Literature DB >> 35776358

In Vitro Brain Organoids and Computational Models to Study Cell Death in Brain Diseases.

Meitham Amereh1,2, Amir Seyfoori1,3, Mohsen Akbari4,5.   

Abstract

Understanding the mechanisms underlying the formation and progression of brain diseases is challenging due to the vast variety of involved genetic/epigenetic factors and the complexity of the environment of the brain. Current preclinical monolayer culture systems fail to faithfully recapitulate the in vivo complexities of the brain. Organoids are three-dimensional (3D) culture systems that mimic much of the complexities of the brain including cell-cell and cell-matrix interactions. Complemented with a theoretical framework to model the dynamic interactions between different components of the brain, organoids can be used as a potential tool for studying disease progression, transport of therapeutic agents in tissues, drug screening, and toxicity analysis. In this chapter, we first report on the fabrication and use of a novel self-filling microwell arrays (SFMWs) platform that is self-filling and enables the formation of organoids with uniform size distributions. Next, we will introduce a mathematical framework that predicts the organoid growth, cell death, and the therapeutic responses of the organoids to different therapeutic agents. Through systematic investigations, the computational model can identify shortcomings of in vitro assays and reduce the time and effort required to improve preclinical tumor models' design. Lastly, the mathematical model provides new testable hypotheses and encourages mathematically driven experiments.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Brain tissue models; In silico modeling; Neuronal cell death; Organoids

Mesh:

Year:  2022        PMID: 35776358     DOI: 10.1007/978-1-0716-2409-8_17

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  In silico experimental modeling of cancer treatment.

Authors:  D G Mallet
Journal:  ISRN Oncol       Date:  2012-02-01
  1 in total
  1 in total

1.  Better In Vitro Tools for Exploring Chlamydia trachomatis Pathogenesis.

Authors:  Simone Filardo; Marisa Di Pietro; Rosa Sessa
Journal:  Life (Basel)       Date:  2022-07-15
  1 in total

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