Faculty Opinions recommendation of A neuropeptide speeds circadian entrainment by reducing intercellular synchrony.
Bibliographic record
Abstract
Shift work or transmeridian travel can desynchronize the body's circadian rhythms from local light-dark cycles. The mammalian suprachiasmatic nucleus (SCN) generates and entrains daily rhythms in physiology and behavior. Paradoxically, we found that vasoactive intestinal polypeptide (VIP), a neuropeptide implicated in synchrony among SCN cells, can also desynchronize them. The degree and duration of desynchronization among SCN neurons depended on both the phase and the dose of VIP. A model of the SCN consisting of coupled stochastic cells predicted both the phase- and the dose-dependent response to VIP and that the transient phase desynchronization, or "phase tumbling", could arise from intrinsic, stochastic noise in small populations of key molecules (notably, Period mRNA near its daily minimum). The model also predicted that phase tumbling following brief VIP treatment would accelerate entrainment to shifted environmental cycles. We tested this using a prepulse of VIP during the day before a shift in either a light cycle in vivo or a temperature cycle in vitro. Although VIP during the day does not shift circadian rhythms, the VIP pretreatment approximately halved the time required for mice to reentrain to an 8-h shifted light schedule and for SCN cultures to reentrain to a 10-h shifted temperature cycle. We conclude that VIP below 100 nM synchronizes SCN cells and above 100 nM reduces synchrony in the SCN. We show that exploiting these mechanisms that transiently reduce cellular synchrony before a large shift in the schedule of daily environmental cues has the potential to reduce jet lag. PMID: 24167276 Funding information This work was supported by: NIDA NIH HHS, United States Grant ID: T90 DA022871 NIGMS NIH HHS, United States Grant ID: T32 GM008151 NIGMS NIH HHS, United States Grant ID: R01 GM096873
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.463 | 0.157 |
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".