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Integrating Non-human Primate, Human, and Mathematical Studies to Determine the Influence of BCG Timing on H56 Vaccine Outcomes

Overview of attention for article published in Frontiers in Microbiology, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

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1 blog
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6 X users

Citations

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11 Dimensions

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38 Mendeley
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Title
Integrating Non-human Primate, Human, and Mathematical Studies to Determine the Influence of BCG Timing on H56 Vaccine Outcomes
Published in
Frontiers in Microbiology, August 2018
DOI 10.3389/fmicb.2018.01734
Pubmed ID
Authors

Louis R. Joslyn, Elsje Pienaar, Robert M. DiFazio, Sara Suliman, Benjamin M. Kagina, JoAnne L. Flynn, Thomas J. Scriba, Jennifer J. Linderman, Denise E. Kirschner

Abstract

Tuberculosis (TB) is the leading cause of death by an infectious agent, and developing an effective vaccine is an important component of the WHO's EndTB Strategy. Non-human primate (NHP) models of vaccination are crucial to TB vaccine development and have informed design of subsequent human trials. However, challenges emerge when translating results from animal models to human applications, and connecting post-vaccination immunological measurements to infection outcomes. The H56:IC31 vaccine is a candidate currently in phase I/IIa trials. H56 is a subunit vaccine that is comprised of 3 mycobacterial antigens: ESAT6, Ag85B, and Rv2660, formulated in IC31 adjuvant. H56, as a boost to Bacillus Calmette-Guérin (BCG, the TB vaccine that is currently used in most countries world-wide) demonstrates improved protection (compared to BCG alone) in mouse and NHP models of TB, and the first human study of H56 reported strong antigen-specific T cell responses to the vaccine. We integrated NHP and human data with mathematical modeling approaches to improve our understanding of NHP and human response to vaccine. We use a mathematical model to describe T-cell priming, proliferation, and differentiation in lymph nodes and blood, and calibrate the model to NHP and human blood data. Using the model, we demonstrate the impact of BCG timing on H56 vaccination response and reveal a general immunogenic response to H56 following BCG prime. Further, we use uncertainty and sensitivity analyses to isolate mechanisms driving differences in vaccination response observed between NHP and human datasets. This study highlights the power of a systems biology approach: integration of multiple modalities to better understand a complex biological system.

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Master 4 11%
Student > Bachelor 4 11%
Student > Ph. D. Student 2 5%
Student > Doctoral Student 2 5%
Other 3 8%
Unknown 15 39%
Readers by discipline Count As %
Immunology and Microbiology 3 8%
Biochemistry, Genetics and Molecular Biology 2 5%
Mathematics 2 5%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Nursing and Health Professions 2 5%
Other 9 24%
Unknown 18 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 09 November 2020.
All research outputs
#2,764,291
of 23,306,612 outputs
Outputs from Frontiers in Microbiology
#2,372
of 25,611 outputs
Outputs of similar age
#57,434
of 333,778 outputs
Outputs of similar age from Frontiers in Microbiology
#112
of 739 outputs
Altmetric has tracked 23,306,612 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 25,611 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 particularly well, scoring higher than 90% 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 333,778 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 82% of its contemporaries.
We're also able to compare this research output to 739 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.