Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
Add more filters











Database
Language
Publication year range
1.
Sci Rep ; 9(1): 16369, 2019 11 08.
Article in English | MEDLINE | ID: mdl-31704992

ABSTRACT

For a wide range of cells, from bacteria to mammals, locomotion movements are a crucial systemic behavior for cellular life. Despite its importance in a plethora of fundamental physiological processes and human pathologies, how unicellular organisms efficiently regulate their locomotion system is an unresolved question. Here, to understand the dynamic characteristics of the locomotion movements and to quantitatively study the role of the nucleus in the migration of Amoeba proteus we have analyzed the movement trajectories of enucleated and non-enucleated amoebas on flat two-dimensional (2D) surfaces using advanced non-linear physical-mathematical tools and computational methods. Our analysis shows that both non-enucleated and enucleated amoebas display the same kind of dynamic migration structure characterized by highly organized data sequences, super-diffusion, non-trivial long-range positive correlations, persistent dynamics with trend-reinforcing behavior, and move-step fluctuations with scale invariant properties. Our results suggest that the presence of the nucleus does not significantly affect the locomotion of amoeba in 2D environments.


Subject(s)
Amoeba/physiology , Cell Nucleus/physiology , Models, Biological , Least-Squares Analysis , Microscopy, Video , Movement/physiology , Nonlinear Dynamics
2.
Magn Reson Med ; 80(1): 317-329, 2018 07.
Article in English | MEDLINE | ID: mdl-29090480

ABSTRACT

PURPOSE: To establish a series of relationships defining how muscle microstructure and diffusion tensor imaging (DTI) are related. METHODS: The relationship among key microstructural features of skeletal muscle (fiber size, fibrosis, edema, and permeability) and the diffusion tensor were systematically simulated over physiologically relevant dimensions individually, and in combination, using a numerical simulation application. Stepwise multiple regression was used to identify which microstructural features of muscle significantly predict the diffusion tensor using single-echo and multi-echo DTI pulse sequences. Simulations were also performed in models with histology-informed geometry to investigate the relationship between fiber size and the diffusion tensor in models with real muscle geometry. RESULTS: Fiber size is the strongest predictor of λ2, λ3, mean diffusivity, and fractional anisotropy in skeletal muscle, accounting for approximately 40% of the variance in the diffusion model when calculated with single-echo DTI. This increased to approximately 70% when diffusion measures were calculated from the short T2 component of the multi-echo DTI sequence. This nonlinear relationship begins to plateau in fibers with greater than 60-µm diameter. CONCLUSIONS: As the normal fiber size of a human muscle fiber is 40 to 60 µm, this suggests that DTI is a sensitive tool to monitor muscle atrophy, but may be limited in measurements of muscle with larger fibers. Magn Reson Med 80:317-329, 2018. © 2017 International Society for Magnetic Resonance in Medicine.


Subject(s)
Diffusion Tensor Imaging , Muscle Fibers, Skeletal/pathology , Muscle, Skeletal/diagnostic imaging , Animals , Anisotropy , Computer Simulation , Diffusion Magnetic Resonance Imaging , Humans , Linear Models , Models, Theoretical , Monte Carlo Method , Muscle, Skeletal/pathology , Muscular Atrophy/diagnostic imaging , Nonlinear Dynamics , Normal Distribution , Rats
3.
Biophys J ; 107(10): 2345-51, 2014 Nov 18.
Article in English | MEDLINE | ID: mdl-25418303

ABSTRACT

Models of biological diffusion-reaction systems require accurate classification of the underlying diffusive dynamics (e.g., Fickian, subdiffusive, or superdiffusive). We use a renormalization group operator to identify the anomalous (non-Fickian) diffusion behavior from a short trajectory of a single molecule. The method provides quantitative information about the underlying stochastic process, including its anomalous scaling exponent. The classification algorithm is first validated on simulated trajectories of known scaling. Then it is applied to experimental trajectories of microspheres diffusing in cytoplasm, revealing heterogeneous diffusive dynamics. The simplicity and robustness of this classification algorithm makes it an effective tool for analysis of rare stochastic events that occur in complex biological systems.


Subject(s)
Diffusion , Models, Biological , Algorithms , Animals , Biological Transport , Oocytes/metabolism , Stochastic Processes , Xenopus
4.
Biophys J ; 104(8): 1652-60, 2013 Apr 16.
Article in English | MEDLINE | ID: mdl-23601312

ABSTRACT

The crowded intracellular environment poses a formidable challenge to experimental and theoretical analyses of intracellular transport mechanisms. Our measurements of single-particle trajectories in cytoplasm and their random-walk interpretations elucidate two of these mechanisms: molecular diffusion in crowded environments and cytoskeletal transport along microtubules. We employed acousto-optic deflector microscopy to map out the three-dimensional trajectories of microspheres migrating in the cytosolic fraction of a cellular extract. Classical Brownian motion (BM), continuous time random walk, and fractional BM were alternatively used to represent these trajectories. The comparison of the experimental and numerical data demonstrates that cytoskeletal transport along microtubules and diffusion in the cytosolic fraction exhibit anomalous (nonFickian) behavior and posses statistically distinct signatures. Among the three random-walk models used, continuous time random walk provides the best representation of diffusion, whereas microtubular transport is accurately modeled with fractional BM.


Subject(s)
Cytoplasm/metabolism , Microspheres , Animals , Biological Transport, Active , Diffusion , Microtubules/metabolism , Models, Biological , Motion , Xenopus
SELECTION OF CITATIONS
SEARCH DETAIL