scholarly journals Asamataxis: A cooperative relayed migration in response to subsurface inhomogeneity leads to long-range self-patterning of cells

2019 ◽  
Author(s):  
Akshada Khadpekar ◽  
Kanksha Mistry ◽  
Nehal Dwivedi ◽  
Aditya Paspunurwar ◽  
Parag Tandaiya ◽  
...  
Keyword(s):  
Pattern Formation ◽  
Long Range ◽  
Cellular Migration ◽  
Surface Structures ◽  
Dimensionless Number ◽  
Self Organized ◽  
Suitable Combination ◽  
Embedded Structure ◽  
Potential Tool

AbstractCells self-organize to give patterns that are essential for tissue functioning. While the effects of biochemical and mechanical cues are relatively well studied, the role of stiffness inhomogeneity on cellular patterning is unexplored. Using a rigid structure embedded in soft polyacrylamide (PAA) gel, we show that such mechanical inhomogeneity leads to long-range self-organized cellular patterns. Our results reveal that this patterning depends on cellular traction and cell morphology. Depending on a suitable combination of cellular morphology and traction, the information about the presence of embedded structure gets relayed outward. In response to this relay, the cells reorient their axis and migrate towards the embedded structure leading to the observed long-range (20-35 cell length) patterning. To predict the possibility of pattern formation, we present a dimensionless number ‘f’ combining the governing parameters. We have also shown that the pattern can be tailor-made by pre-designing sub-surface structures, a potential tool for tissue engineering. This mechanism of directed migration driven long-range pattern formation in response to mechanical inhomogeneity may be involved during several pathophysiological conditions, a proposition that needs further investigation.One Sentence SummarySubstrate inhomogeneity and cooperative cellular traction together lead to cellular migration and long-range pattern formation.

X-Ray Diffraction Applied to the Study of Defects in Surfaces

1984 ◽  
Vol 41 ◽  
Author(s):  
I. K. Robinson ◽  
K. L. D'amico
Keyword(s):  
Long Range ◽  
Domain Walls ◽  
Surface Structures ◽  
Long Range Order ◽  
X Ray Diffraction ◽  
X Ray ◽  
Line Defects ◽  
Reconstructed Surface ◽  
Regular Arrays

AbstractThe role of x-ray diffraction in characterising defects in crystals is reviewed briefly. It is most sensitive to the presence of plane defects which destroy the long-range order. The same argument is shown to apply to line defects in surface structures. Two recent glancing incidence x-ray diffraction experiments provide contrasting examples: randomly distributed steps are found in the Au(110) reconstructed surface, while regular arrays of domain walls modify certain phases of krypton monolayers physisorbed on graphite substrates.

scholarly journals The role of phase separation for self-organized surface pattern formation by ion beam erosion and metal atom co-deposition

2012 ◽  
Vol 111 (2) ◽  
pp. 653-664 ◽  
Author(s):  
H. Hofsäss ◽  
K. Zhang ◽  
A. Pape ◽  
O. Bobes ◽  
M. Brötzmann
Keyword(s):  
Phase Separation ◽  
Pattern Formation ◽  
Metal Atom ◽  
Ion Beam ◽  
Surface Pattern ◽  
Self Organized

scholarly journals Feedback-Driven Plasmonic-Thermal Route to Femtosecond-Laser-Induced Periodic Surface Structures in Silicon Indicated by Pump-Probe Scattering and Diffraction

Surfaces ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 277-294
Author(s):  
Robin Wehner ◽  
Ruediger Grunwald
Keyword(s):  
Surface Structures ◽  
Pump Probe ◽  
Periodic Surface ◽  
Fundamental Interest ◽  
Self Organized ◽  
Spatial Frequencies ◽  
Linearly Polarized ◽  
General Aspects ◽  
Excitation Conditions

The self-organized formation of nanoscale laser-induced periodic surface structures (LIPSS) is still not fully understood with respect to the dynamics and interplay of contributing complex mechanisms. The transition from randomness to order and the specific role of nano-feedback are of fundamental interest because of their general aspects. In our study, the very first steps of the surface reconfiguration are demonstrated by analyzing the topology of evolving nano-crater maps. The evolution of spatial frequencies and directional arrangement indicate a feedback-driven adaptation of k-vectors to the required excitation conditions of elementary dipoles in the linearly polarized laser field. The time-dependent structure formation was studied by pump-probe diffraction and scattering experiments. The ratio of the contributions of characteristic light patterns enables plasmonic and non-plasmonic mechanisms to be distinguished, which subsequently act at distinctly different time scales. Recently developed multistage models for the dynamics of material modification are confirmed. The influence of accumulation effects is clearly demonstrated by characteristic changes in scattering and diffraction with an increasing number of preceding pulses. It is assumed that the thermal and plasmonic contributions to accumulation are coupled and thus generate spatially variable modifications.

scholarly journals Perspective: network-guided pattern formation of neural dynamics

