Different actions of Gabapentin and baclofen in hippocampus from <i>weaver</i> mice
Bibliographic record
Abstract
The pre- and postsynaptic effects of baclofen, a broad-spectrum gamma-aminobutyric acid (GABA)B receptor agonist, and gabapentin, a selective agonist at GABA(B) receptors composed of GABA(B)(1a,2) heterodimers, were examined in CA1 pyramidal cells using whole-cell patch-clamp recordings in hippocampal slices from different strains of mice. In slices from C57BL/6 mice, by means of GABA(B) receptors, gabapentin and baclofen activated outward K+ currents at resting membrane potential. In weaver mice with a Kir3.2 channel mutation, baclofen and gabapentin failed to activate postsynaptic K+ currents. However, in littermate controls of weaver mice, gabapentin failed to evoke K+ currents, whereas baclofen activated currents in the same cells. Thus, postsynaptic actions of gabapentin and baclofen on K+ currents are different in this mouse strain. Via presynaptic GABA(B) receptors, baclofen significantly reduced GABA(A) inhibitory postsynaptic currents (IPSCs) in slices from C57BL/6 mice, as well as weaver and control mice. In contrast, gabapentin did not affect IPSCs significantly in any group of mice. These results indicate that although baclofen and gabapentin are agonists at postsynaptic GABA(B) receptors positively coupled to K+ channels, their mechanism of action differs in certain strains of mice, including the weaver wild-type mice, suggesting a dissociation in their signaling mechanism and coupling to K+ 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".