Cargando…
Understanding nano-engineered particle–cell interactions: biological insights from mathematical models
Understanding the interactions between nano-engineered particles and cells is necessary for the rational design of particles for therapeutic, diagnostic and imaging purposes. In particular, the informed design of particles relies on the quantification of the relationship between the physicochemical...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
RSC
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417320/ https://www.ncbi.nlm.nih.gov/pubmed/36133772 http://dx.doi.org/10.1039/d0na00774a |
_version_ | 1784776686562181120 |
---|---|
author | Johnston, Stuart T. Faria, Matthew Crampin, Edmund J. |
author_facet | Johnston, Stuart T. Faria, Matthew Crampin, Edmund J. |
author_sort | Johnston, Stuart T. |
collection | PubMed |
description | Understanding the interactions between nano-engineered particles and cells is necessary for the rational design of particles for therapeutic, diagnostic and imaging purposes. In particular, the informed design of particles relies on the quantification of the relationship between the physicochemical properties of the particles and the rate at which cells interact with, and subsequently internalise, particles. Quantitative models, both mathematical and computational, provide a powerful tool for elucidating this relationship, as well as for understanding the mechanisms governing the intertwined processes of interaction and internalisation. Here we review the different types of mathematical and computational models that have been used to examine particle–cell interactions and particle internalisation. We detail the mathematical methodology for each type of model, the benefits and limitations associated with the different types of models, and highlight the advances in understanding gleaned from the application of these models to experimental observations of particle internalisation. We discuss the recent proposal and ongoing community adoption of standardised experimental reporting, and how this adoption is an important step toward unlocking the full potential of modelling approaches. Finally, we consider future directions in quantitative models of particle–cell interactions and highlight the need for hybrid experimental and theoretical investigations to address hitherto unanswered questions. |
format | Online Article Text |
id | pubmed-9417320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | RSC |
record_format | MEDLINE/PubMed |
spelling | pubmed-94173202022-09-20 Understanding nano-engineered particle–cell interactions: biological insights from mathematical models Johnston, Stuart T. Faria, Matthew Crampin, Edmund J. Nanoscale Adv Chemistry Understanding the interactions between nano-engineered particles and cells is necessary for the rational design of particles for therapeutic, diagnostic and imaging purposes. In particular, the informed design of particles relies on the quantification of the relationship between the physicochemical properties of the particles and the rate at which cells interact with, and subsequently internalise, particles. Quantitative models, both mathematical and computational, provide a powerful tool for elucidating this relationship, as well as for understanding the mechanisms governing the intertwined processes of interaction and internalisation. Here we review the different types of mathematical and computational models that have been used to examine particle–cell interactions and particle internalisation. We detail the mathematical methodology for each type of model, the benefits and limitations associated with the different types of models, and highlight the advances in understanding gleaned from the application of these models to experimental observations of particle internalisation. We discuss the recent proposal and ongoing community adoption of standardised experimental reporting, and how this adoption is an important step toward unlocking the full potential of modelling approaches. Finally, we consider future directions in quantitative models of particle–cell interactions and highlight the need for hybrid experimental and theoretical investigations to address hitherto unanswered questions. RSC 2021-03-09 /pmc/articles/PMC9417320/ /pubmed/36133772 http://dx.doi.org/10.1039/d0na00774a Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Johnston, Stuart T. Faria, Matthew Crampin, Edmund J. Understanding nano-engineered particle–cell interactions: biological insights from mathematical models |
title | Understanding nano-engineered particle–cell interactions: biological insights from mathematical models |
title_full | Understanding nano-engineered particle–cell interactions: biological insights from mathematical models |
title_fullStr | Understanding nano-engineered particle–cell interactions: biological insights from mathematical models |
title_full_unstemmed | Understanding nano-engineered particle–cell interactions: biological insights from mathematical models |
title_short | Understanding nano-engineered particle–cell interactions: biological insights from mathematical models |
title_sort | understanding nano-engineered particle–cell interactions: biological insights from mathematical models |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417320/ https://www.ncbi.nlm.nih.gov/pubmed/36133772 http://dx.doi.org/10.1039/d0na00774a |
work_keys_str_mv | AT johnstonstuartt understandingnanoengineeredparticlecellinteractionsbiologicalinsightsfrommathematicalmodels AT fariamatthew understandingnanoengineeredparticlecellinteractionsbiologicalinsightsfrommathematicalmodels AT crampinedmundj understandingnanoengineeredparticlecellinteractionsbiologicalinsightsfrommathematicalmodels |