Mechanisms underlying enhanced P2X receptor-mediated responses in the neuropathic pain state
Bibliographic record
Abstract
P2X3 and P2X2/3 receptors in dorsal root ganglia (DRG) appear to participate in producing nociceptive responses after nerve injury. However, the mechanisms underlying the receptor-mediated nociception in the neuropathic state remain unclear. Using spared nerve injury (SNI) rats, we found that allodynic and nocifensive (flinch) behavioral responses developed after injury can be reversed by P2X receptor antagonists, indicating an involvement of P2X receptors. Immunocytochemical studies revealed that P2X3 receptors are expressed in small and medium but rarely in large DRG neurons of both normal and SNI rats. Thus, contrary to the conventional view that only large A beta cells mediate allodynia, small and medium cells are intimately involved in P2X3 receptor-mediated allodynia. Measuring ATP levels in the subcutaneous space of the rat paw, we showed that ATP release does not change after SNI. On the other hand, the P2X receptor agonist, alpha beta-methylene ATP produces 3.5-fold larger flinch responses at a 8.0-fold lower dose. Thus, sensitization of P2X3 receptors rather than a change in ATP release is responsible for the neuropathic pain behaviors. We further demonstrated that sensitization of P2X3 receptors arises from an increase in receptor function. ATP-induced P2X3 receptor-mediated currents in DRG neurons is 2.5-fold larger after SNI. The expression of P2X3 receptors on the cell membrane is significantly enhanced while the total expression of P2X3 receptors remained unchanged. Thus, the enhancement of trafficking of P2X3 receptors is likely an important mechanism contributing to the increase in receptor function after nerve injury.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".