Neuronal interleukin-1 receptors mediate pain in chronic inflammatory diseases
Bibliographic record
Abstract
Chronic pain is a major comorbidity of chronic inflammatory diseases. Here, we report that the cytokine IL-1β, which is abundantly produced during multiple sclerosis (MS), arthritis (RA), and osteoarthritis (OA) both in humans and in animal models, drives pain associated with these diseases. We found that the type 1 IL-1 receptor (IL-1R1) is highly expressed in the mouse and human by a subpopulation of TRPV1+ dorsal root ganglion neurons specialized in detecting painful stimuli, termed nociceptors. Strikingly, deletion of the Il1r1 gene specifically in TRPV1+ nociceptors prevented the development of mechanical allodynia without affecting clinical signs and disease progression in mice with experimental autoimmune encephalomyelitis and K/BxN serum transfer-induced RA. Conditional restoration of IL-1R1 expression in nociceptors of IL-1R1-knockout mice induced pain behavior but did not affect joint damage in monosodium iodoacetate-induced OA. Collectively, these data reveal that neuronal IL-1R1 signaling mediates pain, uncovering the potential benefit of anti-IL-1 therapies for pain management in patients with chronic inflammatory diseases.
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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) | 0.002 | 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".