Automated Quantitative Analysis of ex vivo Blood-Brain Barrier Permeability Using Intellesis Machine-Learning

Automated Quantitative Analysis of ex vivo Blood-Brain Barrier Permeability Using Intellesis Machine-Learning

BackgroundAn increase in blood brain barrier permeability commonly precedes neuro-inflammation and cognitive impairment in models of dementia. Common methods to estimate capillary permeability have potential confounders, or require laborious and subjective semi-manual analysis.New methodHere we used...

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Bibliographic Details
Main Authors: Michael Nesbit, John C. Mamo, Maimuna Majimbi, Virginie Lam, Ryusuke Takechi
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Neuroscience
Subjects:
blood-brain barrier
IgG extravasation
machine-learning
immunofluorescence
laminin-α4
quantitation
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.617221/full

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https://www.frontiersin.org/articles/10.3389/fnins.2021.617221/full

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