Dynamic changes in GABAAreceptors on basal forebrain cholinergic neurons following sleep deprivation and recovery
Bibliographic record
Abstract
BACKGROUND: The basal forebrain (BF) cholinergic neurons play an important role in cortical activation and arousal and are active in association with cortical activation of waking and inactive in association with cortical slow wave activity of sleep. In view of findings that GABAA receptors (Rs) and inhibitory transmission undergo dynamic changes as a function of prior activity, we investigated whether the GABAARs on cholinergic cells might undergo such changes as a function of their prior activity during waking vs. sleep. RESULTS: In the brains of rats under sleep control (SC), sleep deprivation (SD) or sleep recovery (SR) conditions in the 3 hours prior to sacrifice, we examined immunofluorescent staining for beta2-3 subunit GABAARs on choline acetyltransferase (ChAT) immunopositive (+) cells in the magnocellular BF. In sections also stained for c-Fos, beta2-3 GABAARs were present on ChAT+ neurons which expressed c-Fos in the SD group alone and were variable or undetectable on other ChAT+ cells across groups. In dual-immunostained sections, the luminance of beta2-3 GABAARs over the membrane of ChAT+ cells was found to vary significantly across conditions and to be significantly higher in SD than SC or SR groups. CONCLUSION: We conclude that membrane GABAARs increase on cholinergic cells as a result of activity during sustained waking and reciprocally decrease as a result of inactivity during sleep. These changes in membrane GABAARs would be associated with increased GABA-mediated inhibition of cholinergic cells following prolonged waking and diminished inhibition following sleep and could thus reflect a homeostatic process regulating cholinergic cell activity and thereby indirectly cortical activity across the sleep-waking cycle.
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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".