The role of mTORC1/4EBP1 signaling pathway in regulation of orexin ligand-receptor system and sleep-wake states
Bibliographic record
Abstract
Insufficient sleep is recognized as a public health epidemic, where sleep loss and sleep disorder have adverse effects on human health, longevity and social economics. However, the molecular mechanisms involved in sleep-wake regulation remains ambiguous. Recent studies have shown that mTORC1/4EBPs pathway is correlated with sleep and sleep deprivation (SD)1,2,3,4. Sleep promotes protein synthesis in the hypothalamus, while sleep deprivation decreased mTOR activity2,4. The orexin system has been implicated as critical regulator in sleep-wake states, and orexin deficiency leads to sleep disorder narcolepsy5,6,7,8. In this study, I show that for the first time mTORC1/4EBP1 pathway regulates the expression of prepro-orexin at transcriptional level, while affects the expression of orexin receptor 2 (OX2R) translationally. In addition, I demonstrate that even though the prepro-orexin mRNA levels were not affected by 6 hours of SD as reported9, the OX2R expression was affected significantly, and this changes is likely mediated by mTOR pathway. Furthermore, I found that OX2R is a target of ubiquitin proteasomal pathway, and has a rapid turnover rate under normal condition. Overall, these findings show that SD affects the activity of orexin system by regulating the local expression of OX2R instead of prepro-orexin itself. Additionally, the expression of OX2R and prepro-orexin are regulated by mTORC1/4EBPs pathway.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".