Morphine-Induced Changes in δ Opioid Receptor Trafficking Are Linked to Somatosensory Processing in the Rat Spinal Cord
Bibliographic record
Abstract
An in vivo fluorescent deltorphin (Fluo-DLT) internalization assay was used to assess the distribution and regulation of pharmacologically available delta opioid receptors (deltaORs) in the rat lumbar (L4-5) spinal cord. Under basal conditions, intrathecal injection of Fluo-DLT resulted in the labeling of numerous deltaOR-internalizing neurons throughout dorsal and ventral horns. The distribution and number of Fluo-DLT-labeled perikaryal profiles were consistent with that of deltaOR-expressing neurons, as revealed by in situ hybridization and immunohistochemistry, suggesting that a large proportion of these cells was responsive to intrathecally administered deltaOR agonists. Pretreatment of rats with morphine for 48 hr resulted in a selective increase in Fluo-DLT-labeled perikaryal profiles within the dorsal horn. These changes were not accompanied by corresponding augmentations in either deltaOR mRNA or (125)I-deltorphin-II binding levels, suggesting that they were attributable to higher densities of cell surface deltaOR available for internalization rather than to enhanced production of the receptor. Unilateral dorsal rhizotomy also resulted in increased Fluo-DLT internalization in the ipsilateral dorsal horn when compared with the side contralateral to the deafferentation or to non-deafferented controls, suggesting that deltaOR trafficking in dorsal horn neurons may be regulated by afferent inputs. Furthermore, morphine treatment no longer increased Fluo-DLT internalization on either side of the spinal cord after unilateral dorsal rhizotomy, indicating that microOR-induced changes in the cell surface availability of deltaOR depend on the integrity of primary afferent inputs. Together, these results suggest that regulation of deltaOR responsiveness through microOR activation in this region is linked to somatosensory information processing.
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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 | 0.001 |
| 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".