Tumor growth for remodeling process: A 2D approach.

This paper aims to present a comprehensive framework for coupling tumor-bone remodeling processes in a 2-dimensional geometry. This is achieved by introducing a bio-inspired damage that represents the growing tumor, which subsequently affects the main populations involved in the remodeling process, namely, osteoclasts, osteoblasts, and bone tissue. The model is constructed using a set of differential equations based on the Komarova's and Ayati's models, modified to incorporate the bio-inspired damage that may result in tumor mass formation. Three distinct models were developed. The first two models are based on the Komarova's governing equations, with one demonstrating an osteolytic behavior and the second one an osteoblastic model. The third model is a variation of Ayati's model, where the bio-inspired damage is induced through the paracrine and autocrine parameters, exhibiting an osteolytic behavior. The obtained results are consistent with existing literature, leading us to believe that our in-silico experiments will serve as a cornerstone for paving the way towards targeted interventions and personalized treatment strategies, ultimately improving the quality of life for those affected by these conditions.

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

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.

Nature and nurture shape structural connectivity in the face processing brain network.

Face processing is a key ability facilitating social cognition. Only a few studies explored how nature and nurture shape face processing ontogeny at the behavioral and neural level. Also, very little is known about the contributions of nature and nurture to the establishment of white matter fibers supporting this specific human ability. The main purpose of this study was to assess genetic and environmental influences on white matter bundles connecting atlas-defined and functionally-defined face-responsive areas in the brain. Diffusion weighted images from 408 twins (monozygotic = 264, dizygotic = 144) were obtained from the WU-Minn Human Connectome Project. Fractional anisotropy - a widely used measure of fiber quality - of seven white matter tracts in the face network and ten global white matter tracts was analyzed by means of Structural Equation Modeling for twin data. Results revealed small and moderate genetic effects on face network fiber quality in addition to their shared variance with global brain white matter integrity. Furthermore, a theoretically expected common latent factor accounted for limited genetic and larger environmental variance in multiple face network fibers. The findings suggest that both genetic and environmental factors explain individual differences in fiber quality within the face network, as compared with much larger genetic effects on global brain white matter quality. In addition to heritability, individual-specific environmental influences on the face processing brain network are large, a finding that suggests to connect nature and nurture views on this remarkably specific human ability.