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pmid:34332599

Extracellular vesicle-derived AEBP1 mRNA as a novel candidate biomarker for diabetic kidney disease.

Yiying Tao · Xing Wei · Yue Yue · Jiaxin Wang · Jianzhong Li · Lei Shen · Guoyuan Lu · Yang He · Shidi Zhao · Fan Zhao · Zhen Weng · Xiahong Shen · Ling Zhou

Journal of translational medicine · 2021 doi:10.1186/s12967-021-03000-3

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:34332599
kind
science-record
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sha256:5e41261260bd2f78a4078b8026c4285d69458aef361cf0c078000fb07ce9a991
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:41:46Z
updated_at
2026-11-01T22:04:22Z
generator object · 2 fields
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paper object · 10 fields
state
complete
title
Extracellular vesicle-derived AEBP1 mRNA as a novel candidate biomarker for diabetic kidney disease.
doi
10.1186/s12967-021-03000-3
pmid
34332599
authors array · 13 items
[0]
Yiying Tao
[1]
Xing Wei
[2]
Yue Yue
[3]
Jiaxin Wang
[4]
Jianzhong Li
[5]
Lei Shen
[6]
Guoyuan Lu
[7]
Yang He
[8]
Shidi Zhao
[9]
Fan Zhao
[10]
Zhen Weng
[11]
Xiahong Shen
[12]
Ling Zhou
journal
Journal of translational medicine
year
2021
abstract
BACKGROUND: A novel and improved methodology is still required for the diagnosis of diabetic kidney disease (DKD). The aim of the present study was to identify novel biomarkers using extracellular vesicle (EV)-derived mRNA based on kidney tissue microarray data. METHODS: Candidate genes were identified by intersecting the differentially expressed genes (DEGs) and eGFR-correlated genes using the GEO datasets GSE30528 and GSE96804, followed by clinical parameter correlation and diagnostic efficacy assessment. RESULTS: Fifteen intersecting genes, including 8 positively correlated genes, B3GALT2, CDH10, MIR3916, NELL1, OCLM, PRKAR2B, TREM1 and USP46, and 7 negatively correlated genes, AEBP1, CDH6, HSD17B2, LUM, MS4A4A, PTN and RASSF9, were confirmed. The expression level assessment results revealed significantly increased levels of AEBP1 in DKD-derived EVs compared to those in T2DM and control EVs. Correlation analysis revealed that AEBP1 levels were positively correlated with Cr, 24-h urine protein and serum CYC and negatively correlated with eGFR and LDL, and good diagnostic efficacy for DKD was also found using AEBP1 levels to differentiate DKD patients from T2DM patients or controls. CONCLUSIONS: Our results confirmed that the AEBP1 level from plasma EVs could differentiate DKD patients from T2DM patients and control subjects and was a good indication of the function of multiple critical clinical parameters. The AEBP1 level of EVs may serve as a novel and efficacious biomarker for DKD diagnosis.
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Correlation analysis between the clinical parameters and AEBP1 expression level was performed using Pearson correlation. The diagnostic efficacy was calculated by receiver operator characteristic (ROC) curves and area under the curve (AUC) (survivalROC and ROCR R packages).
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methodological
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null
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sections[8] "Statistical analysis" paragraph 2
quote
Correlation analysis between the clinical parameters and AEBP1 expression level was performed using Pearson correlation. The diagnostic efficacy was calculated by receiver operator characteristic (ROC) curves and area under the curve (AUC) (survivalROC and ROCR R packages).
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All data generated or analysed during this study are included in this published article [and its additional files].
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sections[22] "notes" paragraph 1
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All data generated or analysed during this study are included in this published article [and its additional files].
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null
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The claim, method and evidence span published with the source article.
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the published estimate and its evidence
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Obtain the source data from the named repository
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the source data with its repository provenance
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Apply the paper's statistical method to the resolved series and compare the result with the published target.
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[1]
GSM756993
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GSM757008
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GSM757011
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GSM757012
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GSM757013
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22
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null
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null
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571
taxon
Homo sapiens
title
Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Glomeruli vs. Control Glomeruli)
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2026-11-01T15:39:54Z
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All data generated or analysed during this study are included in this published article [and its additional files].
