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Biomechanics and Modeling in Mechanobiology
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
https://dx.doi.org/10.60692/xa...
Other literature type . 2023
Data sources: Datacite
https://dx.doi.org/10.60692/ge...
Other literature type . 2023
Data sources: Datacite
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A coupled mathematical model between bone remodeling and tumors: a study of different scenarios using Komarova’s model

نموذج رياضي مقترن بين إعادة تشكيل العظام والأورام: دراسة لسيناريوهات مختلفة باستخدام نموذج كوماروفا
Authors: S. Ramtani; Juan Felipe Sánchez; Abdelkader Boucetta; Reuben H. Kraft; Juan Jairo Vaca‐González; Diego Alexander Garzón‐Alvarado;

A coupled mathematical model between bone remodeling and tumors: a study of different scenarios using Komarova’s model

Abstract

Abstract This paper aims to construct a general framework of coupling tumor–bone remodeling processes in order to produce plausible outcomes of the effects of tumors on the number of osteoclasts, osteoblasts, and the frequency of the bone turnover cycle. In this document, Komarova’s model has been extended to include the effect of tumors on the bone remodeling processes. Thus, we explored three alternatives for coupling tumor presence into Komarova’s model: first, using a “damage” parameter that depends on the tumor cell concentration. A second model follows the original structure of Komarova, including the tumor presence in those equations powered up to a new parameter, called the paracrine effect of the tumor on osteoclasts and osteoblasts; the last model is replicated from Ayati and collaborators in which the impact of the tumor is included into the paracrine parameters. Through the models, we studied their stability and considered some examples that can reproduce the tumor effects seen in clinic and experimentally. Therefore, this paper has three parts: the exposition of the three models, the results and discussion (where we explore some aspects and examples of the solution of the models), and the conclusion.

Keywords

Tumor Dynamics, Osteoclasts, Cancer research, Tumor cells, Biochemistry, Endocrinology, Rheumatology, In vitro, Biochemistry, Genetics and Molecular Biology, Health Sciences, Machine learning, FOS: Mathematics, Coupling (piping), Stability (learning theory), Biology, Internal medicine, Mathematical Modeling of Cancer Growth and Treatment, Original Paper, Osteoblasts, Osteoblast, Life Sciences, Cell Biology, Models, Theoretical, Regulation and Function of Microtubules in Cell Division, Bone remodeling, Computer science, Materials science, Modeling and Simulation, Physical Sciences, Metallurgy, Paracrine signalling, Medicine, Heterotopic Ossification and Fibrodysplasia Ossificans Progressiva, Bone Remodeling, Mathematics, Receptor

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
Green
hybrid
Related to Research communities
Cancer Research