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Weakly Circadian Cells Improve Resynchrony

Overview of attention for article published in PLoS Computational Biology, November 2012
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Title
Weakly Circadian Cells Improve Resynchrony
Published in
PLoS Computational Biology, November 2012
DOI 10.1371/journal.pcbi.1002787
Pubmed ID
Authors

Alexis B. Webb, Stephanie R. Taylor, Kurt A. Thoroughman, Francis J. Doyle, Erik D. Herzog

Abstract

The mammalian suprachiasmatic nuclei (SCN) contain thousands of neurons capable of generating near 24-h rhythms. When isolated from their network, SCN neurons exhibit a range of oscillatory phenotypes: sustained or damping oscillations, or arrhythmic patterns. The implications of this variability are unknown. Experimentally, we found that cells within SCN explants recover from pharmacologically-induced desynchrony by re-establishing rhythmicity and synchrony in waves, independent of their intrinsic circadian period We therefore hypothesized that a cell's location within the network may also critically determine its resynchronization. To test this, we employed a deterministic, mechanistic model of circadian oscillators where we could independently control cell-intrinsic and network-connectivity parameters. We found that small changes in key parameters produced the full range of oscillatory phenotypes seen in biological cells, including similar distributions of period, amplitude and ability to cycle. The model also predicted that weaker oscillators could adjust their phase more readily than stronger oscillators. Using these model cells we explored potential biological consequences of their number and placement within the network. We found that the population synchronized to a higher degree when weak oscillators were at highly connected nodes within the network. A mathematically independent phase-amplitude model reproduced these findings. Thus, small differences in cell-intrinsic parameters contribute to large changes in the oscillatory ability of a cell, but the location of weak oscillators within the network also critically shapes the degree of synchronization for the population.

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Geographical breakdown

Country Count As %
United Kingdom 2 3%
Germany 1 1%
Portugal 1 1%
Malta 1 1%
Japan 1 1%
Unknown 62 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 25%
Researcher 17 25%
Student > Master 5 7%
Student > Bachelor 5 7%
Student > Doctoral Student 4 6%
Other 15 22%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 28%
Physics and Astronomy 9 13%
Engineering 9 13%
Neuroscience 6 9%
Computer Science 4 6%
Other 15 22%
Unknown 6 9%