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pmid:34588774

Transcriptomics Analysis Identifies the Presence of Upregulated Ribosomal Housekeeping Genes in the Alveolar Macrophages of Patients with Smoking-Induced Chronic Obstructive Pulmonary Disease.

Li Han · Jing Wang · Xiao-Bin Ji · Zai-Yan Wang · Yi Wang · Li-Yue Zhang · Hong-Peng Li · Ze-Ming Zhang · Qing-Yun Li

International journal of chronic obstructive pulmonary disease · 2021 doi:10.2147/COPD.S313252

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:34588774
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2026-11-01T15:41:54Z
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2026-11-01T22:47:37Z
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paper object · 10 fields
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title
Transcriptomics Analysis Identifies the Presence of Upregulated Ribosomal Housekeeping Genes in the Alveolar Macrophages of Patients with Smoking-Induced Chronic Obstructive Pulmonary Disease.
doi
10.2147/COPD.S313252
pmid
34588774
authors array · 9 items
[0]
Li Han
[1]
Jing Wang
[2]
Xiao-Bin Ji
[3]
Zai-Yan Wang
[4]
Yi Wang
[5]
Li-Yue Zhang
[6]
Hong-Peng Li
[7]
Ze-Ming Zhang
[8]
Qing-Yun Li
journal
International journal of chronic obstructive pulmonary disease
year
2021
abstract
BACKGROUND AND AIMS: Alveolar macrophages (AM) play a crucial role in the development of chronic obstructive pulmonary disease (COPD). The role that AM plays in the molecular pathways and clinical phenotypes associated with tobacco-related emphysema remain poorly understood. Thus, we investigated the transcriptomic profile of AM in COPD patients with a history of smoking and explored the molecular mechanisms associated with enriched pathways and hub genes. METHODS: Four data sets (GSE2125, GSE8823, GSE13896 and GSE130928) were retrieved from the GEO Database. A total of 203 GEO samples (GSM) were collated for this study. About 125 of these cases were classified as smokers (91 as healthy non-COPD smokers and 34 as COPD smokers). Based on the bioinformatics obtained using the R3.6.1 program, the data were successively adopted for differential genetic expression analysis, enrichment analysis (EA), and then protein-protein interaction analysis (PPI) in a STRING database. Finally, Cytoscape 3.8 software was used to screen the hub genes. A further data analysis was performed using a set of 154 cases, classified as 64 healthy non-smokers and 91 as healthy smokers. The same procedures were used as for the COPD dataset. RESULTS: When comparing the data pertaining to COPD-smokers and non-COPD smokers, the top ten genes with the greatest transcriptional differences were found to be NADK, DRAP1, DEDD, NONO, KLHL12, PRKAR1A, ITGAL, GLE1, SLC8A1, SVIL. A GSEA (Gene Set Enrichment Analysis) revealed that these genes manifested an up-regulated ribosomal pathway in contrast with other genes that exhibited an extensive down-regulated pathway. The hub genes were mainly genes encoding ribosomal subunits through PPI. Furthermore, it was found that there is a narrow transcriptional difference between healthy non-smokers and non-COPD smokers and the hub genes identified here are mainly members of the chemokines, including CCL5, CCR5, CXCL9 and CXCL11. CONCLUSION: An elevated activity of the ribosome pathway in addition to the increased expression of ribosomal housekeeping genes (also known as hub genes) were identified with COPD-smokers, and these have the potential to cause a wide range of downstream pathogenetic effects. As for the preclinical phase, non-COPD smokers were found to be characterized by enriched pathways of several chemokines in AM.
