{"title":"灰质中纳米粒子扩散的数值模拟研究","authors":"Peiqian Chen , Bing Dong , Weiwu Yao","doi":"10.1016/j.csbj.2024.06.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><p>Nanomedicine-based approaches have shown great potential in the treatment of central nervous system diseases. However, the fate of nanoparticles (NPs) within the brain parenchyma has not received much attention. The complexity of the microstructure of the brain and the invisibility of NPs make it difficult to study NP transport within the grey matter. Moreover, regulation of NP delivery is not fully understood.</p></div><div><h3>Methods</h3><p>2D interstitial system (ISS) models reflecting actual extracellular space (ECS) were constructed. A particle tracing model was used to simulate the diffusion of the NPs. The effect of NP size on NP diffusion was studied using numerical simulations. The diffusion of charged NPs was explored by comparing experimental and numerical simulation data, and the effect of cell membrane potential on the diffusion of charged NPs was further studied.</p></div><div><h3>Results</h3><p>The model was verified using previously published experimental data. Small NPs could diffuse efficiently into the ISS. The diffusion of charged NPs was hindered in the ISS. Changes in cell membrane potential had little effect on NP diffusion.</p></div><div><h3>Conclusion</h3><p>This study constructed 2D brain ISS models that reflected the actual ECS and simulated the diffusion of NPs within it. The study found that uncharged small NPs could effectively diffuse within the ISS and that the cell membrane potential had a limited effect on the diffusion of charged NPs. The model and findings of this study can aid the design of nanomedicines and nanocarriers for the diagnosis and treatment of brain diseases.</p></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2001037024001995/pdfft?md5=e0a2801bf26e2243ba4d4d7cda644491&pid=1-s2.0-S2001037024001995-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Numerical simulation study of nanoparticle diffusion in gray matter\",\"authors\":\"Peiqian Chen , Bing Dong , Weiwu Yao\",\"doi\":\"10.1016/j.csbj.2024.06.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><p>Nanomedicine-based approaches have shown great potential in the treatment of central nervous system diseases. However, the fate of nanoparticles (NPs) within the brain parenchyma has not received much attention. The complexity of the microstructure of the brain and the invisibility of NPs make it difficult to study NP transport within the grey matter. Moreover, regulation of NP delivery is not fully understood.</p></div><div><h3>Methods</h3><p>2D interstitial system (ISS) models reflecting actual extracellular space (ECS) were constructed. A particle tracing model was used to simulate the diffusion of the NPs. The effect of NP size on NP diffusion was studied using numerical simulations. The diffusion of charged NPs was explored by comparing experimental and numerical simulation data, and the effect of cell membrane potential on the diffusion of charged NPs was further studied.</p></div><div><h3>Results</h3><p>The model was verified using previously published experimental data. Small NPs could diffuse efficiently into the ISS. The diffusion of charged NPs was hindered in the ISS. Changes in cell membrane potential had little effect on NP diffusion.</p></div><div><h3>Conclusion</h3><p>This study constructed 2D brain ISS models that reflected the actual ECS and simulated the diffusion of NPs within it. The study found that uncharged small NPs could effectively diffuse within the ISS and that the cell membrane potential had a limited effect on the diffusion of charged NPs. The model and findings of this study can aid the design of nanomedicines and nanocarriers for the diagnosis and treatment of brain diseases.</p></div>\",\"PeriodicalId\":10715,\"journal\":{\"name\":\"Computational and structural biotechnology journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2001037024001995/pdfft?md5=e0a2801bf26e2243ba4d4d7cda644491&pid=1-s2.0-S2001037024001995-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational and structural biotechnology journal\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2001037024001995\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and structural biotechnology journal","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2001037024001995","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Numerical simulation study of nanoparticle diffusion in gray matter
Purpose
Nanomedicine-based approaches have shown great potential in the treatment of central nervous system diseases. However, the fate of nanoparticles (NPs) within the brain parenchyma has not received much attention. The complexity of the microstructure of the brain and the invisibility of NPs make it difficult to study NP transport within the grey matter. Moreover, regulation of NP delivery is not fully understood.
Methods
2D interstitial system (ISS) models reflecting actual extracellular space (ECS) were constructed. A particle tracing model was used to simulate the diffusion of the NPs. The effect of NP size on NP diffusion was studied using numerical simulations. The diffusion of charged NPs was explored by comparing experimental and numerical simulation data, and the effect of cell membrane potential on the diffusion of charged NPs was further studied.
Results
The model was verified using previously published experimental data. Small NPs could diffuse efficiently into the ISS. The diffusion of charged NPs was hindered in the ISS. Changes in cell membrane potential had little effect on NP diffusion.
Conclusion
This study constructed 2D brain ISS models that reflected the actual ECS and simulated the diffusion of NPs within it. The study found that uncharged small NPs could effectively diffuse within the ISS and that the cell membrane potential had a limited effect on the diffusion of charged NPs. The model and findings of this study can aid the design of nanomedicines and nanocarriers for the diagnosis and treatment of brain diseases.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology