soft-matter/trackpy: Trackpy v0.5.0

Allan, Daniel; Caswell, Thomas A; Keim, Nathan C.; Wel, Casper M. van der; Verweij, Ruben W.

doi:10.5281/zenodo.4682814

Cited by 67 publications

(67 citation statements)

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“…First, the d f of sphere gels was determined from their radial distribution function, g(r 0 ). 38 Here, g(r 0 ) is computed from particle centroids using tools available in TRACKPY 39 and FREUD 40 Python libraries. g(r 0 ) describes the average number of particles at a distance r 0 from a basis particle, relative to that of an ideal gas.…”

Section: Box-counting Image Analysis To Compute Fractal Dimensionmentioning

confidence: 99%

Microstructure and elasticity of dilute gels of colloidal discoids

2022

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Section: Box-counting Image Analysis To Compute Fractal Dimensionmentioning

confidence: 99%

Microstructure and elasticity of dilute gels of colloidal discoids

2022

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“…The imaged volume is far from the sample boundaries to prevent edge effects. The particle centers are located and tracked using TrackPy [6], a python package based on the Crocker-Grier algorithm. We chose 55 particles at the center of the image for analysis, marked in red in Fig.…”

Section: Results On Experimental Datamentioning

confidence: 99%

“…Though enhancements to Crocker and Grier's original algorithm have been made, such as handling uniform flow [5,6], the fundamental requirement that particle displacement be far less than the inter-particle separation remains a significant limitation. This problem is particularly acute in 3D imaging due to limitations in the frame rate.…”

Section: Introductionmentioning

confidence: 99%

Improved tracking of particles with highly correlated motion

King¹,

Wang²,

Weitz³

et al. 2022

Preprint

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Despite significant advances in particle imaging technologies over the past two decades, few advances have been made in particle tracking, i.e. linking individual particle positions across time series data. The state-of-the-art tracking algorithm is highly effective for systems in which the particles behave mostly independently. However, these algorithms become inaccurate when particle motion is highly correlated, such as in dense or strongly interacting systems. Accurate particle tracking is essential in the study of the physics of dense colloids, such as the study of dislocation formation, nucleation, and shear transformations. Here, we present a new method for particle tracking that incorporates information about the correlated motion of the particles. We demonstrate significant improvement over the state-of-the-art tracking algorithm in simulated data on highly correlated systems.

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“…The .csv file was imported into Python and converted to a DataFrame. The mean speed of each phage particle were calculated using a custom MATLAB script and the mean square displacement (MSD) was calculated using a custom Python script based on TrackPy 52 .…”

Section: Methodsmentioning

confidence: 99%

Bacterial swarm-mediated phage transportation disrupts a biofilm inherently protected from phage penetration

et al. 2021

Preprint

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Phage therapy, i.e., the treatment of chronic bacterial infections by virus that kill bacteria has shown promise in combating antimicrobial resistance (AMR). A typical phage particle is around 100 times bigger than a typical antibiotic molecule. Due to larger size, a phage particle diffuses slower than an antibiotic molecule, and can get trapped in the polymeric mesh of biofilm matrix. We report that a swarm of Capnocytophaga gingivalis, a bacterium abundant in the human oral microbiota, can actively transport phages over long distances. By tracking fluorescently labeled lambda phages that do not infect C. gingivalis, we demonstrate active predator transport by a C. gingivalis swarm. As a result, the rate of disruption of the prey, i.e., an Escherichia coli colony increases 10 times. Production of curli fiber by a mature E. coli biofilm blocks the intercellular space and is known to inhibit the diffusion of phages within a biofilm. We find that C. gingivalis forms tunnels within the prey biofilm. When phages are actively delivered, curli fiber containing E. coli biofilms are no longer protected against phage infection. Our results demonstrate that active delivery of the predator by a self-propelled swarm might improve the pharmacokinetics of phage therapy. This can lead to the development of a tool to combat chronic AMR biofilms.

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soft-matter/trackpy: Trackpy v0.5.0

Cited by 67 publications

References 0 publications

Microstructure and elasticity of dilute gels of colloidal discoids

Microstructure and elasticity of dilute gels of colloidal discoids

Improved tracking of particles with highly correlated motion

Bacterial swarm-mediated phage transportation disrupts a biofilm inherently protected from phage penetration

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