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Following the process of the batch effect (Figure 2), analysis and visualization of the differentially expressed genes (DEGs), including a PCA (principal component analysis) chart, heat-map and volcano plot were performed using “means” of the corresponding R package “limma”;
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Following the process of the batch effect (Figure 2), analysis and visualization of the differentially expressed genes (DEGs), including a PCA (principal component analysis) chart, heat-map and volcano plot were performed using “means” of the corresponding R package “limma”;
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A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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sections[2] "Materials and Methods" paragraph 2
quote
A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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Alveolar macrophage immunometabolism and lung function impairment in smoking and chronic obstructive pulmonary disease
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A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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Homo sapiens
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Smoking-dependent Reprogramming of Alveolar Macrophage Polarization: Implication for Pathogenesis of COPD
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A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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title
isolated alveolar macrophages
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A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
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The Top 10 Genes with Most Significant Difference of Transcription Between Relevant Groups
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Differential Gene Expression
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The Top 10 Genes with Most Significant Difference of Transcription Between Relevant Groups
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[0] array · 7 items
[0]
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[1]
Entrez ID
[2]
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[3]
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[5]
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[6]
Adj.P
[1] array · 7 items
[0]
The COPD vs non-COPD smokers
[1]
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[3]
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[6]
1.18E-09
[2] array · 6 items
[0]
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[1]
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[5]
2.40E-09
[3] array · 6 items
[0]
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Death Effector Domain Containing
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3.74E-09
[4] array · 6 items
[0]
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[1]
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Non-POU Domain Containing Octamer Binding
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6.67E-09
[5] array · 6 items
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6.67E-09
[6] array · 6 items
[0]
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[1]
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Protein Kinase CAMP-Dependent Type I Regulatory Subunit Alpha
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[5]
6.67E-09
[7] array · 6 items
[0]
3683
[1]
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Integrin Subunit Alpha L
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−0.939391902
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6.67E-09
[8] array · 6 items
[0]
2733
[1]
GLE1
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GLE1 RNA Export Mediator
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−0.762754132
[5]
7.34E-09
[9] array · 6 items
[0]
6546
[1]
SLC8A1
[2]
Solute Carrier Family 8 Member A1
[3]
Down
[4]
−0.860251027
[5]
1.54E-08
[10] array · 6 items
[0]
6840
[1]
SVIL
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Supervillin
[3]
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−0.839944317
[5]
1.87E-08
[11] array · 7 items
[0]
The non-COPD smokers vs non-smokers
[1]
227399
[2]
VGLL3
[3]
Vestigial Like Family Member 3
[4]
Down
[5]
−2.194799911
[6]
1.49E-22
[12] array · 6 items
[0]
226679
[1]
SLC26A11
[2]
Solute Carrier Family 26 Member 11
[3]
Up
[4]
0.980624248
[5]
2.78E-19
[13] array · 6 items
[0]
225224
[1]
NOL4L
[2]
Nucleolar Protein 4 Like
[3]
Down
[4]
−0.840477441
[5]
2.36E-18
[14] array · 6 items
[0]
1553151
[1]
ATP6V0D2
[2]
ATPase H+ Transporting V0 Submit D2
[3]
Up
[4]
1.759028091
[5]
1.37E-16
[15] array · 6 items
[0]
205055
[1]
ITGAE
[2]
Integrin Subunit Alpha E
[3]
Up
[4]
0.864863449
[5]
1.63E-16
[16] array · 6 items
[0]
219572
[1]
CADPS2
[2]
Calcium Dependent Secretion Activator 2
[3]
Down
[4]
−1.635076486
[5]
2.05E-16
[17] array · 6 items
[0]
231192
[1]
LPAR3
[2]
