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Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices
Chronic kidney disease affects millions of people around the globe and many patients rely on hemodialysis (HD) to survive. HD is associated with undesired life-threatening side effects that are linked to membrane biocompatibility and clinical operating conditions. The present study develops a mathem...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8630185/ https://www.ncbi.nlm.nih.gov/pubmed/34845257 http://dx.doi.org/10.1038/s41598-021-01660-1 |
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author | Abdelrasoul, Amira Westphalen, Heloisa Saadati, Shaghayegh Shoker, Ahmed |
author_facet | Abdelrasoul, Amira Westphalen, Heloisa Saadati, Shaghayegh Shoker, Ahmed |
author_sort | Abdelrasoul, Amira |
collection | PubMed |
description | Chronic kidney disease affects millions of people around the globe and many patients rely on hemodialysis (HD) to survive. HD is associated with undesired life-threatening side effects that are linked to membrane biocompatibility and clinical operating conditions. The present study develops a mathematical model to predict the inflammatory biomarkers released in HD patients based on membrane morphology, chemistry, and interaction affinity. Based on the morphological characteristics of two clinical-grade HD membrane modules (CTA and PAES-PVP) commonly used in Canadian hospitals, a molecular docking study, and the release of inflammatory cytokines during HD and in vitro incubation experiments, we develop five sets of equations that describe the concentration of eight biomarkers (serpin/antithrombin-III, properdin, C5a, 1L-1α, 1L-1β, C5b-9, IL6, vWF). The equations developed are functions of membrane properties (pore size, roughness, chemical composition, affinity to fibrinogen, and surface charge) and HD operating conditions (blood flow rate, Qb, and treatment time, t). We expand our model based on available clinical data and increase its range of applicability in terms of flow rate and treatment time. We also modify the original equations to expand their range of applicability in terms of membrane materials, allowing the prediction and validation of the inflammatory response of several clinical and synthesized membrane materials. Our affinity-based model solely relies on theoretical values of molecular docking, which can significantly reduce the experimental load related to the development of more biocompatible materials. Our model predictions agree with experimental clinical data and can guide the development of novel materials and support evidence-based membrane synthesis of HD membranes, reducing the need for trial-and-error approaches. |
format | Online Article Text |
id | pubmed-8630185 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86301852021-12-01 Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices Abdelrasoul, Amira Westphalen, Heloisa Saadati, Shaghayegh Shoker, Ahmed Sci Rep Article Chronic kidney disease affects millions of people around the globe and many patients rely on hemodialysis (HD) to survive. HD is associated with undesired life-threatening side effects that are linked to membrane biocompatibility and clinical operating conditions. The present study develops a mathematical model to predict the inflammatory biomarkers released in HD patients based on membrane morphology, chemistry, and interaction affinity. Based on the morphological characteristics of two clinical-grade HD membrane modules (CTA and PAES-PVP) commonly used in Canadian hospitals, a molecular docking study, and the release of inflammatory cytokines during HD and in vitro incubation experiments, we develop five sets of equations that describe the concentration of eight biomarkers (serpin/antithrombin-III, properdin, C5a, 1L-1α, 1L-1β, C5b-9, IL6, vWF). The equations developed are functions of membrane properties (pore size, roughness, chemical composition, affinity to fibrinogen, and surface charge) and HD operating conditions (blood flow rate, Qb, and treatment time, t). We expand our model based on available clinical data and increase its range of applicability in terms of flow rate and treatment time. We also modify the original equations to expand their range of applicability in terms of membrane materials, allowing the prediction and validation of the inflammatory response of several clinical and synthesized membrane materials. Our affinity-based model solely relies on theoretical values of molecular docking, which can significantly reduce the experimental load related to the development of more biocompatible materials. Our model predictions agree with experimental clinical data and can guide the development of novel materials and support evidence-based membrane synthesis of HD membranes, reducing the need for trial-and-error approaches. Nature Publishing Group UK 2021-11-29 /pmc/articles/PMC8630185/ /pubmed/34845257 http://dx.doi.org/10.1038/s41598-021-01660-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Abdelrasoul, Amira Westphalen, Heloisa Saadati, Shaghayegh Shoker, Ahmed Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices |
title | Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices |
title_full | Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices |
title_fullStr | Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices |
title_full_unstemmed | Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices |
title_short | Hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices |
title_sort | hemodialysis biocompatibility mathematical models to predict the inflammatory biomarkers released in dialysis patients based on hemodialysis membrane characteristics and clinical practices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8630185/ https://www.ncbi.nlm.nih.gov/pubmed/34845257 http://dx.doi.org/10.1038/s41598-021-01660-1 |
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