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Sequence analysis for detection of first-line drug resistance in Mycobacterium tuberculosis strains from a high-incidence setting

Overview of attention for article published in BMC Microbiology, January 2012
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Mentioned by

twitter
1 tweeter

Citations

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66 Dimensions

Readers on

mendeley
113 Mendeley
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Title
Sequence analysis for detection of first-line drug resistance in Mycobacterium tuberculosis strains from a high-incidence setting
Published in
BMC Microbiology, January 2012
DOI 10.1186/1471-2180-12-90
Pubmed ID
Authors

Silke Feuerriegel, Barbara Oberhauser, Abu George, Foday Dafae, Elvira Richter, Sabine Rüsch-Gerdes, Stefan Niemann

Abstract

Drug resistance displays a problem for the therapy of Mycobacterium tuberculosis infections. For molecular resistance testing, it is essential to have precise knowledge on genomic variations involved in resistance development. However, data from high-incidence settings are only sparely available. Therefore we performed a systematic approach and analyzed a total of 97 M. tuberculosis strains from previously treated patients in Sierra Leone for mutations in katG, rpoB, rrs, rpsL, gidB, embB, pncA and where applicable in inhA and ahpC. Of the strains investigated 50 were either mono- or poly-resistant to isoniazid, rifampin, streptomycin, ethambutol and pyrazinamide or MDR and 47 fully susceptible strains served as controls.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
Chile 1 <1%
Unknown 110 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 27 24%
Researcher 20 18%
Student > Ph. D. Student 19 17%
Professor 10 9%
Student > Postgraduate 6 5%
Other 16 14%
Unknown 15 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 27%
Medicine and Dentistry 23 20%
Biochemistry, Genetics and Molecular Biology 22 19%
Computer Science 7 6%
Immunology and Microbiology 4 4%
Other 7 6%
Unknown 19 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 August 2012.
All research outputs
#7,762,012
of 12,372,633 outputs
Outputs from BMC Microbiology
#987
of 1,804 outputs
Outputs of similar age
#70,907
of 126,194 outputs
Outputs of similar age from BMC Microbiology
#13
of 28 outputs
Altmetric has tracked 12,372,633 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,804 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 36th percentile – i.e., 36% 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 126,194 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.