Evidence map›Paper›PMID 29725290›Full record

ArticleFrontiers in cellular neuroscience2018

Automated Morphological Analysis of Microglia After Stroke.

Steffanie Heindl, Benno Gesierich, Corinne Benakis, Gemma Llovera, Marco Duering, Arthur Liesz

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cellular neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 141 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
141citing papers in PubMed, 1 pooled it
10.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

141 citing papers in PubMed, 1 synthesis or guideline pooled it, 237 citations in OpenAlex.

  1. Pooled it
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  17. Injury to repair: Functions of microglia and monocyte-derived cells in ischemic stroke.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2025
    Review
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81 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Steffanie HeindlInstitute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Benno GesierichInstitute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Corinne BenakisInstitute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Gemma LloveraInstitute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Marco DueringInstitute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Arthur LieszInstitute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Ludwig-Maximilians-Universität München · DEMunich Cluster for Systems Neurology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.

Indexed as

image analysismicrogliamorphologyneuroinflammationstroke

Identifiers

PMID29725290
PMCPMC5917008
OpenAlexW2802616779

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.