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Continuous Immune Cell Differentiation Inferred From Single-Cell Measurements Following Allogeneic Stem Cell Transplantation

Overview of attention for article published in Frontiers in Molecular Biosciences, September 2018
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
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Title
Continuous Immune Cell Differentiation Inferred From Single-Cell Measurements Following Allogeneic Stem Cell Transplantation
Published in
Frontiers in Molecular Biosciences, September 2018
DOI 10.3389/fmolb.2018.00081
Pubmed ID
Authors

Yang Chen, Tadepally Lakshmikanth, Axel Olin, Jaromir Mikes, Mats Remberger, Petter Brodin

Abstract

The process of immune system regeneration after allogeneic stem cell transplantation is slow, complex, and insufficiently understood. An entire immune system with all of its cell populations must regenerate from infused donor hematopoietic stem cells over the course of weeks and months post-transplantation. Both innate and adaptive arms of the immune system differ in their capacity and speed to reconstitiute in the recipient, which contributes to inadequacy in global immunity during the delayed reconstitution period. Systems-level analyses of immune systems in human patients have been made possible by high-throughput and high-dimensional, state-of-the-art, single-cell methodologies such as mass cytometry. Mass cytometry has revolutionized our ability to comprehensively profile all immune cell populations simultaneously in blood or tissue samples, providing signatures of differentially regulated cells in a range of clinical conditions. Such kind of systems immunology analyses promise not only for more accurate descriptions of variation between patients but also within individual patients over time, inter-dependencies between cell populations and the inference of developmental trajectories for specific cell populations. Here, we took advantage of a recently performed longitudinal mass cytometry analysis in 26 patients with hematological malignancies followed during the first 12 months following allogeneic stem cell transplantation. We present a proof-of-principle analysis to understand the evolution of individual immune cell populations. By applying non-linear dimensionality reduction and feauture extraction algorithms, we infer trajectories for individual immune cell populations, and map continuous marker expression changes occuring during immune cell regeneration that add novel information about this developmental process.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 32%
Student > Ph. D. Student 5 18%
Other 4 14%
Student > Postgraduate 2 7%
Student > Master 2 7%
Other 3 11%
Unknown 3 11%
Readers by discipline Count As %
Immunology and Microbiology 8 29%
Biochemistry, Genetics and Molecular Biology 6 21%
Agricultural and Biological Sciences 6 21%
Medicine and Dentistry 2 7%
Computer Science 1 4%
Other 1 4%
Unknown 4 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 October 2018.
All research outputs
#13,048,273
of 23,103,436 outputs
Outputs from Frontiers in Molecular Biosciences
#801
of 3,914 outputs
Outputs of similar age
#159,792
of 337,668 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#8
of 17 outputs
Altmetric has tracked 23,103,436 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,914 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 79% 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 337,668 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 52% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.