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Record W3087037682 · doi:10.7554/elife.53994

AANAT1 functions in astrocytes to regulate sleep homeostasis

2020· article· en· W3087037682 on OpenAlexafffund
Sejal Davla, Gregory Artiushin, Yongjun Li, Daryan Chitsaz, Sally Li, Amita Sehgal, Donald J. van Meyel

Bibliographic record

VenueeLife · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMonoamine neurotransmitterDopamineSleep (system call)WakefulnessSerotoninNeuroscienceSleep deprivationBiologyHomeostasisMonoaminergicAstrocyteEndocrinologyInternal medicineCircadian rhythmMedicineCentral nervous systemElectroencephalography

Abstract

fetched live from OpenAlex

How the brain controls the need and acquisition of recovery sleep after prolonged wakefulness is an important issue in sleep research. The monoamines serotonin and dopamine are key regulators of sleep in mammals and in Drosophila . We found that the enzyme arylalkylamine N-acetyltransferase 1 (AANAT1) is expressed by Drosophila astrocytes and specific subsets of neurons in the adult brain. AANAT1 acetylates monoamines and inactivates them, and we found that AANAT1 limited the accumulation of serotonin and dopamine in the brain upon sleep deprivation (SD). Loss of AANAT1 from astrocytes, but not from neurons, caused flies to increase their daytime recovery sleep following overnight SD. Together, these findings demonstrate a crucial role for AANAT1 and astrocytes in the regulation of monoamine bioavailability and homeostatic sleep.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.051
GPT teacher head0.295
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations42
Published2020
Admission routes2
Has abstractyes

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