Toward Predicting Nanoparticle Distribution in Heterogeneous Tumor Tissues
Nanobio interaction studies have generated a significant amount of data. An important next step is to organize the data and design computational techniques to analyze the nanobio interactions. Here we developed a computational technique to correlate the nanoparticle spatial distribution within heter...
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Veröffentlicht in: | Nano letters 2023-08, Vol.23 (15), p.7197-7205 |
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Hauptverfasser: | , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | Nanobio interaction studies have generated a significant amount of data. An important next step is to organize the data and design computational techniques to analyze the nanobio interactions. Here we developed a computational technique to correlate the nanoparticle spatial distribution within heterogeneous solid tumors. This approach led to greater than 88% predictive accuracy of nanoparticle location within a tumor tissue. This proof-of-concept study shows that tumor heterogeneity might be defined computationally by the patterns of biological structures within the tissue, enabling the identification of tumor patterns for nanoparticle accumulation. |
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ISSN: | 1530-6984 1530-6992 |
DOI: | 10.1021/acs.nanolett.3c02186 |