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Single-cell mass cytometry reveals distinct populations of brain myeloid cells in mouse neuroinflammation and neurodegeneration models

Overview of attention for article published in Nature Neuroscience, March 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
69 tweeters
patent
3 patents
facebook
1 Facebook page

Citations

dimensions_citation
231 Dimensions

Readers on

mendeley
469 Mendeley
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Title
Single-cell mass cytometry reveals distinct populations of brain myeloid cells in mouse neuroinflammation and neurodegeneration models
Published in
Nature Neuroscience, March 2018
DOI 10.1038/s41593-018-0100-x
Pubmed ID
Authors

Bahareh Ajami, Nikolay Samusik, Peter Wieghofer, Peggy P. Ho, Andrea Crotti, Zach Bjornson, Marco Prinz, Wendy J. Fantl, Garry P. Nolan, Lawrence Steinman

Abstract

Neuroinflammation and neurodegeneration may represent two poles of brain pathology. Brain myeloid cells, particularly microglia, play key roles in these conditions. We employed single-cell mass cytometry (CyTOF) to compare myeloid cell populations in the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis, the R6/2 model of Huntington's disease (HD) and the mutant superoxide dismutase 1 (mSOD1) model of amyotrophic lateral sclerosis (ALS). We identified three myeloid cell populations exclusive to the CNS and present in each disease model. Blood-derived monocytes comprised five populations and migrated to the brain in EAE, but not in HD and ALS models. Single-cell analysis resolved differences in signaling and cytokine production within similar myeloid populations in EAE compared to HD and ALS models. Moreover, these analyses highlighted α5 integrin on myeloid cells as a potential therapeutic target for neuroinflammation. Together, these findings illustrate how neuropathology may differ between inflammatory and degenerative brain disease.

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 69 tweeters 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 469 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 469 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 102 22%
Researcher 82 17%
Student > Master 57 12%
Student > Bachelor 40 9%
Other 21 4%
Other 71 15%
Unknown 96 20%
Readers by discipline Count As %
Neuroscience 116 25%
Biochemistry, Genetics and Molecular Biology 65 14%
Agricultural and Biological Sciences 57 12%
Immunology and Microbiology 49 10%
Medicine and Dentistry 33 7%
Other 49 10%
Unknown 100 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 69. 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 08 September 2023.
All research outputs
#591,015
of 24,506,807 outputs
Outputs from Nature Neuroscience
#1,092
of 5,463 outputs
Outputs of similar age
#14,068
of 336,526 outputs
Outputs of similar age from Nature Neuroscience
#28
of 71 outputs
Altmetric has tracked 24,506,807 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,463 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.7. This one has done well, scoring higher than 80% 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 336,526 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.