<scp>d</scp>-Serine inhibits AMPA receptor-mediated current in rat hippocampal neurons
Bibliographic record
Abstract
D-Serine, a recently identified gliotransmitter, serves as an endogenous coagonist binding to the glycine site of N-methyl-D-aspartate (NMDA) receptors. However, it is not clear whether this native ligand is able to bind to and modulate alpha-amino-3-hydroxyl-5-methyl-4-isoxazolepropionate (AMPA) receptors. In the present study, we showed that D-serine was able to concentration-dependently inhibit kainate-induced AMPA receptor-mediated current in acutely isolated hippocampal neurons. The blocking action of D-serine on AMPA receptors was characterized by a shift in concentration-response curve of kainate-induced current to the right with no change in the maximal response and independent of holding potential in the range of -80 to +60 mV. This is consistent with a model that D-serine is a competitive antagonist on AMPA receptors. In contrast, L-serine did not exert such an inhibitory action. Consistent with this observation, we found that several D-isoforms, but not L-isoforms, of endogenous and exogenous amino acids were able to block AMPA receptors. These results indicate that there is a low affinity and stereo-selective site at the agonist binding pocket of AMPA receptors for these D-amino acids. More importantly, vesicular-released endogenous D-serine from astrocytes could potentially modulate AMPA receptors in synaptic transmission in hippocampus.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".