Regulation of<scp>μ</scp>and<scp>δ</scp>opioid receptor functions: involvement of cyclin‐dependent kinase 5
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Phosphorylation of δ opioid receptors (DOP receptors) by cyclin-dependent kinase 5 (CDK5) was shown to regulate the trafficking of this receptor. Therefore, we aimed to determine the role of CDK5 in regulating DOP receptors in rats treated with morphine or with complete Freund's adjuvant (CFA). As μ (MOP) and DOP receptors are known to be co-regulated, we also sought to determine if CDK5-mediated regulation of DOP receptors also affects MOP receptor functions. EXPERIMENTAL APPROACH: The role of CDK5 in regulating opioid receptors in CFA- and morphine-treated rats was studied using roscovitine as a CDK inhibitor and a cell-penetrant peptide mimicking the second intracellular loop of DOP receptors (C11-DOPri2). Opioid receptor functions were assessed in vivo in a series of behavioural experiments and correlated by measuring ERK1/2 activity in dorsal root ganglia homogenates. KEY RESULTS: Chronic roscovitine treatment reduced the antinociceptive and antihyperalgesic effects of deltorphin II (Dlt II) in morphine- and CFA-treated rats respectively. Repeated administrations of C11-DOPri2 also robustly decreased Dlt II-induced analgesia. Interestingly, DAMGO-induced analgesia was significantly increased by roscovitine and C11-DOPri2. Concomitantly, in roscovitine-treated rats the Dlt II-induced ERK1/2 activation was decreased, whereas the DAMGO-induced ERK1/2 activation was increased. An acute roscovitine treatment had no effect on Dlt II- or DAMGO-induced analgesia. CONCLUSIONS AND IMPLICATIONS: Together, our results demonstrate that CDK5 is a key player in the regulation of DOP receptors in morphine- and CFA-treated rats and that the regulation of DOP receptors by CDK5 is sufficient to modulate MOP receptor functions through an indirect process.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".