Lysophosphatidic Acid Receptor 3
[3]
Down
[4]
−1.818363959
[5]
2.05E-16
[18] array · 6 items
[0]
203708
[1]
PDE4B
[2]
Phosphodiesterase 4B
[3]
Down
[4]
−1.918284538
[5]
2.24E-16
[19] array · 6 items
[0]
202411
[1]
IFI27
[2]
Interferon Alpha Inducible Protein 27
[3]
Down
[4]
−2.107723118
[5]
2.90E-16
[20] array · 6 items
[0]
203528
[1]
SEMA4D
[2]
Semaphorin 4D
[3]
Down
[4]
−0.954989951
[5]
4.82E-16
locator
section[5]/table-wrap[1]#t0001
[6] object · 16 fields
id
asset:table:pmid:34588774:2
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:7f688c2f6b55f37f0f5fb71e675679985d73d353ef3992cb71433ed8b9847c27
bytes
1873
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[6]/table-wrap[1]#t0002
version
null
note
The Top 10 of Most Significant Pathways Between Relevant Groups
structure object · 5 fields
pmcid
PMC8473850
section_index
6
section_title
The Enrichment Analysis
row_count
21
column_count
7
table object · 8 fields
label
Table 2
caption
The Top 10 of Most Significant Pathways Between Relevant Groups
rows array · 21 items
[0] array · 7 items
[0]
Group
[1]
GO: ID
[2]
Description
[3]
Gene Ratio
[4]
Pathway
[5]
q value
[6]
Adj. P
[1] array · 7 items
[0]
The COPD vs non-COPD smokers
[1]
0005924
[2]
Cell-substrate adherens junction
[3]
64/913
[4]
CC
[5]
2.37E-15
[6]
2.98E-15
[2] array · 6 items
[0]
0005925
[1]
Focal adhesion
[2]
64/913
[3]
CC
[4]
2.37E-15
[5]
2.98E-15
[3] array · 6 items
[0]
0030055
[1]
Cell-substrate junction
[2]
64/913
[3]
CC
[4]
2.61E-15
[5]
3.28E-15
[4] array · 6 items
[0]
0050839
[1]
Cell adhesion molecule binding
[2]
60/885
[3]
MF
[4]
3.28E-07
[5]
3.55E-07
[5] array · 6 items
[0]
0002446
[1]
Neutrophil mediated immunity
[2]
57/885
[3]
BP
[4]
1.04E-06
[5]
1.26E-06
[6] array · 6 items
[0]
0043312
[1]
Neutrophil degranulation
[2]
56/885
[3]
BP
[4]
1.04E-06
[5]
1.26E-06
[7] array · 6 items
[0]
0042119
[1]
Neutrophil activation
[2]
57/885
[3]
BP
[4]
1.04E-06
[5]
1.26E-06
[8] array · 6 items
[0]
0002283
[1]
Neutrophil activation involved in immune response
[2]
57/885
[3]
BP
[4]
1.04E-06
[5]
1.26E-06
[9] array · 6 items
[0]
0045296
[1]
Cadherin binding
[2]
44/885
[3]
MF
[4]
2.02E-06
[5]
2.19E-06
[10] array · 6 items
[0]
0098852
[1]
Lytic vacuole membrane
[2]
41/913
[3]
CC
[4]
8.27E-06
[5]
1.04E-05
[11] array · 7 items
[0]
The non-COPD smokers vs non-smokers
[1]
0097529
[2]
Myeloid leukocyte migration
[3]
29/447
[4]
BP
[5]
1.03E-10
[6]
1.38E-10
[12] array · 6 items
[0]
0005125
[1]
Cytokine activity
[2]
29/446
[3]
MF
[4]
2.37E-10
[5]
2.91E-10
[13] array · 6 items
[0]
0030595
[1]
Leukocyte chemotaxis
[2]
29/447
[3]
BP
[4]
2.80E-10
[5]
3.76E-10
[14] array · 6 items
[0]
0050900
[1]
Leukocyte migration
[2]
42/447
[3]
BP
[4]
2.12E-09
[5]
2.84E-09
[15] array · 6 items
[0]
0060326
[1]
Cell chemotaxis
[2]
32/447
[3]
BP
[4]
2.38E-09
[5]
3.19E-09
[16] array · 6 items
[0]
0071621
[1]
Granulocyte chemotaxis
[2]
20/447
[3]
BP
[4]
1.09E-08
[5]
1.46E-08
[17] array · 6 items
[0]
0097530
[1]
Granulocyte migration
[2]
21/447
[3]
BP
[4]
1.35E-08
[5]
1.81E-08
[18] array · 6 items
[0]
0032496
[1]
Response to lipopolysaccharide
[2]
32/447
[3]
BP
[4]
1.35E-08
[5]
1.81E-08
[19] array · 6 items
[0]
0002237
[1]
Response to molecule of bacterial origin
[2]
32/447
[3]
BP
[4]
2.93E-08
[5]
3.93E-08
[20] array · 6 items
[0]
0005126
[1]
Cytokine receptor binding
[2]
29/446
[3]
MF
[4]
8.20E-08
[5]
1.01E-07
locator
section[6]/table-wrap[1]#t0002
gaps array · 8 items
[0]
asset:data:geo:GSE130928 not downloaded
[1]
asset:data:geo:GSE130928 licence not read
[2]
asset:data:geo:GSE13896 not downloaded
[3]
asset:data:geo:GSE13896 licence not read
[4]
asset:data:geo:GSE2125 not downloaded
[5]
asset:data:geo:GSE2125 licence not read
[6]
asset:data:geo:GSE8823 not downloaded
[7]
asset:data:geo:GSE8823 licence not read
analysis object · 4 fields
state
partial
methods array · 4 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
Following the process of the batch effect (Figure 2), analysis and visualization of the differentially expressed genes (DEGs), including a PCA (principal component analysis) chart, heat-map and volcano plot were performed using “means” of the corresponding R package “limma”;
[1] object · 10 fields
id
method-2
family
principal_component_analysis
specific
pca
label
Principal component analysis
dsl_operations array · 1 item
[0]
pca_fit
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
wide_numeric_matrix
evidence object · 3 fields
score
0.8
band
high
quote
PCA
[2] object · 10 fields
id
method-3
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
protein-protein interaction
[3] object · 10 fields
id
method-4
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.8
band
high
quote
GO enrichment
targets array · 0 items
gaps array · 1 item
[0]
method.reader_differs_from_extractor
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 4 items
[0]
GSE2125
[1]
GSE8823
[2]
GSE13896
[3]
GSE130928
resolved_accessions array · 4 items
[0]
GSE2125
[1]
GSE8823
[2]
GSE13896
[3]
GSE130928
statements array · 1 item
[0]
A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1).
