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

pmid:37830388

Regulation of ferroptosis-related genes in CD8+ NKT cells and classical monocytes may affect the immunotherapy response after combined treatment in triple negative breast cancer.

Zheming Liu · Songjiang He · Zhou Huang · Jiahui Liu · Yiping Gong · Yi Yao · Xue Zhang

Thoracic cancer · 2023 doi:10.1111/1759-7714.15128

Paper

complete

Experiment

partial

Data

partial

Analysis

complete

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:37830388
kind
science-record
content_hash
sha256:5baeab247b25c949daf833dd09c262b9f86415a8ab2882df5e7a85a9a0ddaa00
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T19:02:41Z
updated_at
2026-11-01T22:10:27Z
generator object · 2 fields
name
corpus-assay-engine
run_id
reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
Regulation of ferroptosis-related genes in CD8+ NKT cells and classical monocytes may affect the immunotherapy response after combined treatment in triple negative breast cancer.
doi
10.1111/1759-7714.15128
pmid
37830388
authors array · 7 items
[0]
Zheming Liu
[1]
Songjiang He
[2]
Zhou Huang
[3]
Jiahui Liu
[4]
Yiping Gong
[5]
Yi Yao
[6]
Xue Zhang
journal
Thoracic cancer
year
2023
abstract
BACKGROUND: Drug resistance has led to the failure of immunotherapy in triple negative breast cancer patients. Here we aimed to explore the mechanisms of drug resistance in patients in order to enhance their response to immunotherapy. METHODS: We downloaded publicly available single-cell RNA-sequencing data of peripheral blood mononuclear cells from patients after treatment to investigate the possible mechanisms of drug resistance. The publicly available TCGA transcriptomic data and somatic mutation data were used for further validation. In this study, a series of bioinformatics and machine learning methods were employed. RESULTS: We identified the vital roles of CD8+ NKT cells and classical monocytes in the immunotherapy response of triple-negative breast cancer patients. The proportion of these cell types was significantly increased in group partial response. We also found that downregulation of ferroptosis-related genes regulates the immune pathway. The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance. CONCLUSION: Overall, the composition of the tumor microenvironment affects the immunotherapy response of patients, and DUSP1 may be a potential target for overcoming drug resistance.
claims array · 3 items
[0] object · 6 fields
id
claim-method
statement
The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups.
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:37830388
locator
sections[6] "Survival analysis" paragraph 2
quote
The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups.
state
complete
[1] object · 6 fields
id
claim-data-access
statement
We collected peripheral blood mononuclear cell (PBMC) samples from 22 advanced TNBC patients (4 partial response [PR], 7 stable disease [SD], and 11 pretreatment [Pre]) that were publicly available in the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/).
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:37830388
locator
sections[3] "Data acquisition and preprocessing" paragraph 2
quote
We collected peripheral blood mononuclear cell (PBMC) samples from 22 advanced TNBC patients (4 partial response [PR], 7 stable disease [SD], and 11 pretreatment [Pre]) that were publicly available in the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/).
state
complete
[2] object · 6 fields
id
claim-target-result
statement
The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance.
kind
qualitative
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:37830388
locator
sections[0] "Abstract" paragraph 3
quote
The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance.
state
complete
gaps array · 0 items
experiment object · 8 fields
state
partial
objective
The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance.
steps array · 3 items
[0] object · 13 fields
id
read_published_estimate
order
1
name
Read the published estimate from the source
kind
other
state
complete
blocked_on
null
description
The claim, method and evidence span published with the source article.
parameters object · 0 fields
inputs array · 1 item
[0]
source:pmid:37830388
outputs array · 1 item
[0]
the published estimate and its evidence
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
id
obtain_source_data
order
2
name
Obtain the source data from the named repository
kind
data-preparation
state
blocked
blocked_on
data:accession_absent
description
The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.
parameters object · 0 fields
inputs array · 0 items
outputs array · 1 item
[0]
the source data with its repository provenance
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
id
run_analysis
order
3
name
Run the published analysis
kind
analysis
state
complete
blocked_on
