Apoptotic cell driven ROS burst drives AhR dependent immunologic tolerance and suppression of lupus
Bibliographic record
Abstract
Abstract Tissue-resident macrophages (MΦ) are crucial in driving tolerance and preventing systemic autoimmunity. We have previously shown that exposure to apoptotic cells triggers a regulatory circuit dependent on IL-10 production in resident MΦ. However, key molecular mechanisms driving the regulatory response to apoptosis are not clear. RNA transcriptome analysis of MΦs after exposure to apoptotic cells identified strong transcript association with the aryl hydrocarbon receptor (AhR) signaling pathway, an association that was confirmed by phenotypic and biochemical analysis. When AhR activity was blocked, apoptotic cells induced an alteration in the mRNA signature enhancing proinflammatory effector expression. Functional analysis revealed that the DNA from apoptotic cells activated AhR in a reactive oxygen species (ROS) dependent mechanism and AhR is required for IL-10 production. Consequently, inhibition or deletion of AhR signals fundamentally altered immune responses to apoptotic cells in vivo resulting in proinflammatory cytokine production, increased effector T cell responses, and failure of long-term tolerance to apoptotic cell-associated antigens. Surprisingly, mice lacking AhR developed progressive systemic autoimmunity characterized by excessive MΦ and lymphocyte activation and renal pathology. Similarly, SLE-prone mice treated with AhR antagonist exhibited poor survival, while agonist treatment ablated disease pathology. Finally, an AhR transcriptional signature was significantly associated with active SLE flare in SLE patients. Thus, the data demonstrates the AhR pathway is a key molecular circuit responsible for apoptotic cell driven tolerance and suppression of inflammatory autoimmunity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".