2021
DOI: 10.1063/5.0045278
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Measurements and characterization of the dynamics of tracer particles in an actin network

Abstract: The underlying physics governing the diffusion of a tracer particle in a viscoelastic material is a topic of some dispute. The long-term memory in the mechanical response of such materials should induce diffusive motion with a memory kernel, such as fractional Brownian motion (fBM). This is the reason that microrheology is able to provide the shear modulus of polymer networks. Surprisingly, the diffusion of a tracer particle in a network of a purified protein, actin, was found to conform to the continuous time… Show more

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Cited by 24 publications
(25 citation statements)
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“…In recent years, certain combinations of models were proposed, including switching-diffusivity 11,13,[70][71][72][73][74][75][76][77] and annealed-transienttime models (ATTM), 78 BM with fluctuating or diffusing diffusivity (DD), 70,[79][80][81][82][83][84][85] BM-and anomalous-diffusion-models with ''superstatistically'' distributed model parameters, [86][87][88][89] compound diffusion processes of SBM-DD, 84 SBM-HDPs, 90,91 FBM-DD, 92 FBM-HDPs, 19,93 SBM with exponentially and logarithmically varying D(t), 94 CTRWs with random walks on fractal (RWFs), 95 CTRW-FBM, 16,[96][97][98] as well as several other models, 74,[99][100][101][102][103][104][105][106][107][108][109]…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, certain combinations of models were proposed, including switching-diffusivity 11,13,[70][71][72][73][74][75][76][77] and annealed-transienttime models (ATTM), 78 BM with fluctuating or diffusing diffusivity (DD), 70,[79][80][81][82][83][84][85] BM-and anomalous-diffusion-models with ''superstatistically'' distributed model parameters, [86][87][88][89] compound diffusion processes of SBM-DD, 84 SBM-HDPs, 90,91 FBM-DD, 92 FBM-HDPs, 19,93 SBM with exponentially and logarithmically varying D(t), 94 CTRWs with random walks on fractal (RWFs), 95 CTRW-FBM, 16,[96][97][98] as well as several other models, 74,[99][100][101][102][103][104][105][106][107][108][109]…”
Section: Introductionmentioning
confidence: 99%
“…Observational non-ergodicity has been documented on the time window of 0.01 ~ 100 seconds in various biological phenomena, including the transport of protein molecules or nanoparticles through complex macroscopic biological systems, such as cell membranes, living cells, and actin filaments. [38][39][40][41][42][43] These systems are large enough (> 1 μm) and have structures that are complex and heterogeneous enough to produce complex, non-ergodic dynamics. Single-molecule force-clamp spectroscopy has demonstrated non-ergodicity to occur when unfolding a protein molecule at the time window of 0.01 ~ 10 s. 18,59 However, unfolding or folding corresponds to a dramatic perturbation of the biomolecule, far away from its folded globular functional state.…”
Section: Discussionmentioning
confidence: 99%
“…Indeed, the internal dynamics of SHP2 ages with the observation time. This aging behavior is often interpreted by the framework of continuos-time random walk (CTRW), [38][39][40][41][42][43] and thus why we derive the waiting time distribution in Fig. S7.…”
Section: Observational Non-ergodicity In Shp2 Measured By MDmentioning
confidence: 99%
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“…The ability to precisely tune the control parameters, and hence the ensuing anomaly, is a unique advantage of atomic systems. It is not common that a basic theory such as that of Sisyphus cooling can lead to a detailed theoretical understanding of the origins of anomalous diffusion, usually found in truly complex settings such as biological systems (Barkai et al, 2012;Levin et al, 2021;Lo et al, 2002), economics (Plerou et al, 2000) or turbulent flows (Richardson, 1926). Furthermore, these atomic systems enable both one-shot ensemble averaging of millions of particles, single-particle tracking (Bouton et al, 2020;Katori et al, 1997;Kindermann et al, 2016) and the application of advanced spectral analysis tools.…”
Section: Introductionmentioning
confidence: 99%