Consistent sex-dependent effects of PKMζ gene ablation and pharmacological inhibition on the maintenance of referred pain
Bibliographic record
Abstract
BACKGROUND: Persistently active PKMζ has been implicated in maintaining spinal nociceptive sensitization that underlies pain hypersensitivity. However, evidence for PKMζ in the maintenance of pain hypersensitivity comes exclusively from short-term studies in males using pharmacological agents of questionable selectivity. The present study examines the contribution of PKMζ to long-lasting allodynia associated with neuropathic, inflammatory, or referred visceral and muscle pain in males and females using pharmacological inhibition or genetic ablation. RESULTS: Pharmacological inhibition or genetic ablation of PKMζ reduced mild formalin pain and slowly developing contralateral allodynia in nerve-injured rats, but not moderate formalin pain or ipsilateral allodynia in models of neuropathic and inflammatory pain. Pharmacological inhibition or genetic ablation of PKMζ also effectively reduced referred visceral and muscle pain in male, but not in female mice and rats. CONCLUSION: We show pharmacological inhibition and genetic ablation of PKMζ consistently attenuate long-lasting pain hypersensitivity. However, differential effects in models of referred versus inflammatory and neuropathic pain, and in males versus females, highlight the roles of afferent input-dependent masking and sex differences in the maintenance of pain hypersensitivity.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".