Comparison of nociceptor properties using electrophysiology in preclinical models of osteoarthritis
Bibliographic record
Abstract
Osteoarthritis (OA) pain originates in the joint by sensitization of articular nociceptors. While behavioural assessments provide valuable information regarding pain symptoms, the techniques are subjective and open to interpretation by the experimenter. This study used in vivo electrophysiological approaches to measure objectively joint nociceptor properties in three rodent models of OA. Single unit extracellular recordings of joint mechanosensitive afferents were carried out in male and female rats following either (1) transection of the medial meniscus (MMT: post-traumatic OA), (2) intra-articular injection of sodium monoiodoacetate (MIA: chemically-induced OA), or (3) intra-articular injection of lysophosphatidic acid (LPA: neuropathic OA). In naïve male control rats, the mechanical threshold of joint mechanonociceptors (23.5 ± 1.8 mNm) was significantly reduced with MMT (9.4 ± 1.1 mNm) and MIA (15.1 ± 1.6 mNm). In females, the mechanical threshold of naïve rats (23.2 ± 3.1 mNm) was reduced following induction of MMT (8.3 ± 1.0 mNm) and LPA (10.6 ± 2.2 mNm). Afferent firing frequency increased in male MMT (∼275 %), LPA (∼175 %), MIA (225 %), and female MMT (∼146 %), LPA (∼200 %), and MIA (∼192 %). Mechanical threshold and evoked firing were negatively correlated in all models for both sexes except LPA rats (male + female) and female MMT. These data indicate that MMT, MIA, and LPA induce peripheral sensitization of joint afferents thereby validating their use in OA pain studies.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".