Na+/Cl- Dipole Couples Agonist Binding to Kainate Receptor Activation
Bibliographic record
Abstract
Kainate-selective ionotropic glutamate receptors (GluRs) require external Na+ and Cl- as well as the neurotransmitter L-glutamate for activation. Although, external anions and cations apparently coactivate kainate receptors (KARs) in an identical manner, it has yet to be established how ions of opposite charge achieve this. An additional complication is that KARs are subject to other forms of cation modulation via extracellular acidification (i.e., protons) and divalent ions. Consequently, other cation species may compete with Na+ to regulate the time KARs remain in the open state. Here we designed experiments to unravel how external ions regulate GluR6 KARs. We show that GluR6 kinetics are unaffected by alterations in physiological pH but that divalent and alkali metal ions compete to determine the time course of KAR channel activity. Additionally, Na+ and Cl- ions coactivate GluR6 receptors by establishing a dipole, accounting for their common effect on KARs. Using charged amino acids as tethered ions, we further demonstrate that the docking order is fixed with cations binding first, followed by anions. Together, our findings identify the dipole as a novel gating feature that couples neurotransmitter binding to KAR activation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".