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Genetic makeup of Shiga toxin-producing Escherichia coli in relation to clinical symptoms and duration of shedding: a microarray analysis of isolates from Swedish children

Overview of attention for article published in European Journal of Clinical Microbiology & Infectious Diseases, April 2017
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Title
Genetic makeup of Shiga toxin-producing Escherichia coli in relation to clinical symptoms and duration of shedding: a microarray analysis of isolates from Swedish children
Published in
European Journal of Clinical Microbiology & Infectious Diseases, April 2017
DOI 10.1007/s10096-017-2950-7
Pubmed ID
Authors

A. Matussek, C. Jernberg, I.-M. Einemo, S. Monecke, R. Ehricht, I. Engelmann, S. Löfgren, S. Mernelius

Abstract

Shiga toxin (Stx)-producing Escherichia coli (STECs) cause non-bloody diarrhea, hemorrhagic colitis, and hemolytic uremic syndrome, and are the primary cause of acute renal failure in children worldwide. This study investigated the correlation of genetic makeup of STEC strains as revealed by DNA microarray to clinical symptoms and the duration of STEC shedding. All STEC isolated (n = 96) from patients <10 years of age in Jönköping County, Sweden from 2003 to 2015 were included. Isolates were characterized by DNA microarray, including almost 280 genes. Clinical data were collected through a questionnaire and by reviewing medical records. Of the 96 virulence genes (including stx) in the microarray, 62 genes were present in at least one isolate. Statistically significant differences in prevalence were observed for 21 genes when comparing patients with bloody diarrhea (BD) and with non-bloody stool (18 of 21 associated with BD). Most genes encode toxins (e.g., stx2 alleles, astA, toxB), adhesion factors (i.e. espB_O157, tir, eae), or secretion factors (e.g., espA, espF, espJ, etpD, nleA, nleB, nleC, tccP). Seven genes were associated with prolonged stx shedding; the presence of three genes (lpfA, senB, and stx1) and the absence of four genes (espB_O157, espF, astA, and intI1). We found STEC genes that might predict severe disease outcome already at diagnosis. This can be used to develop diagnostic tools for risk assessment of disease outcome. Furthermore, genes associated with the duration of stx shedding were detected, enabling a possible better prediction of length of STEC carriage after infection.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 5 15%
Student > Ph. D. Student 4 12%
Researcher 4 12%
Student > Bachelor 4 12%
Other 3 9%
Other 10 29%
Unknown 4 12%
Readers by discipline Count As %
Immunology and Microbiology 5 15%
Biochemistry, Genetics and Molecular Biology 5 15%
Medicine and Dentistry 5 15%
Agricultural and Biological Sciences 5 15%
Psychology 2 6%
Other 4 12%
Unknown 8 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 April 2017.
All research outputs
#13,548,595
of 22,965,074 outputs
Outputs from European Journal of Clinical Microbiology & Infectious Diseases
#1,624
of 2,789 outputs
Outputs of similar age
#158,556
of 310,317 outputs
Outputs of similar age from European Journal of Clinical Microbiology & Infectious Diseases
#19
of 55 outputs
Altmetric has tracked 22,965,074 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,789 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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 310,317 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 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 63% of its contemporaries.