δ-Opioid Receptor and Somatostatin Receptor-4 Heterodimerization: Possible Implications in Modulation of Pain Associated Signaling
Bibliographic record
Abstract
Pain relief is the principal action of opioids. Somatostatin (SST), a growth hormone inhibitory peptide is also known to alleviate pain even in cases when opioids fail. Recent studies have shown that mice are prone to sustained pain and devoid of analgesic effect in the absence of somatostatin receptor 4 (SSTR4). In the present study, using brain slices, cultured neurons and HEK-293 cells, we showed that SSTR4 and δ-Opioid receptor (δOR) exist in a heteromeric complex and function in synergistic manner. SSTR4 and δOR co-expressed in cortical/striatal brain regions and spinal cord. Using cultured neuronal cells, we describe the heterogeneous complex formation of SSTR4 and δOR at neuronal cell body and processes. Cotransfected cells display inhibition of cAMP/PKA and co-activation of SSTR4 and δOR oppose receptor trafficking induced by individual receptor activation. Furthermore, downstream signaling pathways either associated with withdrawal or pain relief are modulated synergistically with a predominant role of SSTR4. Inhibition of cAMP/PKA and activation of ERK1/2 are the possible cellular adaptations to prevent withdrawal induced by chronic morphine use. Our results reveal direct intra-membrane interaction between SSTR4 and δOR and provide insights for the molecular mechanism for the anti-nociceptive property of SST in combination with opioids as a potential therapeutic approach to avoid undesirable withdrawal symptoms.
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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".