α5GABA<sub>A</sub>Receptors Mediate Tonic Inhibition in the Spinal Cord Dorsal Horn and Contribute to the Resolution Of Hyperalgesia
Bibliographic record
Abstract
Abstract Neuronal inhibition mediated by GABAAreceptors constrains nociceptive processing in the spinal cord, and loss of GABAergic inhibition can produce allodynia and hyperalgesia. Extrasynaptic α5 subunit‐containing GABAAreceptors (α5GABAARs) generate a tonic conductance that inhibits neuronal activity and constrains learning and memory; however, it is unclear whether α5GABAARs similarly generate a tonic conductance in the spinal cord dorsal horn to constrain nociception. We assessed the distribution of α5GABAARs in the spinal cord dorsal horn by immunohistochemical analysis, and the activity and function of α5GABAARs in neurons of the superficial dorsal horn using electrophysiological and behavioral approaches in male, null‐mutant mice lacking the GABAAR α5 subunit (Gabra5−/−) and wild‐type mice (WT). The expression of α5GABAARs in the superficial dorsal horn followed a laminar pattern of distribution, with a higher expression in lamina II than lamina I. Similarly, the tonic GABAAcurrent in lamina II neurons had a larger contribution from α5GABAARs than in lamina I, with no significant contribution of these receptors to synaptic GABAAcurrent. In behavioural tests, WT andGabra5−/−mice exhibited similar acute thermal and mechanical nociception, and similar mechanical sensitization immediately following intraplantar capsaicin or Complete Freund's Adjuvant (CFA). However,Gabra5−/−mice showed prolonged recovery from sensitization in these models, and increased responses in the late phase of the formalin test. Overall, our data suggest that tonically‐active α5GABAARs in the spinal cord dorsal horn accelerate the resolution of hyperalgesia and may therefore serve as a novel therapeutic target to promote recovery from pathological pain. © 2016 Wiley Periodicals, Inc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".