Pentobarbital Enhances γ-Aminobutyric Acid-Mediated Excitation Without Altering Synaptic Plasticity in Rat Hippocampus
Bibliographic record
Abstract
BACKGROUND: Synaptic plasticity is thought to provide a molecular mechanism for learning and memory. N-methyl-d-aspartate receptor-mediated plasticity requires that N-methyl-d-aspartate receptor activation coincides with postsynaptic depolarizing potentials (DPSP(A)'s). Pentobarbital, in high concentrations, enhances DPSP(A)'s, but high concentrations suppress synaptic plasticity, probably by impairing glutamatergic transmission. Here we tested the hypothesis that low concentrations of pentobarbital can enhance DPSP(A)'s and modify the induction of synaptic plasticity. METHODS: Studies were performed in vitro on rat hippocampal slices. With glutamate transmission blocked, intracellular recording from CA1 neurons was used to investigate the influence of 5 microM pentobarbital on DPSP(A)'s and neuron excitability evoked by high frequency (100 Hz) stimulation. With glutamate transmission intact, extracellular recording was used to examine the effect of 5 microM pentobarbital on the induction of long-term depression and long-term potentiation of synaptic transmission by conditioning stimuli applied to the Schaffer collateral pathway. RESULTS: High frequency stimulation generated typical DPSP(A)'s that were mediated by gamma-aminobutyric acid(A) receptors and dependent upon HCO3-. Pentobarbital (5 microM) increased the amplitude, but not the width, at half-maximal amplitude of DPSPA's (P < 0.01). Pentobarbital increased the probability of action potential generation during the DPSP(A)'s. Pentobarbital did not alter the induction of long-term depression or long-term potentiation. CONCLUSIONS: Despite increasing the amplitude of DPSP(A)'s, 5 microM pentobarbital did not alter the induction of synaptic plasticity by a range of conventional conditioning stimuli. These results do not support the hypothesis that excitatory effects of pentobarbital may alter synaptic plasticity.
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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) | 0.001 | 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 | 0.001 |
| 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".