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Quantifying the impact of tissue metabolism on solute transport in feto-placental microvascular networks
Version 2 2019-05-17, 18:06
Version 1 2019-05-17, 13:12
dataset
posted on 2019-05-17, 18:06 authored by Alexander ErlichAlexander Erlich, Gareth A. Nye, Paul Brownbill, Oliver E. Jensen, Igor ChernyavskyIgor ChernyavskyThe raw geometric data which we use is given as STL files; the capillary surfaces surfaces end in "_Vasculature.stl" (four files) and villous surfaces end in "_Villi.stl" (four files). The geometries can be previewed in 3D by clicking on the file names.
specimen3_FL_stripped.mph & specimen3_DL_stripped.mph: Simulations for calculating flow-limited and diffusion-limited metabolic scale functions G & F, respectively. This underlies Figs. 1, 2, 3 and 7. The mesh has approx. 19.7mio tetrahedral elements and is particularly well resolved at and near the villous surface to ensure that boundary layers for strong metabolism are resolved. Each simulation (to solve for solute in metabolising tissue) ran for approximately 10h. The meshing process itself ran for several hours. We used a powerful computer (128 GB RAM, 16 core CPU). The solutions and meshes were stripped from the Comsol files to comply with figshare's 5GB file size limitation.
specimen3_fully_coupled.mph: Simulations for calculating fully coupled problem with linear uptake kinetics, which underlies Fig. 2 (dots). The mesh has approximately 4.1mio tetrahedral elements.
*.nb and *.xlsx: Codes and data needed to Figures 2, 3, 4 and 7. The *.nb files were created in Mathematica 11.0.1.0, relying on the numerical data contained in the Excel (*.xlsx) files which must be in the same folder as the *.nb files. To reproduce the figures, open a Mathematica file and then go to Evaluation -> Evaluate notebook, which will run all codes automatically and assemble all figures/subfigures. When switching between *.nb files, make sure to either close Mathematica or go to Evaluation -> Quit Kernel -> Local.
Fig6_ex-vivo_uptake_fitting.zip contains a MATLAB .m script (tested on ver. R2018a) and the associated ex-vivo pO2 datasets in a tab-separated .csv. After extracting both files into the same location, run "uptake_fit.m" to estimate the tissue metabolic parameters and reproduce Figure 6.
