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Shiga Toxin-Producing Escherichia coli O157 Shedding Dynamics in an Australian Beef Herd

Overview of attention for article published in Frontiers in Veterinary Science, November 2017
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Title
Shiga Toxin-Producing Escherichia coli O157 Shedding Dynamics in an Australian Beef Herd
Published in
Frontiers in Veterinary Science, November 2017
DOI 10.3389/fvets.2017.00200
Pubmed ID
Authors

Christina Ahlstrom, Petra Muellner, Geraldine Lammers, Meghan Jones, Sophie Octavia, Ruiting Lan, Jane Heller

Abstract

Shiga toxin-producing Escherichia coli (STEC) O157 is an important foodborne pathogen that can be transmitted to humans both directly and indirectly from the feces of beef cattle, its primary reservoir. Numerous studies have investigated the shedding dynamics of E. coli O157 by beef cattle; however, the spatiotemporal trends of shedding are still not well understood. Molecular tools can increase the resolution through the use of strain typing to explore transmission dynamics within and between herds and identify strain-specific characteristics that may influence pathogenicity and spread. Previously, the shedding dynamics and molecular diversity, through the use of multilocus variable number of tandem repeat analysis (MLVA) of STEC O157, were separately investigated in an Australian beef herd over a 9-month study period. Variation in shedding was observed over time, and 33 MLVA types were identified. The study presented here combines the two datasets previously published with an aim to clarify the relationship between epidemiological variables and strain types. Three major genetic clusters (GCs) were identified that were significantly associated with the location of the cattle in different paddocks. No significant association between GCs and individual cow was observed. Results from this molecular epidemiological study provide evidence for herd-level clonal replacement over time that may have been triggered by movement to a new paddock. In conclusion, this study has provided further insight into STEC O157 shedding dynamics and pathogen transmission. Knowledge gaps remain regarding the relationship of strain types and the shedding dynamics of STEC O157 by beef cattle that could be further clarified through the use of whole-genome sequencing.

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The data shown below were collected from the profiles of 3 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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 22%
Professor > Associate Professor 2 11%
Other 1 6%
Lecturer 1 6%
Student > Doctoral Student 1 6%
Other 5 28%
Unknown 4 22%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 3 17%
Biochemistry, Genetics and Molecular Biology 3 17%
Agricultural and Biological Sciences 3 17%
Immunology and Microbiology 1 6%
Medicine and Dentistry 1 6%
Other 0 0%
Unknown 7 39%
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 11 February 2018.
All research outputs
#14,085,315
of 23,008,860 outputs
Outputs from Frontiers in Veterinary Science
#2,092
of 6,317 outputs
Outputs of similar age
#228,681
of 438,449 outputs
Outputs of similar age from Frontiers in Veterinary Science
#34
of 70 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,317 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has gotten more attention than average, scoring higher than 64% 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 438,449 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.