basis
The paper names GSE2125, GSE8823, GSE13896, GSE130928 in GEO Database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 4 items
[0]
source:pmid:34588774
[1]
data:geo:GSE130928
[2]
asset:table:pmid:34588774:1
[3]
asset:table:pmid:34588774:2
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:GSE130928
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:35:20Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
3
usage object · 3 fields
prompt_tokens
24376
completion_tokens
1675
cached_tokens
776
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
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review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
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gaps array · 1 item
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execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:34588774
type
paper
label
pmid:34588774
[1] object · 3 fields
id
source:pmid:34588774
type
manuscript
label
PMID 34588774 full text
[2] object · 3 fields
id
data:geo:GSE130928
type
dataset
label
GEO GSE130928
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:34588774
type
paper
label
pmid:34588774
[1] object · 3 fields
id
source:pmid:34588774
type
manuscript
label
PMID 34588774 full text
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id
data:geo:GSE130928
type
dataset
label
GEO GSE130928
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-34588774
type
extraction
used array · 1 item
[0]
source:pmid:34588774
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE130928
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE130928
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:34588774
parent_hash
sha256:535e4080dbb99aceb97dbede9cb590b2244f6aae288829b161074c0fb874a0c1
fork_of
null
gaps array · 13 items
[0]
asset:data:geo:GSE130928 licence not read
[1]
asset:data:geo:GSE130928 not downloaded
[2]
asset:data:geo:GSE13896 licence not read
[3]
asset:data:geo:GSE13896 not downloaded
[4]
asset:data:geo:GSE2125 licence not read
[5]
asset:data:geo:GSE2125 not downloaded
[6]
asset:data:geo:GSE8823 licence not read
[7]
asset:data:geo:GSE8823 not downloaded
[8]
execution.not_run
[9]
method.reader_differs_from_extractor
[10]
review.human_critique
[11]
review.independent_reader
[12]
review.machine_critique
assays array · 2 items
[0] object · 11 fields
role
data_generation
definition_id
microarray
definition_version
99e1195c7d6f
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support_state
partial
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assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 3 items
[0]
ll on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1). Flow Chart of Da
[1]
y used for the analysis of a gene expression microarray or sequencing data using a generalized linea
[2]
g a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were o
order_basis
paper_text_order:3002
id
assay:1
[1] object · 11 fields
role
analysis
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differential_expression
definition_version
f2132e96ae6c7a4e
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fdr_bh
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Following the process of the batch effect (Figure 2), analysis and visualization of the differentially expressed genes (DEGs), including a PCA (principal component analysis) chart, heat-map and volcano plot were performed using “means” of the corresponding R package “limma”;
order_basis
consumes_earlier_output
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34588774", "kind": "science-record", "revision": 9, "content_hash": "sha256:b0140157461cebc8554084080f86175e28a0c8101b310e941dc5aa5c8830c85f", "created_at": "2026-11-01T15:41:54Z", "updated_at": "2026-11-01T22:47:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptomics Analysis Identifies the Presence of Upregulated Ribosomal Housekeeping Genes in the Alveolar Macrophages of Patients with Smoking-Induced Chronic Obstructive Pulmonary Disease.", "doi": "10.2147/COPD.S313252", "pmid": "34588774", "authors": ["Li Han", "Jing Wang", "Xiao-Bin Ji", "Zai-Yan Wang", "Yi Wang", "Li-Yue Zhang", "Hong-Peng Li", "Ze-Ming Zhang", "Qing-Yun Li"], "journal": "International journal of chronic obstructive pulmonary disease", "year": 2021, "abstract": "BACKGROUND AND AIMS: Alveolar macrophages (AM) play a crucial role in the development of chronic obstructive pulmonary disease (COPD). The role that AM plays in the molecular pathways and clinical phenotypes associated with tobacco-related emphysema remain poorly understood. Thus, we investigated the transcriptomic profile of AM in COPD patients with a history of smoking and explored the molecular mechanisms associated with enriched pathways and hub genes.