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Mendeley readers
Attention Score in Context
| Title |
Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis
|
|---|---|
| Published in |
Frontiers in Cellular Neuroscience, August 2017
|
| DOI | 10.3389/fncel.2017.00235 |
| Pubmed ID | |
| Authors |
María del Mar Fernández-Arjona, Jesús M. Grondona, Pablo Granados-Durán, Pedro Fernández-Llebrez, María D. López-Ávalos |
| Abstract |
It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor. |
X Demographics
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 11% |
| France | 1 | 11% |
| Spain | 1 | 11% |
| Chile | 1 | 11% |
| United States | 1 | 11% |
| Switzerland | 1 | 11% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Scientists | 3 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 482 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 482 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 90 | 19% |
| Student > Bachelor | 69 | 14% |
| Student > Master | 61 | 13% |
| Researcher | 53 | 11% |
| Student > Doctoral Student | 33 | 7% |
| Other | 49 | 10% |
| Unknown | 127 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 139 | 29% |
| Biochemistry, Genetics and Molecular Biology | 72 | 15% |
| Agricultural and Biological Sciences | 41 | 9% |
| Medicine and Dentistry | 26 | 5% |
| Immunology and Microbiology | 12 | 2% |
| Other | 41 | 9% |
| Unknown | 151 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 06 June 2021.
All research outputs
#2,474,869
of 25,375,376 outputs
Outputs from Frontiers in Cellular Neuroscience
#359
of 4,689 outputs
Outputs of similar age
#44,880
of 323,988 outputs
Outputs of similar age from Frontiers in Cellular Neuroscience
#9
of 121 outputs
Altmetric has tracked 25,375,376 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,689 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done particularly well, scoring higher than 92% 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 323,988 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 86% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.