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Taking the Lag out of Jet Lag through Model-Based Schedule Design

Overview of attention for article published in PLoS Computational Biology, June 2009
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Title
Taking the Lag out of Jet Lag through Model-Based Schedule Design
Published in
PLoS Computational Biology, June 2009
DOI 10.1371/journal.pcbi.1000418
Pubmed ID
Authors

Dennis A. Dean, Daniel B. Forger, Elizabeth B. Klerman

Abstract

Travel across multiple time zones results in desynchronization of environmental time cues and the sleep-wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep-wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep-wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep-wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.

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Geographical breakdown

Country Count As %
Germany 5 5%
United States 4 4%
United Kingdom 3 3%
Sweden 1 1%
Portugal 1 1%
Switzerland 1 1%
Finland 1 1%
Unknown 79 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 20%
Student > Ph. D. Student 16 17%
Professor > Associate Professor 11 12%
Student > Master 11 12%
Professor 10 11%
Other 20 21%
Unknown 8 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 19%
Medicine and Dentistry 14 15%
Engineering 11 12%
Psychology 8 8%
Computer Science 6 6%
Other 23 24%
Unknown 15 16%