Stochastic Biological System-of-Systems Modelling for iPSC Culture
Large-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension bioreactors, resulting in insufficient nutrient supply and extra metabolic waste build-up for the cells located at the c...
Gespeichert in:
Veröffentlicht in: | arXiv.org 2023-10 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Zheng, Hua Harcum, Sarah W Jinxiang Pei Xie, Wei |
description | Large-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension bioreactors, resulting in insufficient nutrient supply and extra metabolic waste build-up for the cells located at the core. Since subtle changes in micro-environment can lead to a heterogeneous cell population, a novel Biological System-of-Systems (Bio-SoS) framework is proposed to model cell-to-cell interactions, spatial and metabolic heterogeneity, and cell response to micro-environmental variation. Building on stochastic metabolic reaction network, aggregation kinetics, and reaction-diffusion mechanisms, the Bio-SoS model characterizes causal interdependencies at individual cell, aggregate, and cell population levels. It has a modular design that enables data integration and improves predictions for different monolayer and aggregate culture processes. In addition, a variance decomposition analysis is derived to quantify the impact of factors (i.e., aggregate size) on cell product health and quality heterogeneity. |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2820825613</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2820825613</sourcerecordid><originalsourceid>FETCH-proquest_journals_28208256133</originalsourceid><addsrcrecordid>eNqNikEKwjAQAIMgWLR_CHgOpBtbe25QvAhCvZfSpjUldjWbHPy9gj7A0wzMLFgCSmWi3AGsWEo0SSmh2EOeq4RVdcDu1lKwHa8sOhxt1zpevyiYu8BBfI34GXvjnJ1HPqDn9lJrrqML0ZsNWw6tI5P-uGbb4-GqT-Lh8RkNhWbC6OdPaqAEWUJeZEr9d70BsrY5nA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2820825613</pqid></control><display><type>article</type><title>Stochastic Biological System-of-Systems Modelling for iPSC Culture</title><source>Free E- Journals</source><creator>Zheng, Hua ; Harcum, Sarah W ; Jinxiang Pei ; Xie, Wei</creator><creatorcontrib>Zheng, Hua ; Harcum, Sarah W ; Jinxiang Pei ; Xie, Wei</creatorcontrib><description>Large-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension bioreactors, resulting in insufficient nutrient supply and extra metabolic waste build-up for the cells located at the core. Since subtle changes in micro-environment can lead to a heterogeneous cell population, a novel Biological System-of-Systems (Bio-SoS) framework is proposed to model cell-to-cell interactions, spatial and metabolic heterogeneity, and cell response to micro-environmental variation. Building on stochastic metabolic reaction network, aggregation kinetics, and reaction-diffusion mechanisms, the Bio-SoS model characterizes causal interdependencies at individual cell, aggregate, and cell population levels. It has a modular design that enables data integration and improves predictions for different monolayer and aggregate culture processes. In addition, a variance decomposition analysis is derived to quantify the impact of factors (i.e., aggregate size) on cell product health and quality heterogeneity.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Biological models (mathematics) ; Bioreactors ; Heterogeneity ; Metabolic wastes ; Metabolism ; Stem cells ; System of systems</subject><ispartof>arXiv.org, 2023-10</ispartof><rights>2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>778,782</link.rule.ids></links><search><creatorcontrib>Zheng, Hua</creatorcontrib><creatorcontrib>Harcum, Sarah W</creatorcontrib><creatorcontrib>Jinxiang Pei</creatorcontrib><creatorcontrib>Xie, Wei</creatorcontrib><title>Stochastic Biological System-of-Systems Modelling for iPSC Culture</title><title>arXiv.org</title><description>Large-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension bioreactors, resulting in insufficient nutrient supply and extra metabolic waste build-up for the cells located at the core. Since subtle changes in micro-environment can lead to a heterogeneous cell population, a novel Biological System-of-Systems (Bio-SoS) framework