Joint Damage and Neuropathic Pain in Rats Treated With Lysophosphatidic Acid
Bibliographic record
Abstract
Joint pain is a complex phenomenon that involves multiple endogenous mediators and pathophysiological events. In addition to nociceptive and inflammatory pain, some patients report neuropathic-like pain symptoms. Examination of arthritic joints from humans and preclinical animal models have revealed axonal damage which is likely the source of the neuropathic pain. The mediators responsible for joint peripheral neuropathy are obscure, but lysophosphatidic acid (LPA) has emerged as a leading candidate target. In the present study, male and female Wistar rats received an intra-articular injection of LPA into the right knee and allowed to recover for 28 days. Joint pain was measured by von Frey hair algesiometry, while joint pathology was determined by scoring of histological sections. Both male and female rats showed comparable degenerative changes to the LPA-treated knee including chondrocyte death, focal bone erosion, and synovitis. Mechanical withdrawal thresholds decreased by 20-30% indicative of secondary allodynia in the affected limb; however, there was no significant difference in pain sensitivity between the sexes. Treatment of LPA animals with the neuropathic pain drug amitriptyline reduced joint pain for over 2 hours with no sex differences being observed. In summary, intra-articular injection of LPA causes joint degeneration and neuropathic pain thereby mimicking some of the characteristics of neuropathic osteoarthritis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".