The fractal viewpoint of tumors and nanoparticles.

Journal article


Alexiou, A., Tsagkaris, C., Chatzichronis, S., Koulouris, A., Haranas, I., Gkigkitzis, I., Zouganelis, G., Mukerjee, N., Maitr, S., Jha, N. K., Batiha, G. and Amjad, M. 2022. The fractal viewpoint of tumors and nanoparticles. Current Medicinal Chemistry. 30 (3), pp. 356 - 370. https://doi.org/10.2174/0929867329666220801152347
AuthorsAlexiou, A., Tsagkaris, C., Chatzichronis, S., Koulouris, A., Haranas, I., Gkigkitzis, I., Zouganelis, G., Mukerjee, N., Maitr, S., Jha, N. K., Batiha, G. and Amjad, M.
Abstract

Even though the promising therapies against cancer are rapidly improved, the oncology patients population has seen exponential growth, placing cancer in 5th place among the ten deadliest diseases. Efficient drug delivery systems must overcome multiple barriers and maximize drug delivery to the target tumors, limiting the side effects simultaneously. Since the first observation of the quantum tunneling phenomenon, many multidisciplinary studies have offered quantum-inspired solutions to optimized tumor mapping and efficient nanodrug design. The property of a wave function to propagate through a potential barrier offer the capability of obtaining 3D surface profiles using imaging of individual atoms on the surface of a material. The application of quantum tunneling on a scanning tunneling microscope offers an exact surface roughness mapping of tumors and pharmaceutical particles. Critical elements to cancer nanotherapeutics apply the fractal theory and calculate the fractal dimension for efficient tumor surface imaging at the atomic level. This review study presents the latest biological approaches to cancer management based on fractal geometry.

KeywordsBox-Counting Algorithm; Cancer; Chaos Theory; Drug Delivery; Fractal Dimension; Fractality; Imaging Data; Lacunarity; Nanoparticles; Pharmacokinetics; Quantum Tunneling; Scanning Tunneling Microscope; Succolarity
Year2022
JournalCurrent Medicinal Chemistry
Journal citation30 (3), pp. 356 - 370
PublisherBentham Science
ISSN1875-533X
Digital Object Identifier (DOI)https://doi.org/10.2174/0929867329666220801152347
Web address (URL)https://www.eurekaselect.com/article/125260
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Output statusPublished
Publication dates
Online30 Sep 2022
Publication process dates
Deposited23 Nov 2022
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