Spatial networks as models for organoid cultures and brain research
Peter Simon Sapaty
Abstract
The paper relates to the concept of organoids, the simplified versions of organs produced artificially, which are of growing importance and popularity, especially for disease prediction and prevention and brain research, too. It investigates the potential capabilities of the creation, evolution, and analysis of organoid models with the developed Spatial Grasp Model and Technology (SGT) which has already been tested on various applications, including the management of networked technological, social, and defense systems. The paper first analyzes and classifies the latest organoid-related publications, then briefs the main SGT features, including its basic Spatial Grasp Language with its networked interpretation, resulting in powerful spatial engines capable of covering terrestrial and celestial environments. Then it shows a practical and very compact expression of growing organoid models under SGT which include cell growth, division and replication, cell worm creation and movement, killer cell operation, and finally, a full organoid model with its operation. It also explains how to investigate parameters of the growing organoids that can predict disease-related behavior. The paper reviews some other organoid developments of interest for the use of SGT, including mini-brains in robotics, organoid-emitting brain waves, and the development of organoids in outer space. It concludes with the plans for more detailed and extensive results with SGT which may be used in different ways. Firstly, the networking models of organoids can be obtained much quicker than the growing tissue in labs. Secondly, it may appear useful to combine virtual and living features in the united organoid development and research process. Thirdly, if a living tissue is really needed for organ replacement, advanced virtual growth of such organoids can orient and direct the real tissue development.