Transmembrane AMPA receptor regulatory protein regulation of competitive antagonism: a problem of interpretation
Bibliographic record
Abstract
Synaptic AMPA receptors are greatly influenced by a family of transmembrane AMPA receptor regulatory proteins (TARPs) which control trafficking, channel gating and pharmacology. The prototypical TARP, stargazin (or γ2), shifts the blocking ability of several AMPAR-selective compounds including the commonly used quinoxalinedione antagonists, CNQX and NBQX. Stargazin's effect on CNQX is particularly intriguing as it not only apparently lowers the potency of block, as with NBQX, but also renders it a partial agonist. Given this, agonist behaviour by CNQX has been speculated to account for its weaker blocking effect on AMPAR-TARP complexes. Here we show that this is not the case. The apparent effect of stargazin on CNQX antagonism can be almost entirely explained by an increase in the apparent affinity for l-glutamate (l-Glu), a full agonist and neurotransmitter at AMPAR synapses. Partial agonism at best plays a minor role but not through channel gating per se but rather because CNQX elicits AMPAR desensitization. Our study reveals that CNQX is best thought of as a non-competitive antagonist at glutamatergic synapses due to the predominance of non-equilibrium conditions. Consequently, CNQX primarily reports the proportion of AMPARs available for activation but may also impose additional block by receptor desensitization.
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 | 0.023 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".