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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Open-Source System for Real Time Functional Assessment of In-Vitro Filtration Barriers

Authors: Tess Fallon; Merve Zuvin; Alan D. Stern; Nanditha Anandakrishnan; Ilse S. Daehn; Evren U. Azeloglu;

Open-Source System for Real Time Functional Assessment of In-Vitro Filtration Barriers

Abstract

Microphysiological systems that incorporate synthetic or natural membranes with human cells mimic the human kidney, and they can readily be used to study key cell biological processes as well as drug effects and interactions. We present an affordable, open-source platform for the real-time monitoring of functional filtration status in engineered microphysiological systems. Using readily available components, our assay can linearly detect concentrations of two target molecules, FITC-labeled inulin and Texas Red-labeled human serum albumin, within clinically relevant ranges, and can be easily modified to integrate with different target molecules of different sizes and tags. We show that the platform enables real-time tracking of size-dependent diffusion with minimal fluid volume loss and without manual extraction of media, making it suitable for continuous operational monitoring of filtration status of microphysiological systems. The platform’s affordability and integrability with microphysiological systems make it ideal for many precision medicine applications, including evaluation of drug nephrotoxicity assessment and other forms of drug discovery applications.

Dataset includes raw intensity values and images in .TIFF format. Code can be found at: https://github.com/AzelogluLab/Sensor/

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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