Presynaptic α2-GABA<sub>A</sub>Receptors in Primary Afferent Depolarization and Spinal Pain Control
Bibliographic record
Abstract
Spinal dorsal horn GABA(A) receptors are found both postsynaptically on central neurons and presynaptically on axons and/or terminals of primary sensory neurons, where they mediate primary afferent depolarization (PAD) and presynaptic inhibition. Both phenomena have been studied extensively on a cellular level, but their role in sensory processing in vivo has remained elusive, due to inherent difficulties to selectively interfere with presynaptic receptors. Here, we address the contribution of a major subpopulation of GABA(A) receptors (those containing the α2 subunit) to spinal pain control in mice lacking α2-GABA(A) receptors specifically in primary nociceptors (sns-α2(-/-) mice). sns-α2(-/-) mice exhibited GABA(A) receptor currents and dorsal root potentials of normal amplitude in vitro, and normal response thresholds to thermal and mechanical stimulation in vivo, and developed normal inflammatory and neuropathic pain sensitization. However, the positive allosteric GABA(A) receptor modulator diazepam (DZP) had almost completely lost its potentiating effect on PAD and presynaptic inhibition in vitro and a major part of its spinal antihyperalgesic action against inflammatory hyperalgesia in vivo. Our results thus show that part of the antihyperalgesic action of spinally applied DZP occurs through facilitated activation of GABA(A) receptors residing on primary nociceptors.
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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 | 0.001 |
| 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".