Sensory Neuron-Specific Deletion of Tropomyosin Receptor Kinase A (TrkA) in Mice Abolishes Osteoarthritis (OA) Pain via NGF/TrkA Intervention of Peripheral Sensitization
Bibliographic record
Abstract
Tropomyosin receptor kinase A (TrkA/NTRK1) is a high-affinity receptor for nerve growth factor (NGF), a potent pain mediator. NGF/TrkA signaling elevates synovial sensory neuronal distributions in the joints and causes osteoarthritis (OA) pain. We investigated the mechanisms of pain transmission as to whether peripheral sensory neurons are linked to the cellular plasticity in the dorsal root ganglia (DRG) and are critical for OA hyperalgesia. Sensory neuron-specific deletion of TrkA was achieved by tamoxifen injection in 4-week-old TrkAfl/fl;NaV1.8CreERT2 (Ntrk1 fl/fl;Scn10aCreERT2) mice. OA was induced by partial medial meniscectomy (PMM) in 12-week-old mice, and OA-pain-related behavior was analyzed for 12 weeks followed by comprehensive histopathological examinations. OA-associated joint pain was markedly improved without cartilage protection in sensory-neuron-specific conditional TrkA knock-out (cKO) mice. Alleviated hyperalgesia was associated with suppression of the NGF/TrkA pathway and reduced angiogenesis in fibroblast-like synovial cells. Elevated pain transmitters in the DRG of OA-induced mice were significantly diminished in sensory-neuron-specific TrkA cKO and global TrkA cKO mice. Spinal glial activity and brain-derived neurotropic factor (BDNF) were significantly increased in OA-induced mice but were substantially eliminated by sensory-neuron-specific deletion. Our results suggest that augmentation of NGF/TrkA signaling in the joint synovium and the peripheral sensory neurons facilitate pro-nociception and centralized pain sensitization.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".