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Predicting physiologically-relevant oxygen concentrations in precision-cut liver slices using mathematical modelling

Chidlow, SJ, Randle, LE and Kelly, RA (2022) Predicting physiologically-relevant oxygen concentrations in precision-cut liver slices using mathematical modelling. PLOS ONE, 17 (11).

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Precision cut liver slices represent an encouraging ex vivo method to understand the pathogenesis of liver disease alongside drug induced liver injury. Despite being more physiologically relevant compared to in vitro models, precision cut liver slices are limited by the availability of healthy human tissue and experimental variability. Internal oxygen concentration and media composition govern the longevity and viability of the slices during the culture period and as such, a variety of approaches have been taken to maximise the appropriateness of the internal oxygen concentrations across the slice. The aim of this study was to predict whether it is possible to generate a physiologically relevant oxygen gradient of 35-65mmHg across a precision cut liver slice using mathematical modelling. Simulations explore how the internal oxygen concentration changes as a function of the diameter of the slice, the position inside the well and the external incubator oxygen concentration. The model predicts that the desired oxygen gradient may be achieved using a 5mm diameter slice at atmospheric oxygen concentrations, provided that the slice is positioned at a certain height within the well of a 12-well plate.

Item Type: Article
Uncontrolled Keywords: General Science & Technology
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Computer software
R Medicine > RM Therapeutics. Pharmacology
Divisions: Computer Science & Mathematics
Pharmacy & Biomolecular Sciences
Publisher: Public Library of Science (PLoS)
SWORD Depositor: A Symplectic
Date Deposited: 03 Nov 2022 11:57
Last Modified: 03 Nov 2022 12:00
DOI or Identification number: 10.1371/journal.pone.0275788
URI: https://researchonline.ljmu.ac.uk/id/eprint/18007

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