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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Detection, Characterization, and Typing of Shiga Toxin-Producing Escherichia coli
|
|---|---|
| Published in |
Frontiers in Microbiology, April 2016
|
| DOI | 10.3389/fmicb.2016.00478 |
| Pubmed ID | |
| Authors |
Brendon D. Parsons, Nathan Zelyas, Byron M. Berenger, Linda Chui |
| Abstract |
Shiga toxin-producing Escherichia coli (STEC) are responsible for gastrointestinal diseases reported in numerous outbreaks around the world. Given the public health importance of STEC, effective detection, characterization and typing is critical to any medical laboratory system. While non-O157 serotypes account for the majority of STEC infections, frontline microbiology laboratories may only screen for STEC using O157-specific agar-based methods. As a result, non-O157 STEC infections are significantly under-reported. This review discusses recent advances on the detection, characterization and typing of STEC with emphasis on work performed at the Alberta Provincial Laboratory for Public Health (ProvLab). Candidates for the detection of all STEC serotypes include chromogenic agars, enzyme immunoassays (EIA) and quantitative real time polymerase chain reaction (qPCR). Culture methods allow further characterization of isolates, whereas qPCR provides the greatest sensitivity and specificity, followed by EIA. The virulence gene profiles using PCR arrays and stx gene subtypes can subsequently be determined. Different non-O157 serotypes exhibit markedly different virulence gene profiles and a greater prevalence of stx1 than stx2 subtypes compared to O157:H7 isolates. Finally, recent innovations in whole genome sequencing (WGS) have allowed it to emerge as a candidate for the characterization and typing of STEC in diagnostic surveillance isolates. Methods of whole genome analysis such as single nucleotide polymorphisms and k-mer analysis are concordant with epidemiological data and standard typing methods, such as pulsed-field gel electrophoresis and multiple-locus variable number tandem repeat analysis while offering additional strain differentiation. Together these findings highlight improved strategies for STEC detection using currently available systems and the development of novel approaches for future surveillance. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | <1% |
| Unknown | 157 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 31 | 20% |
| Student > Master | 24 | 15% |
| Student > Bachelor | 22 | 14% |
| Researcher | 18 | 11% |
| Student > Doctoral Student | 10 | 6% |
| Other | 23 | 15% |
| Unknown | 30 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 23% |
| Biochemistry, Genetics and Molecular Biology | 23 | 15% |
| Immunology and Microbiology | 23 | 15% |
| Medicine and Dentistry | 10 | 6% |
| Veterinary Science and Veterinary Medicine | 5 | 3% |
| Other | 20 | 13% |
| Unknown | 41 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 13 December 2022.
All research outputs
#4,611,824
of 23,443,716 outputs
Outputs from Frontiers in Microbiology
#4,576
of 25,847 outputs
Outputs of similar age
#71,624
of 302,301 outputs
Outputs of similar age from Frontiers in Microbiology
#146
of 561 outputs
Altmetric has tracked 23,443,716 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 25,847 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done well, scoring higher than 82% 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 302,301 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 76% of its contemporaries.
We're also able to compare this research output to 561 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 73% of its contemporaries.