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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