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A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers

Overview of attention for article published in Genome Biology, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)

Mentioned by

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6 X users
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2 Wikipedia pages
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1 research highlight platform

Citations

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36 Dimensions

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73 Mendeley
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1 CiteULike
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Title
A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers
Published in
Genome Biology, January 2018
DOI 10.1186/s13059-017-1385-x
Pubmed ID
Authors

Enrique Martin-Gayo, Michael B. Cole, Kellie E. Kolb, Zhengyu Ouyang, Jacqueline Cronin, Samuel W. Kazer, Jose Ordovas-Montanes, Mathias Lichterfeld, Bruce D. Walker, Nir Yosef, Alex K. Shalek, Xu G. Yu

Abstract

Human immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing to examine viral responses among the dendritic cells (DCs) of three elite controllers (ECs) of HIV-1 infection. To overcome the potentially confounding effects of donor-to-donor variability, we present a generally applicable computational framework for identifying reproducible patterns in gene expression across donors who share a unifying classification. Applying it, we discover a highly functional antiviral DC state in ECs whose fractional abundance after in vitro exposure to HIV-1 correlates with higher CD4+ T cell counts and lower HIV-1 viral loads, and that effectively primes polyfunctional T cell responses in vitro. By integrating information from existing genomic databases into our reproducibility-based analysis, we identify and validate select immunomodulators that increase the fractional abundance of this state in primary peripheral blood mononuclear cells from healthy individuals in vitro. Overall, our results demonstrate how single-cell approaches can reveal previously unappreciated, yet important, immune behaviors and empower rational frameworks for modulating systems-level immune responses that may prove therapeutically and prophylactically useful.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 73 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 22%
Researcher 9 12%
Student > Doctoral Student 7 10%
Student > Master 7 10%
Student > Bachelor 6 8%
Other 11 15%
Unknown 17 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 22%
Biochemistry, Genetics and Molecular Biology 9 12%
Immunology and Microbiology 9 12%
Medicine and Dentistry 7 10%
Computer Science 3 4%
Other 10 14%
Unknown 19 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 12 February 2021.
All research outputs
#5,167,753
of 25,382,440 outputs
Outputs from Genome Biology
#2,837
of 4,468 outputs
Outputs of similar age
#106,520
of 450,499 outputs
Outputs of similar age from Genome Biology
#39
of 47 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. 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 450,499 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 76% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.