Antibody-induced pain-like behavior and bone erosion: links to subclinical inflammation, osteoclast activity, and acid-sensing ion channel 3–dependent sensitization
Bibliographic record
Abstract
ABSTRACT: Several bone conditions, eg, bone cancer, osteoporosis, and rheumatoid arthritis (RA), are associated with a risk of developing persistent pain. Increased osteoclast activity is often the hallmark of these bony pathologies and not only leads to bone remodeling but is also a source of pronociceptive factors that sensitize the bone-innervating nociceptors. Although historically bone loss in RA has been believed to be a consequence of inflammation, both bone erosion and pain can occur years before the symptom onset. Here, we have addressed the disconnection between inflammation, pain, and bone erosion by using a combination of 2 monoclonal antibodies isolated from B cells of patients with RA. We have found that mice injected with B02/B09 monoclonal antibodies (mAbs) developed a long-lasting mechanical hypersensitivity that was accompanied by bone erosion in the absence of joint edema or synovitis. Intriguingly, we have noted a lack of analgesic effect of naproxen and a moderate elevation of few inflammatory factors in the ankle joints suggesting that B02/B09-induced pain-like behavior does not depend on inflammatory processes. By contrast, we found that inhibiting osteoclast activity and acid-sensing ion channel 3 signaling prevented the development of B02/B09-mediated mechanical hypersensitivity. Moreover, we have identified secretory phospholipase A2 and lysophosphatidylcholine 16:0 as critical components of B02/B09-induced pain-like behavior and shown that treatment with a secretory phospholipase A2 inhibitor reversed B02/B09-induced mechanical hypersensitivity and bone erosion. Taken together, our study suggests a potential link between bone erosion and pain in a state of subclinical inflammation and offers a step forward in understanding the mechanisms of bone pain in diseases such as RA.
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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 | 0.001 | 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".