Suppression of CYP1 members of the AHR response by pathogen-associated molecular patterns
Bibliographic record
Abstract
Abstract The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that triggers a broad response, which includes the regulation of proinflammatory cytokine production by monocytes and macrophages. AHR is negatively regulated by a set of genes that it transcriptionally activates, including the AHR repressor (Ahrr) and the cytochrome P450 1 (Cyp1) family, which are critical for preventing exacerbated AHR activity. An imbalance in these regulatory mechanisms has been shown to cause severe defects in lymphoid cells. Therefore, we wanted to assess how AHR activation is regulated in monocytes and macrophages in the context of innate immune responses induced by pathogen-associated molecular patterns (PAMPs). We found that concomitant stimulation of primary human monocytes with PAMPs and the AHR agonist 6-formylindolo(3,2-b)carbazole (FICZ) led to a selective dose-dependent inhibition of Cyp1 family members induction. Two other AHR-dependent genes [Ahrr and NADPH quinone dehydrogenase 1 (Nqo1)] were not affected under these conditions, suggesting a split in the AHR regulation by PAMPs. This down-regulation of Cyp1 family members did not require de novo protein production nor signaling through p38, ERK, or PI3K-Akt-mammalian target of rapamycin (mTOR) pathways. Furthermore, such a split regulation of the AHR response was more apparent in GM-CSF-derived macrophages, a finding corroborated at the functional level by decreased CYP1 activity and decreased proinflammatory cytokine production in response to FICZ and LPS. Collectively, our findings identify a role for pattern recognition receptor (PRR) signaling in regulating the AHR response through selective down-regulation of Cyp1 expression in human monocytes and macrophages.
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 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".