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sample_accessions array · 22 items
[0]
GSM757014
[1]
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GSM757016
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GSM757017
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GSM757018
[5]
GSM757019
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GSM757020
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GSM757021
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GSM757022
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GSM757023
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GSM757024
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GSM757025
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GSM757026
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GSM757027
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GSM757031
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GSM757032
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GSM757033
[20]
GSM757034
[21]
GSM757035
sample_count
22
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null
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null
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571
taxon
Homo sapiens
title
Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Tubuli vs. Control Tubuli)
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2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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reader_required
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GSE33744
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null
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All data generated or analysed during this study are included in this published article [and its additional files].
structure object · 15 fields
repository
GEO
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GEO accession URL
access_statement_verbatim
All data generated or analysed during this study are included in this published article [and its additional files].
access_statement_kind
data_availability_statement
sample_accessions array · 39 items
[0]
GSM833993
[1]
GSM833994
[2]
GSM833995
[3]
GSM833996
[4]
GSM833997
[5]
GSM833998
[6]
GSM833999
[7]
GSM834000
[8]
GSM834001
[9]
GSM834002
[10]
GSM834003
[11]
GSM834004
[12]
GSM834005
[13]
GSM834006
[14]
GSM834007
[15]
GSM834008
[16]
GSM834009
[17]
GSM834010
[18]
GSM834011
[19]
GSM834012
[20]
GSM834013
[21]
GSM834014
[22]
GSM834015
[23]
GSM834016
[24]
GSM834017
[25]
GSM834018
[26]
GSM834019
[27]
GSM834020
[28]
GSM834021
[29]
GSM834022
[30]
GSM834023
[31]
GSM834024
[32]
GSM834025
[33]
GSM834026
[34]
GSM834027
[35]
GSM834028
[36]
GSM834029
[37]
GSM834030
[38]
GSM834031
sample_count
39
group_sizes
null
group_sizes_basis
null
platform
1261
taxon
Mus musculus
title
Cross-species transcriptional networks in Diabetic Glomerulopathy in mouse and man
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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data:geo:GSE96804
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raw
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geo-series
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application/vnd.ncbi.geo-series+json
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE96804
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null
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null
access
open
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resolved
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null
reader_status
reader_required
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GSE96804
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null
note
All data generated or analysed during this study are included in this published article [and its additional files].
structure object · 15 fields
