| Title |
Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples
|
|---|---|
| Published in |
Metabolomics, February 2011
|
| DOI | 10.1007/s11306-011-0289-0 |
| Pubmed ID | |
| Authors |
Gaëlle Favé, Manfred Beckmann, Amanda J. Lloyd, Shaobo Zhou, Graham Harold, Wanchang Lin, Kathleen Tailliart, Long Xie, John Draper, John C. Mathers |
| Abstract |
Conventional tools for measuring dietary exposure have well recognized limitations. Measurement of food-derived metabolites in biofluids provides an alternative approach and our aim was to develop an experimental protocol which ensures that extraneous variability does not obscure metabolic signals from ingested foods. Healthy adults consumed a standardized meal in the evening before each test day and collected pooled overnight urine. On each test day of three different studies, urine was collected in the fasted state and at different time points after consumption of a standardized breakfast. Metabolite fingerprinting of samples using Flow Infusion Electrospray-Ionization Mass Spectrometry followed by multivariate data analysis showed strong discrimination between overnight, fasting and postprandial samples, in each study separately and when data from the three studies were pooled. Such differences were robust and highly reproducible within individuals on separate occasions. Urine volume was an efficient data normalization factor for metabolite fingerprinting data. Postprandial urines had a stable chemical composition over a period of 2-4 h after eating a standardized breakfast, suggesting that there is a flexible time window for urine collection. Fasting urine samples provided a stable baseline for universal comparisons with postprandial samples. A dietary exposure biomarker discovery protocol was validated by demonstrating that top-ranked signals discriminating between fasting and 2-4 h postprandial urine samples could be linked to metabolites abundant in some components of the standardized breakfast. We conclude that the protocol developed will have value in the search for biomarker leads of dietary exposure. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0289-0) contains supplementary material, which is available to authorized users. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 2% |
| Colombia | 1 | <1% |
| Australia | 1 | <1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Greece | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 110 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 30 | 25% |
| Researcher | 25 | 21% |
| Student > Master | 10 | 8% |
| Professor > Associate Professor | 7 | 6% |
| Professor | 7 | 6% |
| Other | 24 | 20% |
| Unknown | 15 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 26% |
| Chemistry | 21 | 18% |
| Medicine and Dentistry | 10 | 8% |
| Biochemistry, Genetics and Molecular Biology | 8 | 7% |
| Computer Science | 6 | 5% |
| Other | 23 | 19% |
| Unknown | 19 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 19 December 2016.
All research outputs
#3,420,372
of 23,577,761 outputs
Outputs from Metabolomics
#176
of 1,322 outputs
Outputs of similar age
#15,111
of 108,368 outputs
Outputs of similar age from Metabolomics
#2
of 8 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,322 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 86% 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 108,368 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 83% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.