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Rapid and Robust Identification of the Agents of Black-Grain Mycetoma by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

Overview of attention for article published in Journal of Clinical Microbiology, June 2017
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Rapid and Robust Identification of the Agents of Black-Grain Mycetoma by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry
Published in
Journal of Clinical Microbiology, June 2017
DOI 10.1128/jcm.00417-17
Pubmed ID
Authors

Mark Fraser, Andrew M. Borman, Elizabeth M. Johnson

Abstract

Eumycetoma, a chronic fungal infection endemic in India, Indonesia and parts of Africa and South and Central America, follows traumatic implantation of saprophytic fungi and frequently requires radical surgery or amputation in the absence of appropriate treatment. Fungal species that can cause black-grain mycetomas include Madurella spp., Falciformispora spp., Trematosphaeria grisea, Nigrograna mackinnonii, Pseudochaetosphaeronema larense, Medicopsis romeroi and Emarellia spp. Rhytidhysteron rufulum and Parathyridaria percutanea cause similar subcutaneous infections, but which lack the draining sinuses and fungal grains characteristic of eumycetoma. Accurate identification of the agents of subcutaneous fungal infection is essential to guide appropriate antifungal therapy. Since phenotypic identification of the causative fungi is often difficult, time-consuming molecular approaches are currently required. Here we have evaluated whether MALDI-ToF mass spectrometry might allow the accurate identification of eumycetoma agents and related fungi. A panel of 57 organisms corresponding to 10 different species from confirmed cases of eumycetoma and subcutaneous pedal masses, previously formally identified by PCR amplification and sequencing of ITS1, were employed. Representative isolates of each species were used to create reference MALDI-ToF spectra, which were then used for the identification of the remaining isolates in a user-blinded manner. Here, we demonstrate that MALDI-ToF mass spectrometry accurately identified all of the test isolates, with 100%, 90.4% and 67.3% of isolates achieving LogScores greater than 1.8, 1.9 and 2.0, respectively.

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X Demographics

The data shown below were collected from the profiles of 11 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 24%
Other 4 12%
Student > Postgraduate 3 9%
Student > Master 3 9%
Student > Bachelor 2 6%
Other 6 18%
Unknown 7 21%
Readers by discipline Count As %
Immunology and Microbiology 9 27%
Medicine and Dentistry 4 12%
Agricultural and Biological Sciences 4 12%
Economics, Econometrics and Finance 2 6%
Biochemistry, Genetics and Molecular Biology 2 6%
Other 3 9%
Unknown 9 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 18 August 2017.
All research outputs
#6,375,394
of 25,382,440 outputs
Outputs from Journal of Clinical Microbiology
#5,208
of 14,318 outputs
Outputs of similar age
#94,329
of 331,588 outputs
Outputs of similar age from Journal of Clinical Microbiology
#48
of 91 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 14,318 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has gotten more attention than average, scoring higher than 63% 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 331,588 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 71% of its contemporaries.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.