repository
GEO
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GEO accession URL
access_statement_verbatim
All data generated or analysed during this study are included in this published article [and its additional files].
access_statement_kind
data_availability_statement
sample_accessions array · 61 items
[0]
GSM2544275
[1]
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[2]
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[3]
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[4]
GSM2544279
[5]
GSM2544280
[6]
GSM2544281
[7]
GSM2544282
[8]
GSM2544283
[9]
GSM2544284
[10]
GSM2544285
[11]
GSM2544286
[12]
GSM2544287
[13]
GSM2544288
[14]
GSM2544289
[15]
GSM2544290
[16]
GSM2544291
[17]
GSM2544292
[18]
GSM2544293
[19]
GSM2544294
[20]
GSM2544295
[21]
GSM2544296
[22]
GSM2544297
[23]
GSM2544298
[24]
GSM2544299
[25]
GSM2544300
[26]
GSM2544301
[27]
GSM2544302
[28]
GSM2544303
[29]
GSM2544304
[30]
GSM2544305
[31]
GSM2544306
[32]
GSM2544307
[33]
GSM2544308
[34]
GSM2544309
[35]
GSM2544310
[36]
GSM2544311
[37]
GSM2544312
[38]
GSM2544313
[39]
GSM2544314
[40]
GSM2544315
[41]
GSM2544316
[42]
GSM2544317
[43]
GSM2544318
[44]
GSM2544319
[45]
GSM2544320
[46]
GSM2544321
[47]
GSM2544322
[48]
GSM2544323
[49]
GSM2544324
[50]
GSM2544325
[51]
GSM2544326
[52]
GSM2544327
[53]
GSM2544328
[54]
GSM2544329
[55]
GSM2544330
[56]
GSM2544331
[57]
GSM2544332
[58]
GSM2544333
[59]
GSM2544334
[60]
GSM2544335
sample_count
61
group_sizes
null
group_sizes_basis
null
platform
17586
taxon
Homo sapiens
title
Exon Level Expression Profiling of Diabetic Nephropathy
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
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Clinical characteristics of the included subjects
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PMC8325821
section_index
3
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Patient inclusion and clinical data collection
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30
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5
table object · 8 fields
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Table 1
caption
Clinical characteristics of the included subjects
rows array · 30 items
[0] array · 5 items
[0]
Clinical parameters
[1]
Control (n = 10)
[2]
T2DM (n = 15)
[3]
DKD (n = 15)
[4]
P-value
[1] array · 5 items
[0]
Age (yrs)
[1]
47.10 ± 9.27
[2]
48.00 ± 10.95
[3]
60.13 ± 11.76
[4]
0.0048
[2] array · 5 items
[0]
Gender (female, %)
[1]
3 (30.00%)
[2]
4(26.67%)
[3]
2 (13.33%)
[4]
0.5585
[3] array · 5 items
[0]
BMI
[1]
23.75 ± 3.54
[2]
26.33 ± 5.77
[3]
24.80 ± 2.16
[4]
0.3081
[4] array · 5 items
[0]
SBP (mmHg)
[1]
127.10 ± 16.96
[2]
123.07 ± 10.07
[3]
155.50 ± 20.18
[4]
< 0.0001
[5] array · 5 items
[0]
DBP (mmHg)
[1]
82.50 (78.75–85.50)
[2]
81.00 (76.00–85.00)
[3]
85.00 (81.00–90.00)
[4]
0.4273
[6] array · 5 items
[0]
T2DM duration (yrs)
[1]
–
[2]
2(0.25–8)
[3]
10 (10–20)
[4]
< 0.0001
[7] array · 5 items
[0]
HbA1c (%)
[1]
–
[2]
10.32 ± 2.24
[3]
7.34 ± 1.26
[4]
< 0.0001
[8] array · 5 items
[0]
eGFR (MDRD, ml/min/1.73m2)
[1]
133.95 ± 32.80
[2]
143.73 ± 30.72
[3]
18.59 ± 12.64
[4]
< 0.0001
[9] array · 5 items
[0]
eGFR (CKD-EPI, ml/min/1.73m2)
[1]
107.19 ± 16.53
[2]
116.34 ± 13.32
[3]
18.05 ± 12.87
[4]
< 0.0001
[10] array · 5 items
[0]
BUN (mmol/L)
[1]
4.75 ± 1.10
[2]
5.20 ± 1.89
[3]
19.17 ± 10.53
[4]
< 0.0001
[11] array · 5 items
[0]
Creatinine (µmol/L)
[1]
57.83 ± 11.96
[2]
55.70 ± 11.48
[3]
465.72 ± 342.07
[4]
< 0.0001
[12] array · 5 items
[0]
TC (mmol/L)
[1]
4.71 ± 0.87
[2]
4.72 ± 0.83
[3]
4.85 ± 1.82
[4]
0.9483
[13] array · 5 items
[0]
TG (mmol)
[1]
0.85(0.54–2.34)
[2]
1.77(1.57–3.02)
[3]
1.49 (1.27–2.95)
[4]
0.0791
[14] array · 5 items
[0]
LDL (mmol/L)
[1]
–
[2]
2.62 ± 0.84
[3]
2.55 ± 1.33
[4]
0.8668
[15] array · 5 items
[0]
HDL (mmol/L)
[1]
–
[2]
0.93 ± 0.27
[3]
0.91 ± 0.17
[4]
0.8344
[16] array · 5 items
[0]
24-h urine protein (g/d)
[1]
–
[2]
–
[3]
6.92 ± 3.10
[4]
–
[17] array · 5 items
[0]
Urine protein to creatinine ratio
[1]
–
[2]
0.06 ± 0.04
[3]
4.87 ± 2.03
[4]
< 0.0001
[18] array · 5 items
[0]
Albumin (g/L)
[1]
43.47 ± 1.81
[2]
40.42 ± 3.10
[3]
30.37 ± 6.26
[4]
< 0.0001
[19] array · 5 items
[0]
Albumin/creatinine ratio (mg/g)
[1]
3.44 (0.22–6.49)
[2]
–
[3]
2692.30 (1251.19–4346.50)
[4]
< 0.0001
[20] array · 5 items
[0]
Urine β2MG (mg/L)
[1]
0.21 (0.04–0.27)
[2]
–
[3]
20.83 (12.07–31.28)
[4]
< 0.0001
[21] array · 5 items
[0]
Urine RBP (mg/L)
[1]
0.15 (0.01–0.42)
[2]
–
[3]
13.40 (7.80–18.54)
[4]
< 0.0001
[22] array · 5 items
[0]
Urine CYC (mg/L)
[1]
0.01 (0.01–0.11)
[2]
–
[3]
1.58 (0.82–2.21)
[4]
< 0.0001
[23] array · 5 items
[0]
Serum CYC (mg/L)
[1]
–
[2]
0.78 ± 0.07
[3]
3.64 ± 1.71
[4]
< 0.0001
[24] array · 5 items
[0]
Hemoglobin (g/L)
[1]
137.20 ± 8.64
[2]
141.47 ± 13.63
[3]
94.40 ± 17.76
[4]
< 0.0001
[25] array · 5 items
[0]
WBC (109/L)
[1]
6.15 ± 1.06
[2]
6.23 ± 1.04
[3]
6.10 ± 1.87
[4]
0.9712
[26] array · 5 items
[0]
Monocytes (109/L)
[1]
0.43 ± 0.07
[2]
0.45 ± 0.13
[3]
0.51 ± 0.28
[4]
0.5720
[27] array · 5 items
[0]
Lymphocytes (109/L)
[1]
2.11 ± 0.59
[2]
2.12 ± 0.47
[3]
1.45 ± 1.20
[4]
0.0685
[28] array · 5 items
[0]
Neutrophils (109/L)
[1]
3.45 ± 0.98
[2]
3.50 ± 1.03
[3]
4.12 ± 1.45
[4]
0.2756
[29] array · 5 items
[0]
hsCRP (mg/L)
[1]
–
[2]
1.51(1.13–2.88)
[3]
1.92(0.61–3.18)
[4]
0.9907
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section[3]/table-wrap[1]#Tab1
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Correlation coefficient and gene function of 15 intersected genes
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pmcid
PMC8325821
section_index
10
section_title
Identification of candidate genes and pathway analysis
row_count
16
column_count
3
table object · 8 fields
label
Table 2
caption
Correlation coefficient and gene function of 15 intersected genes
rows array · 16 items
[0] array · 3 items
[0]
Gene names
[1]
R value
[2]
P value
[1] array · 3 items
[0]
AEBP1
[1]
− 0.68
[2]
0.042
[2] array · 3 items
[0]
B3GALT2
[1]
0.83
[2]
0.0047
[3] array · 3 items
[0]
CDH10
[1]
0.67
[2]
0.046
[4] array · 3 items
[0]
CDH6
[1]
− 0.73
[2]
0.025
[5] array · 3 items
[0]
HSD17B2
[1]
− 0.74
[2]
0.021
[6] array · 3 items
[0]
LUM
[1]
− 0.69
[2]
0.041
[7] array · 3 items
[0]
MIR3916
[1]
0.67
[2]
0.047
[8] array · 3 items
[0]
MS4A4A
[1]
− 0.91
[2]
0.00079
[9] array · 3 items
[0]
NELL1
[1]
0.80
[2]
0.0092
[10] array · 3 items
[0]
OCLM
[1]
0.73
[2]
0.023
[11] array · 3 items
[0]
PRKAR2B
[1]
0.72
[2]
0.028
[12] array · 3 items
[0]
PTN
[1]
− 0.84
[2]
0.0043
[13] array · 3 items
[0]
RASSF9
[1]
− 0.67
[2]
0.049
[14] array · 3 items
[0]
TREM1
[1]
0.77
[2]
0.014
[15] array · 3 items
[0]
USP46
[1]
0.68
[2]
0.046
locator
section[10]/table-wrap[1]#Tab2
[7] object · 16 fields
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asset:table:pmid:34332599:3
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:1f68f7c93f1468be64d9347f2b3542f29426d59a1a99ddeb808ba4194900c248
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835
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read_table
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available
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section[11]/table-wrap[1]#Tab3
version
null
note
Significantly up and down-regulated genes in different microarray datasets among the 15 intersected genes
structure object · 5 fields
pmcid
PMC8325821
section_index
11
section_title
Identification of the expression pattern of 15 intersecting genes
row_count
6
column_count
4
table object · 8 fields
label
Table 3
caption
Significantly up and down-regulated genes in different microarray datasets among the 15 intersected genes
rows array · 6 items
[0] array · 4 items
[0]
Microarray set no.
