Redefining the classification of AMPA‐selective ionotropic glutamate receptors
Bibliographic record
Abstract
AMPA-type ionotropic glutamate receptors (iGluRs) represent the major excitatory neurotransmitter receptor in the developing and adult vertebrate CNS. They are crucial for the normal hardwiring of glutamatergic circuits but also fine tune synaptic strength by cycling into and out of synapses during periods of sustained patterned activity or altered homeostasis. AMPARs are grouped into two functionally distinct tetrameric assemblies based on the inclusion or exclusion of the GluA2 receptor subunit. GluA2-containing receptors are thought to be the most abundant AMPAR in the CNS, typified by their small unitary events, Ca(2+) impermeability and insensitivity to polyamine block. In contrast, GluA2-lacking AMPARs exhibit large unitary conductance, marked divalent permeability and nano- to micromolar polyamine affinity. Here, I review evidence for the existence of a third class of AMPAR which, though similarly Ca(2+) permeable, is characterized by its near-insensitivity to internal and external channel block by polyamines. This novel class of AMPAR is most notably found at multivesicular release synapses found in the avian auditory brainstem and mammalian retina. Curiously, these synapses lack NMDA-type iGluRs, which are conventionally associated with controlling AMPAR insertion. The lack of NMDARs suggests that a different set of rules may govern AMPAR cycling at these synapses. AMPARs with similar functional profiles are also found on some glial cells suggesting they may have a more widespread distribution in the mammalian CNS. I conclude by noting that modest changes to the ion-permeation pathway might be sufficient to retain divalent permeability whilst eliminating polyamine sensitivity. Consequently, this emerging AMPAR subclass need not be assembled from novel subunits, yet to be cloned, but could simply occur by varying the stoichiometry of existing proteins.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".