G‐protein‐coupled receptor oligomers: two or more for what? Lessons from mGlu and GABA<sub>B</sub> receptors
Bibliographic record
Abstract
G-protein-coupled receptors (GPCRs) are key players in the precise tuning of intercellullar communication. In the brain, both major neurotransmitters, glutamate and GABA, act on specific GPCRs [the metabotropic glutamate (mGlu) and GABA(B) receptors] to modulate synaptic transmission. These receptors are encoded by the largest gene family, and have been found to associate into both homo- and hetero-oligomers, which increases the complexity of this cell communication system. Here we show that dimerization is required for mGlu and GABA(B) receptors to function, since the activation process requires a relative movement between the subunits to occur. We will also show that, in contrast to the mGlu receptors, which form strict dimers, the GABA(B) receptors assemble into larger complexes, both in transfected cells and in the brain, resulting in a decreased G-protein coupling efficacy. We propose that GABA(B) receptor oligomerization offers a way to increase the possibility of modulating receptor signalling and activity, allowing the same receptor protein to have specific properties in neurons at different locations.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".