null
description
Apply the paper's statistical method to the resolved series and compare the result with the published target.
parameters object · 0 fields
inputs array · 0 items
outputs array · 1 item
[0]
the replicated result and its comparison
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 1 item
[0]
step:obtain_source_data blocked on data:accession_absent
data object · 3 fields
state
partial
assets array · 1 item
[0] object · 15 fields
id
source:pmid:37830388
role
manuscript
format
xml
media_type
application/xml
uri
https://doi.org/10.1111/1759-7714.15128
sha256
sha256:4dac66080eb24d5ee61519c5145c5bc30188d45dd47d5d9f4b0eba983ca69d20
bytes
42634
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
10.1111/1759-7714.15128
version
null
note
Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.
structure object · 4 fields
pmcid
PMC10693945
source
europe_pmc_fulltext
coverage
whole_body
text_hash_scope
rendered_section_body
gaps array · 0 items
analysis object · 4 fields
state
complete
methods array · 4 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
band
verbatim
quote
The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups.
[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
Principal component analysis
[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
0.8
band
high
quote
PPI
[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
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
blocked
tier
R4
blocked_on
data:accession_absent
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R4
reachable
false
accessions array · 0 items
resolved_accessions array · 0 items
statements array · 1 item
[0]
We collected peripheral blood mononuclear cell (PBMC) samples from 22 advanced TNBC patients (4 partial response [PR], 7 stable disease [SD], and 11 pretreatment [Pre]) that were publicly available in the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/).
basis
The paper names no accession to its source data, so the data has to come from the authors.
can_run object · 3 fields
dsl_operations array · 1 item
[0]
cox_ph
assets array · 1 item
[0]
source:pmid:37830388
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:None
gaps array · 1 item
[0]
data:accession_absent
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T18:56:04Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
5
usage object · 3 fields
prompt_tokens
11897
completion_tokens
2019
cached_tokens
264
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:37830388
type
paper
label
pmid:37830388
[1] object · 3 fields
id
source:pmid:37830388
type
manuscript
label
PMID 37830388 full text
[2] object · 3 fields
id
data:geo:None
type
dataset
label
GEO None
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:37830388
type
paper
label
pmid:37830388
[1] object · 3 fields
id
source:pmid:37830388
type
manuscript
label
PMID 37830388 full text
[2] object · 3 fields
id
data:geo:None
type
dataset
label
GEO None
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-37830388
type
extraction
used array · 1 item
[0]
source:pmid:37830388
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-None
type
accession_resolution
used array · 1 item
[0]
data:geo:None
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:37830388
parent_hash
sha256:52a9b50a668a875f652da7186a1642486cdc49c57cd8fc871ce17a7ad96cb0c0
fork_of
null
gaps array · 5 items
[0]
execution.not_run
[1]
review.human_critique
[2]
review.independent_reader
[3]
review.machine_critique
[4]
step:obtain_source_data blocked on data:accession_absent
assays array · 2 items
[0] object · 11 fields
role
data_generation
definition_id
apoptosis_assay
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 2 items
[0]
F1 and F2 were particularly enriched in the apoptosis process. F1 mainly consisted of T cells and
[1]
iological processes such as immune response, apoptosis, and inflammation response in the C2, indica
order_basis
paper_text_order:7354
id
assay:1
[1] object · 11 fields
role
analysis
definition_id
survival_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
[0]
cox_ph
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups.
order_basis
consumes_earlier_output
id
assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37830388", "kind": "science-record", "revision": 3, "content_hash": "sha256:5baeab247b25c949daf833dd09c262b9f86415a8ab2882df5e7a85a9a0ddaa00", "created_at": "2026-11-01T19:02:41Z", "updated_at": "2026-11-01T22:10:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Regulation of ferroptosis-related genes in CD8+ NKT cells and classical monocytes may affect the immunotherapy response after combined treatment in triple negative breast cancer.", "doi": "10.1111/1759-7714.15128", "pmid": "37830388", "authors": ["Zheming Liu", "Songjiang He", "Zhou Huang", "Jiahui Liu", "Yiping Gong", "Yi Yao", "Xue Zhang"], "journal": "Thoracic cancer", "year": 2023, "abstract": "BACKGROUND: Drug resistance has led to the failure of immunotherapy in triple negative breast cancer patients. Here we aimed to explore the mechanisms of drug resistance in patients in order to enhance their response to immunotherapy.