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A Pilot Characterization of the Human Chronobiome

Overview of attention for article published in Scientific Reports, December 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
8 news outlets
blogs
2 blogs
twitter
85 X users
facebook
2 Facebook pages

Citations

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71 Dimensions

Readers on

mendeley
111 Mendeley
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Title
A Pilot Characterization of the Human Chronobiome
Published in
Scientific Reports, December 2017
DOI 10.1038/s41598-017-17362-6
Pubmed ID
Authors

Carsten Skarke, Nicholas F. Lahens, Seth D. Rhoades, Amy Campbell, Kyle Bittinger, Aubrey Bailey, Christian Hoffmann, Randal S. Olson, Lihong Chen, Guangrui Yang, Thomas S. Price, Jason H. Moore, Frederic D. Bushman, Casey S. Greene, Gregory R. Grant, Aalim M. Weljie, Garret A. FitzGerald

Abstract

Physiological function, disease expression and drug effects vary by time-of-day. Clock disruption in mice results in cardio-metabolic, immunological and neurological dysfunction; circadian misalignment using forced desynchrony increases cardiovascular risk factors in humans. Here we integrated data from remote sensors, physiological and multi-omics analyses to assess the feasibility of detecting time dependent signals - the chronobiome - despite the "noise" attributable to the behavioral differences of free-living human volunteers. The majority (62%) of sensor readouts showed time-specific variability including the expected variation in blood pressure, heart rate, and cortisol. While variance in the multi-omics is dominated by inter-individual differences, temporal patterns are evident in the metabolome (5.4% in plasma, 5.6% in saliva) and in several genera of the oral microbiome. This demonstrates, despite a small sample size and limited sampling, the feasibility of characterizing at scale the human chronobiome "in the wild". Such reference data at scale are a prerequisite to detect and mechanistically interpret discordant data derived from patients with temporal patterns of disease expression, to develop time-specific therapeutic strategies and to refine existing treatments.

X Demographics

X Demographics

The data shown below were collected from the profiles of 85 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 111 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 16%
Researcher 14 13%
Student > Master 12 11%
Student > Bachelor 11 10%
Professor > Associate Professor 8 7%
Other 20 18%
Unknown 28 25%
Readers by discipline Count As %
Medicine and Dentistry 20 18%
Biochemistry, Genetics and Molecular Biology 16 14%
Agricultural and Biological Sciences 9 8%
Neuroscience 7 6%
Immunology and Microbiology 5 5%
Other 17 15%
Unknown 37 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 113. 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 25 January 2023.
All research outputs
#366,878
of 25,331,507 outputs
Outputs from Scientific Reports
#4,080
of 139,412 outputs
Outputs of similar age
#8,177
of 453,759 outputs
Outputs of similar age from Scientific Reports
#145
of 4,323 outputs
Altmetric has tracked 25,331,507 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 139,412 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.7. This one has done particularly well, scoring higher than 97% 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 453,759 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 4,323 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.