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A metabolomic analytical approach permits identification of urinary biomarkers for Plasmodium falciparum infection: a case–control study

Overview of attention for article published in Malaria Journal, May 2017
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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6 X users

Citations

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25 Dimensions

Readers on

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70 Mendeley
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Title
A metabolomic analytical approach permits identification of urinary biomarkers for Plasmodium falciparum infection: a case–control study
Published in
Malaria Journal, May 2017
DOI 10.1186/s12936-017-1875-z
Pubmed ID
Authors

Salah Abdelrazig, Catharine A. Ortori, Gail Davey, Wakgari Deressa, Dhaba Mulleta, David A. Barrett, Alemayehu Amberbir, Andrew W. Fogarty

Abstract

Currently available diagnostic techniques of Plasmodium falciparum infection are not optimal for non-invasive, population-based screening for malaria. It was hypothesized that a mass spectrometry-based metabolomics approach could identify urinary biomarkers of falciparum malaria. The study used a case-control design, with cases consisting of 21 adults in central Ethiopia with a diagnosis of P. falciparum infection confirmed with microscopy, and 25 controls of adults with negative blood smears for malaria matched on age and sex. Urinary samples were collected from these individuals during presentation at the clinic, and a second sample was collected from both cases and controls 4 weeks later, after the cases had received anti-malarial medication. The urine samples were screened for small molecule urinary biomarkers, using mass spectrometry-based metabolomics analyses followed by multivariate analysis using principal component analysis and orthogonal partial least square-discriminant analysis. The chemical identity of statistically significant malaria biomarkers was confirmed using tandem mass spectrometry. The urinary metabolic profiles of cases with P. falciparum infection were distinct from healthy controls. After treatment with anti-malarial medication, the metabolomic profile of cases resembled that of healthy controls. Significantly altered levels of 29 urinary metabolites were found. Elevated levels of urinary pipecolic acid, taurine, N-acetylspermidine, N-acetylputrescine and 1,3-diacetylpropane were identified as potential biomarkers of falciparum malaria. The urinary biomarkers of malaria identified have potential for the development of non-invasive and rapid diagnostic test of P. falciparum infection.

X Demographics

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The data shown below were collected from the profiles of 6 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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 20%
Student > Ph. D. Student 11 16%
Student > Bachelor 8 11%
Student > Master 8 11%
Student > Doctoral Student 2 3%
Other 7 10%
Unknown 20 29%
Readers by discipline Count As %
Medicine and Dentistry 10 14%
Biochemistry, Genetics and Molecular Biology 10 14%
Pharmacology, Toxicology and Pharmaceutical Science 6 9%
Agricultural and Biological Sciences 6 9%
Immunology and Microbiology 3 4%
Other 9 13%
Unknown 26 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 15 June 2017.
All research outputs
#8,076,539
of 24,400,706 outputs
Outputs from Malaria Journal
#2,530
of 5,827 outputs
Outputs of similar age
#121,841
of 319,930 outputs
Outputs of similar age from Malaria Journal
#83
of 138 outputs
Altmetric has tracked 24,400,706 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 5,827 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 55% 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 319,930 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.