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preprint
posted on 2025-01-09, 19:12authored byArthur ShermanArthur Sherman, Joon Ha, Stephanie ChungStephanie Chung, Max Springer, Joon Young Kim, Phil Chen, Melanie Cree-Green, Cecilia Diniz Behn, Anne E. Sumner, Silva Arslanian, Aaryan Chhabra
<p dir="ltr">This is supplemental material for the article,</p><p dir="ltr">"Estimating Insulin Sensitivity and Beta-Cell Function from the Oral Glucose Tolerance Test: Validation of a new Insulin Sensitivity and Secretion (ISS) Model", Am. J. Physiol.</p><p dir="ltr">doi: https://doi.org/10.1152/ajpendo.00189.2023</p><p dir="ltr">PubMed: https://pubmed.ncbi.nlm.nih.gov/38054972/</p><p dir="ltr">Early preprint at bioRxiv, doi: https://doi.org/10.1101/2023.06.16.545377</p><p dir="ltr">Items:</p><p><br></p><p dir="ltr">Supplemental Table S1</p><p dir="ltr">Supplemental Figures S1 - S13</p><p dir="ltr">File S1 Supplemental Equations</p><p dir="ltr">File S2 Matlab Fitting Code</p><p dir="ltr">File S3 Python Fitting Code</p><p dir="ltr">File S4 Supplemental Methods</p><p dir="ltr">For File S2, run the Matlab script OGTT_fit.m, which calls OGTT_cost_function_universal.m and GI_ode_universal.m.</p><p dir="ltr">It will read in the synthetic data Synthetic_Data.xlsx and output the fits to Synthetic_Fits.xlsx. The included file Expected_Synthetic_Fits.xlsx should agree with your output.</p><p dir="ltr">The parameters are set to those used in the paper, but can be customized as desired.</p><p dir="ltr">For File S3, consult the readme.md file contained in the zip file.</p><p><br></p><p><br></p><p><br></p>
Funding
NIDDK Z01DK075137
2022H1D3A2A01063552
DGE 1840340
NIH R01 HD27503
NIH K24 HD/DK01357
University of Pittsburgh Clinical and Translational Science Institute
National Center for Advancing Translational Sciences