Sensitivity of synaptic GABA<sub>A</sub> receptors to allosteric modulators in hippocampal oriens‐alveus interneurons
Bibliographic record
Abstract
GABA(A) receptors are heteropentamers that are heterogeneously distributed at different synapses in the central nervous system. Although the modulation of GABA(A) receptors received much attention in hippocampal pyramidal cells, information is scarce regarding the pharmacology of these receptors in inhibitory interneurons. We investigated the pharmacological properties of GABA(A)-mediated miniature inhibitory postsynaptic currents (mIPSCs) using whole-cell voltage clamp recordings in two morphologically identified types of hippocampal CA1 interneurons, horizontal and vertical cells of stratum oriens-alveus. The negative modulators zinc (200 microM) and furosemide (600 microM) significantly decreased the amplitude of mIPSCs. Benzodiazepine agonists also produced significant effects: 10 microM zolpidem increased the amplitude, rise time, and decay time constant (decay tau) of mIPSCs, whereas 10 microM flunitrazepam affected similarly the amplitude and decay tau, but not the rise time. The neurosteroid allopregnanolone (10 microM) prolonged the decay tau of mIPSCs. Since these modulators act on different GABA(A) receptor subunits, this pharmacological profile suggests that GABA(A) receptors at spontaneously active inhibitory synapses onto vertical and horizontal interneurons are heterogeneous and formed by co-assembly of different combinations of subunits (alpha(1-5)beta(1-3)gamma(1-3)). Furthermore, these synaptic GABA(A) receptors appear in large part pharmacologically similar to those of pyramidal cells.
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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) | 0.001 | 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".