\nMETHODS: We downloaded publicly available single-cell RNA-sequencing data of peripheral blood mononuclear cells from patients after treatment to investigate the possible mechanisms of drug resistance. The publicly available TCGA transcriptomic data and somatic mutation data were used for further validation. In this study, a series of bioinformatics and machine learning methods were employed.\nRESULTS: We identified the vital roles of CD8+ NKT cells and classical monocytes in the immunotherapy response of triple-negative breast cancer patients. The proportion of these cell types was significantly increased in group partial response. We also found that downregulation of ferroptosis-related genes regulates the immune pathway. The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance.\nCONCLUSION: Overall, the composition of the tumor microenvironment affects the immunotherapy response of patients, and DUSP1 may be a potential target for overcoming drug resistance.", "claims": [{"id": "claim-method", "statement": "The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37830388", "locator": "sections[6] \"Survival analysis\" paragraph 2", "quote": "The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We collected peripheral blood mononuclear cell (PBMC) samples from 22 advanced TNBC patients (4 partial response [PR], 7 stable disease [SD], and 11 pretreatment [Pre]) that were publicly available in the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37830388", "locator": "sections[3] \"Data acquisition and preprocessing\" paragraph 2", "quote": "We collected peripheral blood mononuclear cell (PBMC) samples from 22 advanced TNBC patients (4 partial response [PR], 7 stable disease [SD], and 11 pretreatment [Pre]) that were publicly available in the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37830388", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance.", "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:37830388"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37830388", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1111/1759-7714.15128", "sha256": "sha256:4dac66080eb24d5ee61519c5145c5bc30188d45dd47d5d9f4b0eba983ca69d20", "bytes": 42634, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1111/1759-7714.15128", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10693945", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups."}}, {"id": "method-2", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "Principal component analysis"}}, {"id": "method-3", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "PPI"}}, {"id": "method-4", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "pathway enrichment"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["We collected peripheral blood mononuclear cell (PBMC) samples from 22 advanced TNBC patients (4 partial response [PR], 7 stable disease [SD], and 11 pretreatment [Pre]) that were publicly available in the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/)."], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:37830388"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:56:04Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 11897, "completion_tokens": 2019, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:37830388", "type": "paper", "label": "pmid:37830388"}, {"id": "source:pmid:37830388", "type": "manuscript", "label": "PMID 37830388 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37830388", "type": "paper", "label": "pmid:37830388"}, {"id": "source:pmid:37830388", "type": "manuscript", "label": "PMID 37830388 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37830388", "type": "extraction", "used": ["source:pmid:37830388"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "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:37830388", "parent_hash": "sha256:52a9b50a668a875f652da7186a1642486cdc49c57cd8fc871ce17a7ad96cb0c0", "fork_of": null, "generation": 2}, "gaps": ["execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"], "assays": [{"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["F1 and F2 were particularly enriched in the apoptosis process. F1 mainly consisted of T cells and", "iological processes such as immune response, apoptosis, and inflammation response in the C2, indica"], "order_basis": "paper_text_order:7354", "id": "assay:1"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The R package Survival was used to estimate the survival differences between the two groups. The Kaplan–Meier method was used to plot survival curves, and the log‐rank test was used to assess the statistical differences in prognoses between different groups."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}