scholarly journals Engineering pattern formation and morphogenesis

2020 ◽  
Vol 48 (3) ◽  
pp. 1177-1185
Author(s):  
Jamie A. Davies ◽  
Fokion Glykofrydis
Keyword(s):  
Tissue Engineering ◽  
Synthetic Biology ◽  
Pattern Formation ◽  
Research And Development ◽  
Reaction Diffusion ◽  
Future Research ◽  
Self Organized ◽  
Physical Form ◽  
Basic Understanding ◽  
Self Organizing

The development of natural tissues, organs and bodies depends on mechanisms of patterning and of morphogenesis, typically (but not invariably) in that order, and often several times at different final scales. Using synthetic biology to engineer patterning and morphogenesis will both enhance our basic understanding of how development works, and provide important technologies for advanced tissue engineering. Focusing on mammalian systems built to date, this review describes patterning systems, both contact-mediated and reaction-diffusion, and morphogenetic effectors. It also describes early attempts to connect the two to create self-organizing physical form. The review goes on to consider how these self-organized systems might be modified to increase the complexity and scale of the order they produce, and outlines some possible directions for future research and development.

scholarly journals Una Exploración Conceptual de la Formación de Patrones en Sistemas Sociales Autorganizados

Ingeniería ◽  
2018 ◽  
Vol 23 (1) ◽  
pp. 84
Author(s):  
David Anzola
Keyword(s):  
Pattern Formation ◽  
Interdisciplinary Collaboration ◽  
Complexity Science ◽  
Self Organization ◽  
Social Self ◽  
Social Scientists ◽  
Self Organized ◽  
Scientists And Engineers ◽  
High Level ◽  
Self Organizing

Context: The concept of self-organization plays a major role in contemporary complexity science. Yet, the current framework for the study of self-organization is only able to capture some of the nuances of complex social self-organizing phenomena.Method: This article addresses some of the problematic elements in the study of social selforganization. For this purpose, it focuses on pattern formation, a feature of self-organizing phenomena that is common across definitions. The analysis is carried out through three main questions: where can we find these patterns, what are these patterns and how can we study these patterns.Results: The discussion shows that there is a high level of specificity in social self-organized phenomena that is not adequately addressed by the current complexity framework. It argues that some elements are neglected by this framework because they are relatively exclusive to social science; others, because of the relative novelty of social complexity.Conclusions: It is suggested that interdisciplinary collaboration between social scientists and complexity scientists and engineers is needed, in order to overcome traditional disciplinary limitations in the study of social self-organized phenomena.

scholarly journals Pattern formation mechanisms of self-organizing reaction-diffusion systems

2020 ◽  
Vol 460 (1) ◽  
pp. 2-11 ◽  
Author(s):  
Amit N. Landge ◽  
Benjamin M. Jordan ◽  
Xavier Diego ◽  
Patrick Müller
Keyword(s):  
Pattern Formation ◽  
Reaction Diffusion ◽  
Formation Mechanisms ◽  
Reaction Diffusion Systems ◽  
Diffusion Systems ◽  
Self Organizing

scholarly journals Morphogenesis in robot swarms

2018 ◽  
Vol 3 (25) ◽  
pp. eaau9178 ◽  
Author(s):  
I. Slavkov ◽  
D. Carrillo-Zapata ◽  
N. Carranza ◽  
X. Diego ◽  
F. Jansson ◽  
...  
Keyword(s):  
Reaction Diffusion ◽  
Intrinsic Noise ◽  
Top Down ◽  
Local Interactions ◽  
Gene Circuits ◽  
Changing Environments ◽  
Robot Swarms ◽  
Self Organized ◽  
Robotic Applications ◽  
Self Organizing

Morphogenesis allows millions of cells to self-organize into intricate structures with a wide variety of functional shapes during embryonic development. This process emerges from local interactions of cells under the control of gene circuits that are identical in every cell, robust to intrinsic noise, and adaptable to changing environments. Constructing human technology with these properties presents an important opportunity in swarm robotic applications ranging from construction to exploration. Morphogenesis in nature may use two different approaches: hierarchical, top-down control or spontaneously self-organizing dynamics such as reaction-diffusion Turing patterns. Here, we provide a demonstration of purely self-organizing behaviors to create emergent morphologies in large swarms of real robots. The robots achieve this collective organization without any self-localization and instead rely entirely on local interactions with neighbors. Results show swarms of 300 robots that self-construct organic and adaptable shapes that are robust to damage. This is a step toward the emergence of functional shape formation in robot swarms following principles of self-organized morphogenetic engineering.

scholarly journals Tuning the Spatially Controlled Growth, Structural Self-Organizing and Cluster-Assembling of the Carbyne-Enriched Nanostructured Metamaterials during Ion-Assisted Pulse-Plasma Deposition

