scholarly journals Correction to: Time resolution effect on the apparent particle dynamics confined in a nanochannel evaluated by the single particle tracking subject to Brownian motion

2020 ◽  
Vol 24 (10) ◽  
Author(s):  
Itsuo Hanasaki ◽  
Yutaka Kazoe ◽  
Takehiko Kitamori
Keyword(s):  
Brownian Motion ◽  
Particle Tracking ◽  
Time Resolution ◽  
Single Particle ◽  
Particle Dynamics ◽  
Single Particle Tracking

scholarly journals The cell wall regulates dynamics and size of plasma-membrane nanodomains inArabidopsis

2019 ◽  
Vol 116 (26) ◽  
pp. 12857-12862 ◽  
Author(s):  
J. F. McKenna ◽  
D. J. Rolfe ◽  
S. E. D. Webb ◽  
A. F. Tolmie ◽  
S. W. Botchway ◽  
...  
Keyword(s):  
Cell Wall ◽  
Plasma Membrane ◽  
Confocal Microscopy ◽  
Particle Tracking ◽  
Single Particle ◽  
Cluster Size ◽  
Particle Dynamics ◽  
Single Particle Tracking ◽  
Signaling Cascade ◽  
Plant Plasma Membrane

Plant plasma-membrane (PM) proteins are involved in several vital processes, such as detection of pathogens, solute transport, and cellular signaling. For these proteins to function effectively there needs to be structure within the PM allowing, for example, proteins in the same signaling cascade to be spatially organized. Here we demonstrate that several proteins with divergent functions are located in clusters of differing size in the membrane using subdiffraction-limited Airyscan confocal microscopy. Single particle tracking reveals that these proteins move at different rates within the membrane. Actin and microtubule cytoskeletons appear to significantly regulate the mobility of one of these proteins (the pathogen receptor FLS2) and we further demonstrate that the cell wall is critical for the regulation of cluster size by quantifying single particle dynamics of proteins with key roles in morphogenesis (PIN3) and pathogen perception (FLS2). We propose a model in which the cell wall and cytoskeleton are pivotal for regulation of protein cluster size and dynamics, thereby contributing to the formation and functionality of membrane nanodomains.

scholarly journals Inertia triggers nonergodicity of fractional Brownian motion

2021 ◽  
Author(s):  
Andrey Cherstvy ◽  
Wei Wang ◽  
Ralf Metzler ◽  
Igor Sokolov
Keyword(s):  
Brownian Motion ◽  
Fractional Brownian Motion ◽  
Particle Tracking ◽  
Single Particle ◽  
Single Particle Tracking ◽  
Langevin Equations ◽  
Ergodic Properties ◽  
Massive Particles ◽  
Breaking Parameter ◽  
Ergodicity Breaking

How related are the ergodic properties of the over- and underdamped Langevin equations driven by fractional Gaussian noise? We here find that for massive particles performing fractional Brownian motion (FBM) inertial effects not only destroy the stylized fact of the equivalence of the ensemble-averaged mean-squared displacement (MSD) to the time-averaged MSD (TAMSD) of overdamped or massless FBM, but also concurrently dramatically alter the values of the ergodicity breaking parameter (EB). Our theoretical results for the behavior of EB for underdamped ot massive FBM for varying particle mass m, Hurst exponent H, and trace length T are in excellent agreement with the findings of extensive stochastic computer simulations. The current results can be of interest for the experimental community employing various single-particle-tracking techniques and aiming at assessing the degree of nonergodicity for the recorded time series (studying e.g. the behavior of EB versus lag time). To infer FBM as a realizable model of anomalous diffusion for a set single-particle-tracking data when massive particles are being tracked, the EBs from the data should be compared to EBs of massive (rather than massless) FBM.

scholarly journals Information-Efficient, Off-Center Sampling Results in Improved Precision in 3D Single-Particle Tracking Microscopy

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 498
Author(s):  
Chen Zhang ◽  
Kevin Welsher
Keyword(s):  
Fisher Information ◽  
Particle Tracking ◽  
Single Particle ◽  
Biological Samples ◽  
Tracking System ◽  
Single Particle Tracking ◽  
Uniform Sampling ◽  
Single Dimension ◽  
3D Localization ◽  
Particle Localization

In this work, we present a 3D single-particle tracking system that can apply tailored sampling patterns to selectively extract photons that yield the most information for particle localization. We demonstrate that off-center sampling at locations predicted by Fisher information utilizes photons most efficiently. When performing localization in a single dimension, optimized off-center sampling patterns gave doubled precision compared to uniform sampling. A ~20% increase in precision compared to uniform sampling can be achieved when a similar off-center pattern is used in 3D localization. Here, we systematically investigated the photon efficiency of different emission patterns in a diffraction-limited system and achieved higher precision than uniform sampling. The ability to maximize information from the limited number of photons demonstrated here is critical for particle tracking applications in biological samples, where photons may be limited.

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