Local sampling paints a global picture: Local concentration measurements sense direction in complex chemical gradients

BioEssays ◽  
2017 ◽  
Vol 39 (7) ◽  
pp. 1600134 ◽  
Author(s):  
Björn Hegemann ◽  
Matthias Peter
Keyword(s):  
Local Concentration ◽  
Complex Chemical ◽  
Chemical Gradients ◽  
Sense Direction ◽  
Concentration Measurements ◽  
Local Sampling

scholarly journals Measuring concentration fields in microfluidic channels in situ with a Fabry–Perot interferometer

Lab on a Chip ◽  
2015 ◽  
Vol 15 (7) ◽  
pp. 1689-1696 ◽  
Author(s):  
Douglas R. Vogus ◽  
Vincent Mansard ◽  
Michael V. Rapp ◽  
Todd M. Squires
Keyword(s):  
Fluorescent Labeling ◽  
Microfluidic Channels ◽  
Concentration Profiles ◽  
Complex Chemical ◽  
Chemical Gradients ◽  
Microfluidic Technology ◽  
Fabry Perot ◽  
Spatio Temporal ◽  
And Control

Recent advancements in microfluidic technology have allowed for the generation and control of complex chemical gradients; however, few general techniques can measure these spatio-temporal concentration profiles without fluorescent labeling.

Cyclic Concentration Measurements for Characterizing Pulsating Flow

2013 ◽  
Author(s):  
Judith Ann Bamberger
Keyword(s):  
Concentration Profile ◽  
Pulsating Flow ◽  
Local Concentration ◽  
Concentration Data ◽  
Jet Mixing ◽  
Periodic Pulse ◽  
Solids Concentration ◽  
Concentration Measurements ◽  
Pulse Jet ◽  
Pulse Jet Mixing

Slurry mixed in vessels via pulse jet mixers has a periodic, rather than steady, concentration profile. Measurements of local concentration taken at the center of the tank at a range of elevations within the mixed region were analyzed to obtain a greater understanding of how the periodic pulse jet mixing cycle affects the local concentration. Data were obtained at the critical suspension velocity, when all solids are suspended at the end of the pulse. The data at a range of solids loadings are analyzed to observe the effect of solids concentration during the suspension and settling portions of the mixing cycle.

scholarly journals Study on the Formation of Complex Chemical Waveforms by Different Computational Methods

Processes ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 393
Author(s):  
Jiali Ai ◽  
Chi Zhai ◽  
Wei Sun
Keyword(s):  
Reaction Kinetics ◽  
Spiral Wave ◽  
Reaction Diffusion ◽  
Local Concentration ◽  
Periodic Patterns ◽  
Concentration Difference ◽  
Complex Chemical ◽  
Mass Transfer Theory ◽  
Chemical Waves ◽  
Oregonator Model

Chemical wave is a special phenomenon that presents periodic patterns in space-time domain, and the Belousov–Zhabotinsky (B-Z) reaction is the first well-known reaction-diffusion system that exhibits organized patterns out of a homogeneous environment. In this paper, the B-Z reaction kinetics is described by the Oregonator model, and formation and evolution of chemical waves are simulated based on this model. Two different simulation methods, partial differential equations (PDEs) and cellular automata (CA) are implemented to simulate the formation of chemical waveform patterns, i.e., target wave and spiral wave on a two-dimensional plane. For the PDEs method, reaction caused changes of molecules at different location are considered, as well as diffusion driven by local concentration difference. Specifically, a PDE model of the B-Z reaction is first established based on the B-Z reaction kinetics and mass transfer theory, and it is solved by a nine-point finite difference (FD) method to simulate the formation of chemical waves. The CA method is based on system theory, and interaction relations with the cells nearest neighbors are mainly concerned. By comparing these two different simulation strategies, mechanisms that cause the formation of complex chemical waves are explored, which provides a reference for the subsequent research on complex systems.

scholarly journals Chemotactic movement of a polarity site enables yeast cells to find their mates

2021 ◽  
Vol 118 (22) ◽  
pp. e2025445118
Author(s):  
Debraj Ghose ◽  
Katherine Jacobs ◽  
Samuel Ramirez ◽  
Timothy Elston ◽  
Daniel Lew
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Computational Model ◽  
Initial Orientation ◽  
Yeast Cells ◽  
Eukaryotic Cells ◽  
Stochastic Effects ◽  
Bottom Up ◽  
Complex Chemical ◽  
Chemical Gradients

How small eukaryotic cells can interpret dynamic, noisy, and spatially complex chemical gradients to orient growth or movement is poorly understood. We address this question using Saccharomyces cerevisiae, where cells orient polarity up pheromone gradients during mating. Initial orientation is often incorrect, but polarity sites then move around the cortex in a search for partners. We find that this movement is biased by local pheromone gradients across the polarity site: that is, movement of the polarity site is chemotactic. A bottom-up computational model recapitulates this biased movement. The model reveals how even though pheromone-bound receptors do not mimic the shape of external pheromone gradients, nonlinear and stochastic effects combine to generate effective gradient tracking. This mechanism for gradient tracking may be applicable to any cell that searches for a target in a complex chemical landscape.

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