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A metabolic biosignature of early response to anti-tuberculosis treatment

Overview of attention for article published in BMC Infectious Diseases, January 2014
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Mentioned by

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2 tweeters

Citations

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53 Dimensions

Readers on

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111 Mendeley

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Title
A metabolic biosignature of early response to anti-tuberculosis treatment
Published in
BMC Infectious Diseases, January 2014
DOI 10.1186/1471-2334-14-53
Pubmed ID
24484441
Authors

Sebabrata Mahapatra, Ann M Hess, John L Johnson, Kathleen D Eisenach, Mary A DeGroote, Phineas Gitta, Moses L Joloba, Gilla Kaplan, Gerhard Walzl, W Henry Boom, John T Belisle

Abstract

The successful treatment of tuberculosis (TB) requires long-term multidrug chemotherapy. Clinical trials to evaluate new drugs and regimens for TB treatment are protracted due to the slow clearance of Mycobacterium tuberculosis (Mtb) infection and the lack of early biomarkers to predict treatment outcome. Advancements in the field of metabolomics make it possible to identify metabolic profiles that correlate with disease states or successful chemotherapy. However, proof-of-concept of this approach has not been provided for a TB-early treatment response biosignature (TB-ETRB).

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Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
South Africa 1 <1%
Unknown 108 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 28%
Student > Ph. D. Student 17 15%
Student > Master 13 12%
Student > Bachelor 8 7%
Student > Postgraduate 6 5%
Other 20 18%
Unknown 16 14%
Readers by discipline Count As %
Medicine and Dentistry 33 30%
Agricultural and Biological Sciences 21 19%
Immunology and Microbiology 15 14%
Biochemistry, Genetics and Molecular Biology 11 10%
Computer Science 2 2%
Other 10 9%
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 15 February 2014.
All research outputs
#4,609,760
of 6,232,855 outputs
Outputs from BMC Infectious Diseases
#2,219
of 3,010 outputs
Outputs of similar age
#100,834
of 150,713 outputs
Outputs of similar age from BMC Infectious Diseases
#108
of 137 outputs
Altmetric has tracked 6,232,855 research outputs across all sources so far. This one is in the 15th percentile – i.e., 15% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,010 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 7th percentile – i.e., 7% 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 150,713 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.

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