[1]
Sample type
[2]
Up
[3]
Down
[1] array · 4 items
[0]
GSE30528
[1]
Human DKD and control glomeruli samples
[2]
AEBP1, CDH6, LUM, MS4A4A
[3]
B3GALT2, CDH10, NELL1, PRKAR2B, USP46
[2] array · 4 items
[0]
GSE30529
[1]
Human DKD and control tubuli samples
[2]
AEBP1, CDH6, LUM, MS4A4A, PRKAR2B
[3]
B3GALT2, CDH10, NELL1, OCLM
[3] array · 4 items
[0]
GSE33744
[1]
Glomeruli samples from Diabetic BKS db/db mice
[2]
AEBP1, B3GALT2, NELL1, PRKAR2B
[3]
HSD17B2
[4] array · 4 items
[0]
GSE33744
[1]
Glomeruli samples from Diabetic DBA-STZ mice
[2]
AEBP1
[3]
HSD17B2
[5] array · 4 items
[0]
GSE33744
[1]
Glomeruli samples from Diabetic BKS db/db eNOS −/− mice
[2]
[3]
HSD17B2, PTN, RASSF9, USP46
locator
section[11]/table-wrap[1]#Tab3
[8] object · 16 fields
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asset:table:pmid:34332599:4
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table
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jats-table
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application/vnd.jats.table+json
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sha256:fd864b7f8df7f4ba3835cf1edc613dfd6377e8b572bad5bfa2d0e66f6dbefbc7
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section[13]/table-wrap[1]#Tab4
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note
Correlation between exosome AEBP1 level and clinical parameters in DKD patients
structure object · 5 fields
pmcid
PMC8325821
section_index
13
section_title
Correlation between the expression level of EV-derived AEBP1 and clinical indexes of DKD and exploration of the diagnostic efficacy of AEBP1
row_count
29
column_count
3
table object · 8 fields
label
Table 4
caption
Correlation between exosome AEBP1 level and clinical parameters in DKD patients
rows array · 29 items
[0] array · 2 items
[0]
Clinical parameters
[1]
Exosome AEBP1 level
[1] array · 2 items
[0]
R value
[1]
P value
[2] array · 3 items
[0]
Age (yrs)
[1]
− 0.283
[2]
0.307
[3] array · 3 items
[0]
BMI
[1]
− 0.242
[2]
0.384
[4] array · 3 items
[0]
SBP (mmHg)
[1]
− 0.309
[2]
0.263
[5] array · 3 items
[0]
DBP (mmHg)
[1]
− 0.140
[2]
0.619
[6] array · 3 items
[0]
HbA1c (%)
[1]
− 0.062
[2]
0.827
[7] array · 3 items
[0]
eGFR (MDRD, ml/min/1.73m2)
[1]
− 0.614
[2]
0.0015
[8] array · 3 items
[0]
eGFR (CKD-EPI, ml/min/1.73m2)
[1]
− 0.59
[2]
0.020
[9] array · 3 items
[0]
BUN (mmol/L)
[1]
0.298
[2]
0.280
[10] array · 3 items
[0]
Creatinine (µmol/L)
[1]
0.629
[2]
0.012
[11] array · 3 items
[0]
TC (mmol/L)
[1]
− 0.170
[2]
0.545
[12] array · 3 items
[0]
TG (mmol)
[1]
− 0.161
[2]
0.567
[13] array · 3 items
[0]
LDL (mmol/L)
[1]
− 0.556
[2]
0.031
[14] array · 3 items
[0]
HDL (mmol/L)
[1]
− 0.034
[2]
0.905
[15] array · 3 items
[0]
24-h urine protein (g/d)
[1]
0.559
[2]
0.0304
[16] array · 3 items
[0]
Urine protein to creatinine ratio
[1]
− 0.079
[2]
0.778
[17] array · 3 items
[0]
Albumin (g/L)
[1]
− 0.335
[2]
0.222
[18] array · 3 items
[0]
Albumin/creatinine ratio (mg/g)
[1]
0.258
[2]
0.374
[19] array · 3 items
[0]
Urine β2MG (mg/L)
[1]
− 0.003
[2]
0.993
[20] array · 3 items
[0]
Urine RBP (mg/L)
[1]
0.357
[2]
0.255
[21] array · 3 items
[0]
Urine CYC (mg/L)
[1]
− 0.189
[2]
0.667
[22] array · 3 items
[0]
Serum CYC (mg/L)
[1]
0.656
[2]
0.008
[23] array · 3 items
[0]
Hemoglobin (g/L)
[1]
− 0.424
[2]