\nMETHODS: Four data sets (GSE2125, GSE8823, GSE13896 and GSE130928) were retrieved from the GEO Database. A total of 203 GEO samples (GSM) were collated for this study. About 125 of these cases were classified as smokers (91 as healthy non-COPD smokers and 34 as COPD smokers). Based on the bioinformatics obtained using the R3.6.1 program, the data were successively adopted for differential genetic expression analysis, enrichment analysis (EA), and then protein-protein interaction analysis (PPI) in a STRING database. Finally, Cytoscape 3.8 software was used to screen the hub genes. A further data analysis was performed using a set of 154 cases, classified as 64 healthy non-smokers and 91 as healthy smokers. The same procedures were used as for the COPD dataset.\nRESULTS: When comparing the data pertaining to COPD-smokers and non-COPD smokers, the top ten genes with the greatest transcriptional differences were found to be NADK, DRAP1, DEDD, NONO, KLHL12, PRKAR1A, ITGAL, GLE1, SLC8A1, SVIL. A GSEA (Gene Set Enrichment Analysis) revealed that these genes manifested an up-regulated ribosomal pathway in contrast with other genes that exhibited an extensive down-regulated pathway. The hub genes were mainly genes encoding ribosomal subunits through PPI. Furthermore, it was found that there is a narrow transcriptional difference between healthy non-smokers and non-COPD smokers and the hub genes identified here are mainly members of the chemokines, including CCL5, CCR5, CXCL9 and CXCL11.\nCONCLUSION: An elevated activity of the ribosome pathway in addition to the increased expression of ribosomal housekeeping genes (also known as hub genes) were identified with COPD-smokers, and these have the potential to cause a wide range of downstream pathogenetic effects. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE2125", "GSE8823", "GSE13896", "GSE130928"], "resolved_accessions": ["GSE2125", "GSE8823", "GSE13896", "GSE130928"], "statements": ["A total of 4 datasets: GSE2125 (n=45), GSE8823 (n=24), GSE13896 (n=88), GSE130928 (n=70), representing a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1)."], "basis": "The paper names GSE2125, GSE8823, GSE13896, GSE130928 in GEO Database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:34588774", "data:geo:GSE130928", "asset:table:pmid:34588774:1", "asset:table:pmid:34588774:2"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE130928"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:35:20Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 3, "usage": {"prompt_tokens": 24376, "completion_tokens": 1675, "cached_tokens": 776}}, "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:34588774", "type": "paper", "label": "pmid:34588774"}, {"id": "source:pmid:34588774", "type": "manuscript", "label": "PMID 34588774 full text"}, {"id": "data:geo:GSE130928", "type": "dataset", "label": "GEO GSE130928"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:34588774", "type": "paper", "label": "pmid:34588774"}, {"id": "source:pmid:34588774", "type": "manuscript", "label": "PMID 34588774 full text"}, {"id": "data:geo:GSE130928", "type": "dataset", "label": "GEO GSE130928"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-34588774", "type": "extraction", "used": ["source:pmid:34588774"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE130928", "type": "accession_resolution", "used": ["data:geo:GSE130928"], "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:34588774", "parent_hash": "sha256:535e4080dbb99aceb97dbede9cb590b2244f6aae288829b161074c0fb874a0c1", "fork_of": null, "generation": 8}, "gaps": ["asset:data:geo:GSE130928 licence not read", "asset:data:geo:GSE130928 not downloaded", "asset:data:geo:GSE13896 licence not read", "asset:data:geo:GSE13896 not downloaded", "asset:data:geo:GSE2125 licence not read", "asset:data:geo:GSE2125 not downloaded", "asset:data:geo:GSE8823 licence not read", "asset:data:geo:GSE8823 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": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ll on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were obtained (Figure 1). Flow Chart of Da", "y used for the analysis of a gene expression microarray or sequencing data using a generalized linea", "g a total of 203 cases of GSM, and all on an Affymetrix HG-U133 Plus 2.0 (GPL570 microarray), were o"], "order_basis": "paper_text_order:3002", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Following the process of the batch effect (Figure 2), analysis and visualization of the differentially expressed genes (DEGs), including a PCA (principal component analysis) chart, heat-map and volcano plot were performed using “means” of the corresponding R package “limma”;"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}