2014 ◽  
Vol 369 (1653) ◽  
pp. 20130522 ◽  
Author(s):  
Marc-Thorsten Hütt ◽  
Marcus Kaiser ◽  
Claus C. Hilgetag
Keyword(s):  
Pattern Formation ◽  
Network Architecture ◽  
Brain Connectivity ◽  
Activity Patterns ◽  
Neural Dynamics ◽  
Self Organized ◽  
Topological Features ◽  
Small Set ◽  
Spatio Temporal

The understanding of neural activity patterns is fundamentally linked to an understanding of how the brain's network architecture shapes dynamical processes. Established approaches rely mostly on deviations of a given network from certain classes of random graphs. Hypotheses about the supposed role of prominent topological features (for instance, the roles of modularity, network motifs or hierarchical network organization) are derived from these deviations. An alternative strategy could be to study deviations of network architectures from regular graphs (rings and lattices) and consider the implications of such deviations for self-organized dynamic patterns on the network. Following this strategy, we draw on the theory of spatio-temporal pattern formation and propose a novel perspective for analysing dynamics on networks, by evaluating how the self-organized dynamics are confined by network architecture to a small set of permissible collective states. In particular, we discuss the role of prominent topological features of brain connectivity, such as hubs, modules and hierarchy, in shaping activity patterns. We illustrate the notion of network-guided pattern formation with numerical simulations and outline how it can facilitate the understanding of neural dynamics.

The Role of Technological Change in the Long-run Global Economy Forecasting

2013 ◽  
pp. 97-116 ◽  
Author(s):  
A. Apokin
Keyword(s):  
Technological Change ◽  
Data Quality ◽  
Long Range ◽  
Global Economy ◽  
World Economy ◽  
Qualitative Approaches ◽  
Long Run ◽  
The World ◽  
National Economies

The author compares several quantitative and qualitative approaches to forecasting to find appropriate methods to incorporate technological change in long-range forecasts of the world economy. A?number of long-run forecasts (with horizons over 10 years) for the world economy and national economies is reviewed to outline advantages and drawbacks for different ways to account for technological change. Various approaches based on their sensitivity to data quality and robustness to model misspecifications are compared and recommendations are offered on the choice of appropriate technique in long-run forecasts of the world economy in the presence of technological change.

The role of asymmetric excitation in self-organized nanostructure formation upon femtosecond laser ablation

2011 ◽  
Vol 104 (3) ◽  
pp. 969-973 ◽  
Author(s):  
Juergen Reif ◽  
Olga Varlamova ◽  
Sergej Varlamov ◽  
Michael Bestehorn
Keyword(s):  
Laser Ablation ◽  
Femtosecond Laser ◽  
Femtosecond Laser Ablation ◽  
Nanostructure Formation ◽  
Self Organized

scholarly journals The Role of Src Kinase in Macrophage-Mediated Inflammatory Responses

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Se Eun Byeon ◽  
Young-Su Yi ◽  
Jueun Oh ◽  
Byong Chul Yoo ◽  
Sungyoul Hong ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Immune Responses ◽  
Inflammatory Responses ◽  
Inflammatory Diseases ◽  
Src Kinase ◽  
Multiple Roles ◽  
Cellular Migration ◽  
Pharmaceutical Drugs ◽  
Tyrosine Protein Kinase

Src kinase (Src) is a tyrosine protein kinase that regulates cellular metabolism, survival, and proliferation. Many studies have shown that Src plays multiple roles in macrophage-mediated innate immunity, such as phagocytosis, the production of inflammatory cytokines/mediators, and the induction of cellular migration, which strongly implies that Src plays a pivotal role in the functional activation of macrophages. Macrophages are involved in a variety of immune responses and in inflammatory diseases including rheumatoid arthritis, atherosclerosis, diabetes, obesity, cancer, and osteoporosis. Previous studies have suggested roles for Src in macrophage-mediated inflammatory responses; however, recently, new functions for Src have been reported, implying that Src functions in macrophage-mediated inflammatory responses that have not been described. In this paper, we discuss recent studies regarding a number of these newly defined functions of Src in macrophage-mediated inflammatory responses. Moreover, we discuss the feasibility of Src as a target for the development of new pharmaceutical drugs to treat macrophage-mediated inflammatory diseases. We provide insights into recent reports regarding new functions for Src that are related to macrophage-related inflammatory responses and the development of novel Src inhibitors with strong immunosuppressive and anti-inflammatory properties, which could be applied to various macrophage-mediated inflammatory diseases.

Role of Nuclei in Liesegang Pattern Formation: Insights from Experiment and Reaction-Diffusion Simulation

2018 ◽  
Vol 122 (6) ◽  
pp. 3669-3676 ◽  
Author(s):  
Masaki Itatani ◽  
Qing Fang ◽  
Kei Unoura ◽  
Hideki Nabika
Keyword(s):  
Pattern Formation ◽  
Reaction Diffusion ◽  
Diffusion Simulation
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