Delta opioid receptor‐mediated analgesia is not altered in preprotachykinin A knockout mice
Bibliographic record
Abstract
We have shown that delta opioid receptor (DOPR)-mediated analgesia was enhanced in the complete Freund's adjuvant (CFA) model of inflammation. This effect is thought to originate from translocation of DOPR in the plasma membrane of dorsal root ganglia and spinal cord neurons. Among the putative mechanisms involved in the regulation of DOPR trafficking, an interaction with substance P (SP) in large dense-core vesicles has been described as an essential event for the externalization of DOPR. As we have previously observed that membrane DOPRs were upregulated in small- and medium-sized neurons under inflammatory pain conditions (whereas SP is mainly expressed by small dorsal root ganglia neurons), we raised the hypothesis that an SP-independent mechanism mediates DOPR trafficking and functional emergence in the CFA model. Therefore, we investigated the role of SP in DOPR-mediated analgesia by using preprotachykinin A (precursor of SP) knockout mice (PPTA(-/-) ) in the CFA model of inflammation. First, we confirmed that PPTA(-/-) mice are not expressing SP and have a similar level of CFA-induced inflammation as wildtype mice. Then, using the thermal plantar test, we found that an intrathecal injection of deltorphin II induced DOPR-mediated antihyperalgesia, which was not modified by the absence of SP (similar efficacy and potency in wildtype and PPTA(-/-) mice). We also observed similar analgesia of intrathecal deltorphin II for PPTA(-/-) and wildtype mice in the hot-water immersion tail-flick test. Consequently, our results suggest that SP is not essential for membrane insertion and for the functional emergence of DOPR.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".