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Phenotypic and Genotypic Characteristics of Shiga Toxin-Producing Escherichia coli Isolated from Surface Waters and Sediments in a Canadian Urban-Agricultural Landscape

Overview of attention for article published in Frontiers in Cellular and Infection Microbiology, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

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Title
Phenotypic and Genotypic Characteristics of Shiga Toxin-Producing Escherichia coli Isolated from Surface Waters and Sediments in a Canadian Urban-Agricultural Landscape
Published in
Frontiers in Cellular and Infection Microbiology, April 2016
DOI 10.3389/fcimb.2016.00036
Pubmed ID
Authors

Stephanie Nadya, Pascal Delaquis, Jessica Chen, Kevin Allen, Roger P. Johnson, Kim Ziebell, Chad Laing, Victor Gannon, Susan Bach, Edward Topp

Abstract

A hydrophobic grid membrane filtration-Shiga toxin immunoblot method was used to examine the prevalence of Shiga toxin-producing Escherichia coli (STEC) in four watersheds located in the Lower Mainland of British Columbia, Canada, a region characterized by rapid urbanization and intensive agricultural activity. STEC were recovered from 21.6, 23.2, 19.5, and 9.2% of surface water samples collected monthly from five sites in each watershed over a period of 1 year. Overall prevalence was subject to seasonal variation however, ranging between 13.3% during fall months and 34.3% during winter months. STEC were also recovered from 23.8% of sediment samples collected in one randomly selected site. One hundred distinct STEC isolates distributed among 29 definitive and 4 ambiguous or indeterminate serotypes were recovered from water and sediments, including isolates from Canadian "priority" serogroups O157 (3), O26 (4), O103 (5), and O111 (7). Forty seven isolates were further characterized by analysis of whole genome sequences to detect Shiga toxin gene (stx 1 and stx 2), intimin gene (eaeA) allelic variants and acquired virulence factors. These analyses collectively showed that surface waters from the region support highly diverse STEC populations that include strains with virulence factors commonly associated with human pathotypes. The present work served to characterize the microbiological hazard implied by STEC to support future assessments of risks to public health arising from non-agricultural and agricultural uses of surface water resources in the region.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Researcher 4 13%
Student > Master 3 10%
Student > Postgraduate 2 7%
Professor > Associate Professor 2 7%
Other 4 13%
Unknown 9 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 13%
Environmental Science 3 10%
Biochemistry, Genetics and Molecular Biology 3 10%
Immunology and Microbiology 2 7%
Engineering 2 7%
Other 5 17%
Unknown 11 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 16 August 2016.
All research outputs
#2,251,769
of 22,673,450 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#370
of 6,287 outputs
Outputs of similar age
#39,278
of 300,638 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#2
of 30 outputs
Altmetric has tracked 22,673,450 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 94% 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 300,638 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 86% of its contemporaries.
We're also able to compare this research output to 30 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.