Functional Modifications of Acid-Sensing Ion Channels by Ligand-Gated Chloride Channels
Bibliographic record
Abstract
Together, acid-sensing ion channels (ASICs) and epithelial sodium channels (ENaC) constitute the majority of voltage-independent sodium channels in mammals. ENaC is regulated by a chloride channel, the cystic fibrosis transmembrane conductance regulator (CFTR). Here we show that ASICs were reversibly inhibited by activation of GABA(A) receptors in murine hippocampal neurons. This inhibition of ASICs required opening of the chloride channels but occurred with both outward and inward GABA(A) receptor-mediated currents. Moreover, activation of the GABA(A) receptors modified the pharmacological features and kinetic properties of the ASIC currents, including the time course of activation, desensitization and deactivation. Modification of ASICs by open GABA(A) receptors was also observed in both nucleated patches and outside-out patches excised from hippocampal neurons. Interestingly, ASICs and GABA(A) receptors interacted to regulate synaptic plasticity in CA1 hippocampal slices. The activation of glycine receptors, which are similar to GABA(A) receptors, also modified ASICs in spinal neurons. We conclude that GABA(A) receptors and glycine receptors modify ASICs in neurons through mechanisms that require the opening of chloride channels.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".