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Record W4413596049 · doi:10.1186/s10020-025-01324-0

CpG-oligodeoxynucleotides challenged macrophages ameliorate acetaminophen induced liver injury by activating TLR9/IRG1/itaconate metabolic pathway

2025· article· en· W4413596049 on OpenAlexaff
Yibai Qu, Zehui Jiang, Zhixia Chen, Si-Dan Luo, Bingyao Xie, Xubo Wu, Gang Yuan, Kai Wu, Li Chen, Tian Tian, Shan Li, Haihua Luo, Quan Li, Yuan Ding, Y. Zhang, Yanxia Gao, Jun Zhou, Zhengzheng Yan, Yong Jiang

Bibliographic record

VenueMolecular Medicine · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsCpG OligodeoxynucleotideTLR9CytotoxicityPharmacologyAcetaminophenIn vivoLiver injuryImmune systemApoptosisIn vitroBiologyCancer researchImmunologyBiochemistryGene expressionGeneDNA methylation

Abstract

fetched live from OpenAlex

BACKGROUND: Acetaminophen, or N-acetyl-para-aminophenol (APAP), causes severe liver damage and acute liver failure when overdosed. Oligodeoxynucleotides containing CpG motifs (CpG ODN) can regulate the function of macrophages, which play an important role in drug-induced liver injury. It is unclear whether CpG ODN-treated macrophages play an immune regulation role in APAP-induced liver injury. In the present study, we aim to explore the role of CpG ODN-activated macrophages in APAP-induced liver injury and the underlying mechanism in protecting against the cytotoxicity of APAP. METHODS: In vivo, C57BL/6 mice were treated with APAP (300 mg/Kg) or/and CpG ODN (ODN 1826, 1.65 mg/Kg) by intraperitoneal injection, then survival rate, histopathological evaluation, and inflammatory factors were observed to ascertain the protective effect of CpG ODN. Then, CpG ODN-treated macrophages were reinfused into the animal model to determine the effector cells. In vitro, RNA sequencing and untargeted metabolomics detection were performed to illustrate the underlying mechanism. Last, Acod1 siRNA interference was used to clarify the role of IRG1 in resistance to APAP cytotoxicity by ROS and apoptosis indicator detections. RESULTS: We found that CpG ODN showed a protective effect against APAP cytotoxicity by stimulating macrophages rather than hepatic parenchymal cells. In particular, reinfusion of CpG ODN-treated macrophages to mice can alleviate APAP-induced liver injury. Transcriptome and metabolome analysis revealed that the expression of aconitate decarboxylase 1 (Acod1; also known as immune responsive gene 1, IRG1) and the metabolite itaconate generated by IRG1 catalysis increased after CpG ODN stimulation. In addition, we found that the mechanism of this protective effect is ascribed to the increased expression of Acod1 and the antioxidative function of itaconate by the activation of the TLR9/NF-κB signaling pathway. CONCLUSION: CpG ODN alleviated liver injury induced by APAP through the activation of the TLR9/NF-κB signaling pathway in macrophages, upregulating the expression of IRG1 protein, promoting the production of endogenous metabolite itaconate, and inhibiting macrophage apoptosis which was regulated by upregulating the expression of Nrf2 to inhibit ROS production. This study sheds new light on CpG ODN as a therapeutic strategy in resistance to APAP-induced liver injury.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.400
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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