asset:data:geo:GSE19339 not downloaded
[3]
asset:data:geo:GSE19339 licence not read
[4]
asset:data:geo:GSE61741 not downloaded
[5]
asset:data:geo:GSE61741 licence not read
[6]
asset:data:geo:GSE66360 not downloaded
[7]
asset:data:geo:GSE66360 licence not read
[8]
asset:data:geo:GSE97320 not downloaded
[9]
asset:data:geo:GSE97320 licence not read
analysis object · 4 fields
state
complete
methods array · 2 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 (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control).
[1] object · 10 fields
id
method-2
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
pathway enrichment
targets array · 0 items
gaps array · 0 items
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
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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 · 5 items
[0]
GSE66360
[1]
GSE19339
[2]
GSE97320
[3]
GSE61741
[4]
GSE168281
resolved_accessions array · 5 items
[0]
GSE66360
[1]
GSE19339
[2]
GSE97320
[3]
GSE61741
[4]
GSE168281
statements array · 1 item
[0]
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
basis
The paper names GSE66360, GSE19339, GSE97320, GSE61741, GSE168281 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 3 items
[0]
normalise_counts
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differential_expression_fit
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fdr_bh
assets array · 2 items
[0]
source:pmid:38457553
[1]
data:geo:GSE168281
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:GSE168281
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
2026-11-01T19:11:05Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
9296
completion_tokens
2225
cached_tokens
256
stages array · 1 item
[0] object · 4 fields
id
extraction
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complete
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MiniMax-M3.1-Flash
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minimax
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review.independent_reader
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review.human_critique
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absent
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not_run
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null
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gaps array · 1 item
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execution.not_run
provenance object · 7 fields
entities array · 3 items
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pmid:38457553
type
paper
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pmid:38457553
[1] object · 3 fields
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source:pmid:38457553
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manuscript
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PMID 38457553 full text
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id
data:geo:GSE168281
type
dataset
label
GEO GSE168281
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
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id
pmid:38457553
type
paper
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pmid:38457553
[1] object · 3 fields
id
source:pmid:38457553
type
manuscript
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PMID 38457553 full text
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id
data:geo:GSE168281
type
dataset
label
GEO GSE168281
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agent:corpus-assay-engine
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id
activity-read-38457553
type
extraction
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[0]
source:pmid:38457553
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE168281
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE168281
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agent:corpus-assay-engine
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agent:corpus-assay-engine
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software
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Corpus assay engine
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id
agent:minimax-reader
type
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MiniMax literature reader
source_run_id
reading-sci-2026-11-01
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343fb30756ba6ec3
capability_table_fingerprint
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ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:38457553
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sha256:b07401c4ad8762c164abc1b2fc8ccfbbc13beda54e6b50f3da60327757a57bf1
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gaps array · 14 items
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asset:data:geo:GSE168281 licence not read
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[3]
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[5]
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[6]
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[7]
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[8]
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[9]
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analysis
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differential_expression
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f2132e96ae6c7a4e
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normalise_counts
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[2]
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control).
order_basis
analysis_only
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assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38457553", "kind": "science-record", "revision": 5, "content_hash": "sha256:fc28db77d1f332a473803ec89ac4be9a916e1aae8154655b64b24ca1be1d3bdf", "created_at": "2026-11-01T19:20:23Z", "updated_at": "2026-11-01T22:53:50Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction of LncRNA-mediated CeRNA network for investigating the immune pathogenesis of myocardial infarction.", "doi": "10.1097/MD.0000000000037413", "pmid": "38457553", "authors": ["Dongmei Wei", "Yuanting Meng", "Hua Fan", "Yang Sun", "Rongtao Chen"], "journal": "Medicine", "year": 2024, "abstract": "BACKGROUND: Myocardial infarction (MI) is a cardiovascular disease that seriously threatens human health. However, an immune-related competitive endogenous RNA (ceRNA) network has not been reported in MI.\nMETHODS: The GSE66360, GSE19339, GSE97320, GSE61741, and GSE168281 datasets were acquired from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) from MI patients and healthy controls were screened and an immune-related ceRNA network was constructed. Furthermore, the key long noncoding RNAs(lncRNAs) highly related to the immune mechanism of MI were identified utilizing the random walk with restart algorithm. Finally, the expression of the hub genes was further verified in the GSE66360, GSE19339, and GSE97320 datasets, and quantitativereal-time polymerase chain reaction (qRT-PCR) was performed for the MI patients and healthy controls.\nRESULTS: A total of 184 differentially expressed immune-related genes(DE-IRGs) and 432 DE-miRNAs were obtained, and an immune-related ceRNA network comprising 1421 lncRNAs, 61 DE-miRNAs, and 139 DE-IRGs was constructed. According to the order of stress, betweenness, and closeness, NEAT1, KCNQ1OT1, and XIST were identified as key lncRNAs. Moreover, random walk with restart analysis also suggested that NEAT1, KCNQ1OT1, and XIST are key lncRNAs. Subsequently, a ceRNA network of 10 hub genes and 3 lncRNAs was constructed. Finally, we found that the expression of FCER1G and TYROBP significantly differed between MI patients and control individuals in the GSE66360, GSE19339, and GSE97320 datasets. qRT-PCR revealed that the expression of NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP was significantly elevated in MI tissue samples compared to healthy control tissue samples.\nCONCLUSION: NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI. Furthermore, the immune system plays an essential role in the onset and progression of MI.", "claims": [{"id": "claim-method", "statement": "The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38457553", "locator": "sections[4] \"2.2. Differential expression analysis\" paragraph 2", "quote": "The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38457553", "locator": "sections[24] \"fn-group\" paragraph 1", "quote": "The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38457553", "locator": "sections[0] \"Abstract\" paragraph 6", "quote": "NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI.", "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:38457553"], "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:GSE168281"], "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:GSE168281"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38457553", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1097/MD.0000000000037413", "sha256": "sha256:dbca2d55b9a5d9eca91dd9b42cc5037c40ab295e56af9cdf943c255abb2f49be", "bytes": 30586, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1097/MD.0000000000037413", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10919540", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE168281", "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=GSE168281", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE168281", "version": null, "note": "The datasets generated during and/or analyzed during the current study are available from the corresponding 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