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International Journal for Multiscale Computational Engineering

年間 6 号発行

ISSN 印刷: 1543-1649

ISSN オンライン: 1940-4352

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.4 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.3 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 2.2 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00034 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.46 SJR: 0.333 SNIP: 0.606 CiteScore™:: 3.1 H-Index: 31

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A HIERARCHICAL MULTISCALE MODEL FOR PREDICTING THE VASCULAR BEHAVIOR OF BLOOD-BORNE NANOMEDICINES

巻 18, 発行 3, 2020, pp. 335-359
DOI: 10.1615/IntJMultCompEng.2020033358
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要約

In the field of nanomedicine, there is a pressing need for predictive, quantitative tools to rationally design and optimize carriers for therapeutic and imaging applications. Current nano/microfabrication technologies allow us to control a large number of parameters, including the size, shape surface properties, and mechanical stiffness. These design parameters affect the biophysical behavior of nanomedicines in terms of blood longevity, tissue deposition, drug release, contrast imaging amplification, and more. Thus, sophisticated, multiscale and multiphysics computational models are needed to predict the behavior of nanomedicines and guide the fabrication process toward optimal delivery systems. This work is a first step toward the realization of a fully integrated simulation platform. Here a computational model for describing blood flow in the microvasculature, particle transport, and molecular interaction with the vascular walls is presented. The model predicts particle deposition within a tumor microvasculature as a function of different design parameters. The simulations show that there is a complex interaction between the morphology of the vascular network, the particle surface and mechanical properties, and the particle deposition on the vascular walls. Specifically, the computational model shows and provides interpretation of how the stiffness affects significantly the probability of adhesion onto the vascular walls and the distribution along the network of blood-borne nanomedicines.

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によって引用された
  1. Possenti Luca, Cicchetti Alessandro, Rosati Riccardo, Cerroni Daniele, Costantino Maria Laura, Rancati Tiziana, Zunino Paolo, A Mesoscale Computational Model for Microvascular Oxygen Transfer, Annals of Biomedical Engineering, 49, 12, 2021. Crossref

  2. Coclite A., de Tullio M.D., Pascazio G., Politi T., Characterization of micro-capsules deformation in branching channels, Applied Mathematics and Computation, 434, 2022. Crossref

  3. Astefanoaei Iordana, Stancu Alexandru, Heat transfer computations in an intravascular tumoral region for magnetic hyperthermia, The European Physical Journal Plus, 137, 10, 2022. Crossref

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