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Record W4406728112 · doi:10.1126/sciadv.adq7307

Mitochondrial respiratory complex III sustains IL-10 production in activated macrophages and promotes tumor-mediated immune evasion

2025· article· en· W4406728112 on OpenAlexaff
Alessia Zotta, Juliana E. Toller-Kawahisa, Eva M. Pålsson‐McDermott, Shane M. O’Carroll, Órlaith C. Henry, Emily A. Day, Anne F. McGettrick, Ross W. Ward, Dylan G. Ryan, Mark A. Watson, Martin D. Brand, Marah C. Runtsch, Kathrin Maitz, Anna Lueger, Julia Kargl, Jan Lj. Miljković, Ed C. Lavelle, Luke O'neill

Bibliographic record

VenueScience Advances · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsWestern University
FundersBuck Institute for Research on Aging
KeywordsBiologyImmune systemCell biologyInflammationAP-1 transcription factorCytokineCancer researchTranscription factorImmunologyBiochemistry

Abstract

fetched live from OpenAlex

The cytokine interleukin-10 (IL-10) limits the immune response and promotes resolution of acute inflammation. Because of its immunosuppressive effects, IL-10 up-regulation is a common feature of tumor progression and metastasis. Recently, IL-10 regulation has been shown to depend on mitochondria and redox-sensitive signals. We have found that Suppressor of site III Qo Electron Leak 1.2 (S3QEL 1.2), a specific inhibitor of reactive oxygen species (ROS) production from mitochondrial complex III, and myxothiazol, a complex III inhibitor, decrease IL-10 in lipopolysaccharide (LPS)–activated macrophages. IL-10 down-regulation is likely to be mediated by suppression of c-Fos, which is a subunit of activator protein 1 (AP1), a transcription factor required for IL-10 gene expression. S3QEL 1.2 impairs IL-10 production in vivo after LPS challenge and promotes the survival of mice bearing B16F10 melanoma by lowering tumor growth. Our data identify a link between complex III–dependent ROS generation and IL-10 production in macrophages, the targeting of which could have potential in boosting antitumor immunity.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.038
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.285
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations28
Published2025
Admission routes1
Has abstractyes

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