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Analysis of the Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells to Discriminate Latent from Active Tuberculosis in HIV-Uninfected and HIV-Infected Individuals

Overview of attention for article published in Frontiers in immunology, August 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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1 policy source
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9 X users

Citations

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Title
Analysis of the Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells to Discriminate Latent from Active Tuberculosis in HIV-Uninfected and HIV-Infected Individuals
Published in
Frontiers in immunology, August 2017
DOI 10.3389/fimmu.2017.00968
Pubmed ID
Authors

Catherine Riou, Natacha Berkowitz, Rene Goliath, Wendy A. Burgers, Robert J. Wilkinson

Abstract

Several immune-based assays have been suggested to differentiate latent from active tuberculosis (TB). However, their relative performance as well as their efficacy in HIV-infected persons, a highly at-risk population, remains unclear. In a study of 81 individuals, divided into four groups based on their HIV-1 status and TB disease activity, we compared the differentiation (CD27 and KLRG1), activation (HLA-DR), homing potential (CCR4, CCR6, CXCR3, and CD161) and functional profiles (IFNγ, IL-2, and TNFα) of Mycobacterium tuberculosis (Mtb)-specific CD4+ T cells using flow cytometry. Active TB disease induced major changes within the Mtb-responding CD4+ T cell population, promoting memory maturation, elevated activation and increased inflammatory potential when compared to individuals with latent TB infection. Moreover, the functional profile of Mtb-specific CD4+ T cells appeared to be inherently related to their degree of differentiation. While these specific cell features were all capable of discriminating latent from active TB, irrespective of HIV status, HLA-DR expression showed the best performance for TB diagnosis [area-under-the-curve (AUC) = 0.92, 95% CI: 0.82-1.01, specificity: 82%, sensitivity: 84% for HIV- and AUC = 0.99, 95% CI: 0.98-1.01, specificity: 94%, sensitivity: 93% for HIV+]. In conclusion, these data support the idea that analysis of T cell phenotype can be diagnostically useful in TB.

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The data shown below were collected from the profiles of 9 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 18%
Student > Master 11 14%
Researcher 8 10%
Student > Postgraduate 8 10%
Student > Bachelor 6 8%
Other 14 18%
Unknown 18 23%
Readers by discipline Count As %
Immunology and Microbiology 17 22%
Medicine and Dentistry 14 18%
Biochemistry, Genetics and Molecular Biology 11 14%
Agricultural and Biological Sciences 9 11%
Nursing and Health Professions 1 1%
Other 6 8%
Unknown 21 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 01 May 2018.
All research outputs
#4,544,586
of 25,411,814 outputs
Outputs from Frontiers in immunology
#4,854
of 31,614 outputs
Outputs of similar age
#73,061
of 327,607 outputs
Outputs of similar age from Frontiers in immunology
#80
of 446 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 31,614 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done well, scoring higher than 84% 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 327,607 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 77% of its contemporaries.
We're also able to compare this research output to 446 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.