2021 ◽  
Author(s):  
Alexander Lukin ◽  
Oğuz Gülseren
Keyword(s):  
Pattern Formation ◽  
Electric Field ◽  
Spatial Structure ◽  
Plasma Deposition ◽  
The Self ◽  
Self Organization ◽  
Structure And Properties ◽  
Self Organized ◽  
Wave Patterns ◽  
Self Organizing

Structural self-organizing and pattern formation are universal and key phenomena observed during growth and cluster-assembling of the carbyne-enriched nanostructured metamaterials at the ion-assisted pulse-plasma deposition. Fine tuning these universal phenomena opens access to designing the properties of the growing carbyne-enriched nano-matrix. The structure of bonds in the grown carbyne-enriched nano-matrices can be programmed by the processes of self-organization and auto-synchronization of nanostructures. We propose the innovative concept, connected with application of the universal Cymatics phenomena during the predictive growth of the carbyne-enriched nanostructured metamaterials. We also propose the self-organization approach for increase stability of the long linear carbon chains. The main idea of suggested concept is manipulating by the self-organized wave patterns excitation phenomenon and their distribution by the spatial structure and properties of the nanostructured metamaterial grows region through the new synergistic effect. Mentioned effect will be provided through the vibration-assisted self-organized wave patterns excitation along with simultaneous manipulating by their properties through the electric field. We propose to use acoustic activation of the plasma zone of nano-matrix growing. Interaction between the inhomogeneous electric field distribution generated on the vibrating layer and the plasma ions will serve as the additional energizing factor controlling the local pattern formation and self-organizing of the nano-structures. Suggested concept makes it possible to provide precise predictive designing the spatial structure and properties of the advanced carbyne-enriched nanostructured metamaterials.

Synthetic biology for improving cell fate decisions and tissue engineering outcomes

2019 ◽  
Vol 3 (5) ◽  
pp. 631-643 ◽  
Author(s):  
Adam M. Vogel ◽  
Kylie M. Persson ◽  
Travis R. Seamons ◽  
Tara L. Deans
Keyword(s):  
Tissue Engineering ◽  
Stem Cells ◽  
Synthetic Biology ◽  
Cell Fate ◽  
Genome Engineering ◽  
Future Research ◽  
Genetic Circuits ◽  
Cell Fate Decisions ◽  
Work Done ◽  
The Way

Synthetic biology is a relatively new field of science that combines aspects of biology and engineering to create novel tools for the construction of biological systems. Using tools within synthetic biology, stem cells can then be reprogrammed and differentiated into a specified cell type. Stem cells have already proven to be largely beneficial in many different therapies and have paved the way for tissue engineering and regenerative medicine. Although scientists have made great strides in tissue engineering, there still remain many questions to be answered in regard to regeneration. Presented here is an overview of synthetic biology, common tools built within synthetic biology, and the way these tools are being used in stem cells. Specifically, this review focuses on how synthetic biologists engineer genetic circuits to dynamically control gene expression while also introducing emerging topics such as genome engineering and synthetic transcription factors. The findings mentioned in this review show the diverse use of stem cells within synthetic biology and provide a foundation for future research in tissue engineering with the use of synthetic biology tools. Overall, the work done using synthetic biology in stem cells is in its early stages, however, this early work is leading to new approaches for repairing diseased and damaged tissues and organs, and further expanding the field of tissue engineering.

scholarly journals A Synthetic Biology Approach to Sequential Stripe Patterning and Somitogenesis

2019 ◽  
Author(s):  
Fuqing Wu ◽  
Changhan He ◽  
Xin Fang ◽  
Javier Baez ◽  
Thai Ohnmacht ◽  
...  
Keyword(s):  
Gene Expression ◽  
Synthetic Biology ◽  
Pattern Formation ◽  
Gene Networks ◽  
Gene Expression Regulation ◽  
Initial Conditions ◽  
Reaction Diffusion ◽  
Bacterial Cells ◽  
Stripe Pattern

AbstractReaction-diffusion (RD) based clock and wavefront model has long been proposed as the mechanism underlying biological pattern formation of repeated and segmented structures including somitogenesis. However, systematic molecular level understanding of the mechanism remains elusive, largely due to the lack of suitable experimental systems to probe RD quantitatively in vivo. Here we design a synthetic gene circuit that couples gene expression regulation (reaction) with quorum sensing (diffusion) to guide bacterial cells self-organizing into stripe patterns at both microscopic and colony scales. An experimentally verified mathematical model confirms that these periodic spatial structures are emerged from the integration of oscillatory gene expression as the molecular clock and the outward expanding diffusions as the propagating wavefront. Furthermore, our paired model-experiment data illustrate that the RD-based patterning is sensitive to initial conditions and can be modulated by external inducers to generate diverse patterns, including multiple-stripe pattern, target-like pattern and ring patterns with reversed fluorescence. Powered by our synthetic biology setup, we also test different topologies of gene networks and show that network motifs enabling robust oscillations are foundations of sequential stripe pattern formation. These results verified close connections between gene network topology and resulting RD driven pattern formation, offering an engineering approach to help understand biological development.

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