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Analysis Method and Experimental Conditions Affect Computed Circadian Phase from Melatonin Data

Overview of attention for article published in PLOS ONE, April 2012
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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1 policy source
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53 Mendeley
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Article details
Title
Analysis Method and Experimental Conditions Affect Computed Circadian Phase from Melatonin Data
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0033836
Pubmed ID
Authors
Abstract

Accurate determination of circadian phase is necessary for research and clinical purposes because of the influence of the master circadian pacemaker on multiple physiologic functions. Melatonin is presently the most accurate marker of the activity of the human circadian pacemaker. Current methods of analyzing the plasma melatonin rhythm can be grouped into three categories: curve-fitting, threshold-based and physiologically-based linear differential equations. To determine which method provides the most accurate assessment of circadian phase, we compared the ability to fit the data and the variability of phase estimates for seventeen different markers of melatonin phase derived from these methodological categories. We used data from three experimental conditions under which circadian rhythms - and therefore calculated melatonin phase - were expected to remain constant or progress uniformly. Melatonin profiles from older subjects and subjects with lower melatonin amplitude were less likely to be fit by all analysis methods. When circadian drift over multiple study days was algebraically removed, there were no significant differences between analysis methods of melatonin onsets (P = 0.57), but there were significant differences between those of melatonin offsets (P<0.0001). For a subset of phase assessment methods, we also examined the effects of data loss on variability of phase estimates by systematically removing data in 2-hour segments. Data loss near onset of melatonin secretion differentially affected phase estimates from the methods, with some methods incorrectly assigning phases too early while other methods assigning phases too late; missing data at other times did not affect analyses of the melatonin profile. We conclude that melatonin data set characteristics, including amplitude and completeness of data collection, differentially affect the results depending on the melatonin analysis method used.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 4%
Spain 1 2%
Australia 1 2%
Unknown 49 92%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 16 30%
Student > Ph. D. Student 11 21%
Student > Master 4 8%
Professor > Associate Professor 4 8%
Other 3 6%
Other 7 13%
Unknown 8 15%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 12 23%
Agricultural and Biological Sciences 9 17%
Psychology 6 11%
Engineering 5 9%
Computer Science 3 6%
Other 9 17%
Unknown 9 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 January 2025.
All research outputs
#6,768,898
of 34,364,397 outputs
Outputs from PLOS ONE
#64,321
of 224,528 outputs
Outputs of similar age
#40,970
of 209,702 outputs
Outputs of similar age from PLOS ONE
#1,176
of 4,069 outputs
Altmetric has tracked 34,364,397 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 224,528 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 209,702 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 4,069 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.