is proposed to model cell-to-cell interactions, spatial and metabolic heterogeneity, and cell response to micro-environmental variation. Building on stochastic metabolic reaction network, aggregation kinetics, and reaction-diffusion mechanisms, the Bio-SoS model characterizes causal interdependencies at individual cell, aggregate, and cell population levels. It has a modular design that enables data integration and improves predictions for different monolayer and aggregate culture processes. In addition, a variance decomposition analysis is derived to quantify the impact of factors (i.e., aggregate size) on cell product health and quality heterogeneity.</description><subject>Biological models (mathematics)</subject><subject>Bioreactors</subject><subject>Heterogeneity</subject><subject>Metabolic wastes</subject><subject>Metabolism</subject><subject>Stem cells</subject><subject>System of systems</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNikEKwjAQAIMgWLR_CHgOpBtbe25QvAhCvZfSpjUldjWbHPy9gj7A0wzMLFgCSmWi3AGsWEo0SSmh2EOeq4RVdcDu1lKwHa8sOhxt1zpevyiYu8BBfI34GXvjnJ1HPqDn9lJrrqML0ZsNWw6tI5P-uGbb4-GqT-Lh8RkNhWbC6OdPaqAEWUJeZEr9d70BsrY5nA</recordid><startdate>20231011</startdate><enddate>20231011</enddate><creator>Zheng, Hua</creator><creator>Harcum, Sarah W</creator><creator>Jinxiang Pei</creator><creator>Xie, Wei</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20231011</creationdate><title>Stochastic Biological System-of-Systems Modelling for iPSC Culture</title><author>Zheng, Hua ; Harcum, Sarah W ; Jinxiang Pei ; Xie, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_28208256133</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Biological models (mathematics)</topic><topic>Bioreactors</topic><topic>Heterogeneity</topic><topic>Metabolic wastes</topic><topic>Metabolism</topic><topic>Stem cells</topic><topic>System of systems</topic><toplevel>online_resources</toplevel><creatorcontrib>Zheng, Hua</creatorcontrib><creatorcontrib>Harcum, Sarah W</creatorcontrib><creatorcontrib>Jinxiang Pei</creatorcontrib><creatorcontrib>Xie, Wei</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zheng, Hua</au><au>Harcum, Sarah W</au><au>Jinxiang Pei</au><au>Xie, Wei</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Stochastic Biological System-of-Systems Modelling for iPSC Culture</atitle><jtitle>arXiv.org</jtitle><date>2023-10-11</date><risdate>2023</risdate><eissn>2331-8422</eissn><abstract>Large-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension bioreactors, resulting in insufficient nutrient supply and extra metabolic waste build-up for the cells located at the core. Since subtle changes in micro-environment can lead to a heterogeneous cell population, a novel Biological System-of-Systems (Bio-SoS) framework is proposed to model cell-to-cell interactions, spatial and metabolic heterogeneity, and cell response to micro-environmental variation. Building on stochastic metabolic reaction network, aggregation kinetics, and reaction-diffusion mechanisms, the Bio-SoS model characterizes causal interdependencies at individual cell, aggregate, and cell population levels. It has a modular design that enables data integration and improves predictions for different monolayer and aggregate culture processes. In addition, a variance decomposition analysis is derived to quantify the impact of factors (i.e., aggregate size) on cell product health and quality heterogeneity.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2023-10 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2820825613 |
source | Free E- Journals |
subjects | Biological models (mathematics) Bioreactors Heterogeneity Metabolic wastes Metabolism Stem cells System of systems |
title | Stochastic Biological System-of-Systems Modelling for iPSC Culture |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T09%3A04%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Stochastic%20Biological%20System-of-Systems%20Modelling%20for%20iPSC%20Culture&rft.jtitle=arXiv.org&rft.au=Zheng,%20Hua&rft.date=2023-10-11&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2820825613%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2820825613&rft_id=info:pmid/&rfr_iscdi=true |