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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Sequence analysis for detection of first-line drug resistance in Mycobacterium tuberculosis strains from a high-incidence setting
|
|---|---|
| Published in |
BMC Microbiology, May 2012
|
| DOI | 10.1186/1471-2180-12-90 |
| Pubmed ID | |
| Authors |
Silke Feuerriegel, Barbara Oberhauser, Abu Garawani 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 2% |
| Unknown | 128 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 19% |
| Student > Master | 24 | 18% |
| Student > Ph. D. Student | 22 | 17% |
| Professor | 11 | 8% |
| Student > Postgraduate | 7 | 5% |
| Other | 17 | 13% |
| Unknown | 24 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 24% |
| Medicine and Dentistry | 26 | 20% |
| Biochemistry, Genetics and Molecular Biology | 21 | 16% |
| Immunology and Microbiology | 7 | 5% |
| Computer Science | 6 | 5% |
| Other | 10 | 8% |
| Unknown | 29 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 04 February 2021.
All research outputs
#7,356,343
of 25,374,917 outputs
Outputs from BMC Microbiology
#792
of 3,489 outputs
Outputs of similar age
#49,822
of 178,898 outputs
Outputs of similar age from BMC Microbiology
#11
of 40 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 3,489 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 76% 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 178,898 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 40 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 70% of its contemporaries.