Trafficking of Preassembled Opioid μ−δ Heterooligomer−Gz Signaling Complexes to the Plasma Membrane: Coregulation by Agonists
Bibliographic record
Abstract
The cellular site of formation, Galpha-coupling preference, and agonist regulation of mu-delta opioid receptor (OR) heterooligomers were studied. Bioluminescence resonance energy transfer (BRET) showed that mu-deltaOR heterooligomers, composed of preformed mu and delta homooligomers, interacted constitutively in the endoplasmic reticulum (ER) with Galpha-proteins forming heteromeric signaling complexes before being targeted to the plasma membrane. Compared to muOR homooligomers, the mu-delta heterooligomers showed higher affinity and efficiency of interaction for Gz over Gi, indicating a switch in G-protein preference. Treatment with DAMGO or deltorphin II led to coregulated internalization of both receptors, whereas DPDPE and DSLET had no effect on mu-delta internalization. Staggered expression resulted in non-interacting mu and delta receptors, even though both receptors were colocalized at the cell surface. Agonists failed to induce BRET between staggered receptors, and resulted in internalization solely of the receptor targeted by agonist. Thus, mu-deltaOR heterooligomers form and preferentially associate with Gz to generate a signaling complex in the ER, and have a distinct agonist-internalization profile compared to either mu or delta homooligomers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".