0.116
[24] array · 3 items
[0]
WBC (109/L)
[1]
− 0.101
[2]
0.719
[25] array · 3 items
[0]
Monocytes (109/L)
[1]
− 0.068
[2]
0.810
[26] array · 3 items
[0]
Lymphocytes (109/L)
[1]
− 0.157
[2]
0.576
[27] array · 3 items
[0]
Neutrophils (109/L)
[1]
− 0.041
[2]
0.885
[28] array · 3 items
[0]
hsCRP (mg/L)
[1]
0.474
[2]
0.074
locator
section[13]/table-wrap[1]#Tab4
gaps array · 8 items
[0]
asset:data:geo:GSE30528 not downloaded
[1]
asset:data:geo:GSE30528 licence not read
[2]
asset:data:geo:GSE30529 not downloaded
[3]
asset:data:geo:GSE30529 licence not read
[4]
asset:data:geo:GSE33744 not downloaded
[5]
asset:data:geo:GSE33744 licence not read
[6]
asset:data:geo:GSE96804 not downloaded
[7]
asset:data:geo:GSE96804 licence not read
analysis object · 4 fields
state
partial
methods array · 2 items
[0] object · 10 fields
id
method-1
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correlation_analysis
specific
pearson
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Correlation analysis
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[0]
pearson_r
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data_shapes array · 1 item
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paired_numeric_columns
evidence object · 3 fields
score
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verbatim
quote
Correlation analysis between the clinical parameters and AEBP1 expression level was performed using Pearson correlation. The diagnostic efficacy was calculated by receiver operator characteristic (ROC) curves and area under the curve (AUC) (survivalROC and ROCR R packages).
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group_comparison
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Group comparison
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[0]
group_summary
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welch_t
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bootstrap_mean_difference
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group_comparison_anova
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two_or_more_groups_continuous
evidence object · 3 fields
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0.8
band
high
quote
ANOVA
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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
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statistical_regression
[4]
pca
[5]
molecular_docking
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network_analysis
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differential_expression
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gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
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method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
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pearson_r
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: pearson.
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 · 4 items
[0]
GSE96804
[1]
GSE30528
[2]
GSE30529
[3]
GSE33744
resolved_accessions array · 4 items
[0]
GSE96804
[1]
GSE30528
[2]
GSE30529
[3]
GSE33744
statements array · 1 item
[0]
All data generated or analysed during this study are included in this published article [and its additional files].
