Faculty Opinions recommendation of D1 receptor activation in the mushroom bodies rescues sleep-loss-induced learning impairments in Drosophila.
Bibliographic record
Abstract
BACKGROUND: Extended wakefulness disrupts acquisition of short-term memories in mammals. However, the underlying molecular mechanisms triggered by extended waking and restored by sleep are unknown. Moreover, the neuronal circuits that depend on sleep for optimal learning remain unidentified.RESULTS: Learning was evaluated with aversive phototaxic suppression. In this task, flies learn to avoid light that is paired with an aversive stimulus (quinine-humidity). We demonstrate extensive homology in sleep-deprivation-induced learning impairment between flies and humans. Both 6 hr and 12 hr of sleep deprivation are sufficient to impair learning in Canton-S (Cs) flies. Moreover, learning is impaired at the end of the normal waking day in direct correlation with time spent awake. Mechanistic studies indicate that this task requires intact mushroom bodies (MBs) and requires the dopamine D1-like receptor (dDA1). Importantly, sleep-deprivation-induced learning impairments could be rescued by targeted gene expression of the dDA1 receptor to the MBs.CONCLUSIONS: These data provide direct evidence that extended wakefulness disrupts learning in Drosophila. These results demonstrate that it is possible to prevent the effects of sleep deprivation by targeting a single neuronal structure and identify cellular and molecular targets adversely affected by extended waking in a genetically tractable model organism. PMID: 18674913 Funding information This work was supported by: NINDS NIH HHS, United States Grant ID: R01 NS051305 NINDS NIH HHS, United States Grant ID: R01 NS051305-04 NINDS NIH HHS, United States Grant ID: R01 NS051305-03 NINDS NIH HHS, United States Grant ID: NS057105 NINDS NIH HHS, United States Grant ID: 1 R01 NS051305-01A1 NINDS NIH HHS, United States Grant ID: P30 NS057105 More Less keyboard_arrow_down
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.332 | 0.099 |
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".