basis
The paper names GSE96804, GSE30528, GSE30529, GSE33744 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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dsl_operations array · 1 item
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pearson_r
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source:pmid:34332599
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data:geo:GSE30528
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asset:table:pmid:34332599:1
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asset:table:pmid:34332599:2
[4]
asset:table:pmid:34332599:3
[5]
asset:table:pmid:34332599:4
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[0]
run_analysis
must_build object · 5 fields
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data:geo:GSE30528
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review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:33:03Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
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3
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prompt_tokens
28926
completion_tokens
2013
cached_tokens
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id
extraction
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complete
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minimax
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review.independent_reader
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review.machine_critique
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review.human_critique
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state
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execution.not_run
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pmid:34332599
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paper
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pmid:34332599
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source:pmid:34332599
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PMID 34332599 full text
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data:geo:GSE30528
type
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GEO GSE30528
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pmid:34332599
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source:pmid:34332599
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PMID 34332599 full text
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data:geo:GSE30528
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GEO GSE30528
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agent:corpus-assay-engine
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agent:minimax-reader
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agent:corpus-assay-engine
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agent:minimax-reader
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MiniMax literature reader
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dsl_catalogue_fingerprint
343fb30756ba6ec3
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parent_id
pmid:34332599
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sha256:a3bb949b26b5492545c2160f881f33e86efef6db91d11ed0a4a32d6fff28cf48
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asset:data:geo:GSE30528 licence not read
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[3]
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[4]
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[5]
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[6]
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execution.not_run
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99e1195c7d6f
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99e1195c7d6f
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[0]
cle (EV)-derived mRNA based on kidney tissue microarray data. METHODS: Candidate genes were identifi
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paper_text_order:302
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tron microscopy (Fig. 5A), DLS (Fig. 5B) and western blotting results (Fig. 5C), we obtained round morphol
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f2132e96ae6c7a4e
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Correlation analysis between the clinical parameters and AEBP1 expression level was performed using Pearson correlation. The diagnostic efficacy was calculated by receiver operator characteristic (ROC) curves and area under the curve (AUC) (survivalROC and ROCR R packages).
order_basis
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34332599", "kind": "science-record", "revision": 7, "content_hash": "sha256:5e41261260bd2f78a4078b8026c4285d69458aef361cf0c078000fb07ce9a991", "created_at": "2026-11-01T15:41:46Z", "updated_at": "2026-11-01T22:04:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Extracellular vesicle-derived AEBP1 mRNA as a novel candidate biomarker for diabetic kidney disease.", "doi": "10.1186/s12967-021-03000-3", "pmid": "34332599", "authors": ["Yiying Tao", "Xing Wei", "Yue Yue", "Jiaxin Wang", "Jianzhong Li", "Lei Shen", "Guoyuan Lu", "Yang He", "Shidi Zhao", "Fan Zhao", "Zhen Weng", "Xiahong Shen", "Ling Zhou"], "journal": "Journal of translational medicine", "year": 2021, "abstract": "BACKGROUND: A novel and improved methodology is still required for the diagnosis of diabetic kidney disease (DKD). The aim of the present study was to identify novel biomarkers using extracellular vesicle (EV)-derived mRNA based on kidney tissue microarray data.\nMETHODS: Candidate genes were identified by intersecting the differentially expressed genes (DEGs) and eGFR-correlated genes using the GEO datasets GSE30528 and GSE96804, followed by clinical parameter correlation and diagnostic efficacy assessment.\nRESULTS: Fifteen intersecting genes, including 8 positively correlated genes, B3GALT2, CDH10, MIR3916, NELL1, OCLM, PRKAR2B, TREM1 and USP46, and 7 negatively correlated genes, AEBP1, CDH6, HSD17B2, LUM, MS4A4A, PTN and RASSF9, were confirmed. The expression level assessment results revealed significantly increased levels of AEBP1 in DKD-derived EVs compared to those in T2DM and control EVs. Correlation analysis revealed that AEBP1 levels were positively correlated with Cr, 24-h urine protein and serum CYC and negatively correlated with eGFR and LDL, and good diagnostic efficacy for DKD was also found using AEBP1 levels to differentiate DKD patients from T2DM patients or controls.\nCONCLUSIONS: Our results confirmed that the AEBP1 level from plasma EVs could differentiate DKD patients from T2DM patients and control subjects and was a good indication of the function of multiple critical clinical parameters. The AEBP1 level of EVs may serve as a novel and efficacious biomarker for DKD diagnosis.", "claims": [{"id": "claim-method", "statement": "Correlation analysis between the clinical parameters and AEBP1 expression level was performed using Pearson correlation. 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