Publications by authors named "Feng Wei Yang"

6 Publications

  • Page 1 of 1

Investigating Optimal Time Step Intervals of Imaging for Data Quality through a Novel Fully-Automated Cell Tracking Approach.

J Imaging 2020 Jul 7;6(7). Epub 2020 Jul 7.

School of Mathematical and Physical Sciences, Department of Mathematics, University of Sussex, Brighton BN1 9QH, UK.

Computer-based fully-automated cell tracking is becoming increasingly important in cell biology, since it provides unrivalled capacity and efficiency for the analysis of large datasets. However, automatic cell tracking's lack of superior pattern recognition and error-handling capability compared to its human manual tracking counterpart inspired decades-long research. Enormous efforts have been made in developing advanced cell tracking packages and software algorithms. Typical research in this field focuses on dealing with existing data and finding a best solution. Here, we investigate a novel approach where the quality of data acquisition could help improve the accuracy of cell tracking algorithms and vice-versa. Generally speaking, when tracking cell movement, the more frequent the images are taken, the more accurate cells are tracked and, yet, issues such as damage to cells due to light intensity, overheating in equipment, as well as the size of the data prevent a constant data streaming. Hence, a trade-off between the frequency at which data images are collected and the accuracy of the cell tracking algorithms needs to be studied. In this paper, we look at the effects of different choices of the time step interval (i.e., the frequency of data acquisition) within the microscope to our existing cell tracking algorithms. We generate several experimental data sets where the true outcomes are known (i.e., the direction of cell migration) by either using an effective chemoattractant or employing no-chemoattractant. We specify a relatively short time step interval (i.e., 30 s) between pictures that are taken at the data generational stage, so that, later on, we may choose some portion of the images to produce datasets with different time step intervals, such as 1 min, 2 min, and so on. We evaluate the accuracy of our cell tracking algorithms to illustrate the effects of these different time step intervals. We establish that there exist certain relationships between the tracking accuracy and the time step interval associated with experimental microscope data acquisition. We perform fully-automatic adaptive cell tracking on multiple datasets, to identify optimal time step intervals for data acquisition, while at the same time demonstrating the performance of the computer cell tracking algorithms.
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http://dx.doi.org/10.3390/jimaging6070066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321081PMC
July 2020

Implications for First-Order Cosmological Phase Transitions from the Third LIGO-Virgo Observing Run.

Phys Rev Lett 2021 Apr;126(15):151301

Department of Physics and Astronomy, University of Utah, Salt Lake City, Utah 84112, USA.

We place constraints on the normalized energy density in gravitational waves from first-order strong phase transitions using data from Advanced LIGO and Virgo's first, second, and third observing runs. First, adopting a broken power law model, we place 95% confidence level upper limits simultaneously on the gravitational-wave energy density at 25 Hz from unresolved compact binary mergers, Ω_{CBC}<6.1×10^{-9}, and strong first-order phase transitions, Ω_{BPL}<4.4×10^{-9}. The inclusion of the former is necessary since we expect this astrophysical signal to be the foreground of any detected spectrum. We then consider two more complex phenomenological models, limiting at 25 Hz the gravitational-wave background due to bubble collisions to Ω_{pt}<5.0×10^{-9} and the background due to sound waves to Ω_{pt}<5.8×10^{-9} at 95% confidence level for phase transitions occurring at temperatures above 10^{8}  GeV.
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http://dx.doi.org/10.1103/PhysRevLett.126.151301DOI Listing
April 2021

Cell migration through three-dimensional confining pores: speed accelerations by deformation and recoil of the nucleus.

Philos Trans R Soc Lond B Biol Sci 2019 08 1;374(1779):20180225. Epub 2019 Jul 1.

Department of Cell Biology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands.

Directional cell migration in dense three-dimensional (3D) environments critically depends upon shape adaptation and is impeded depending on the size and rigidity of the nucleus. Accordingly, the nucleus is primarily understood as a physical obstacle; however, its pro-migratory functions by stepwise deformation and reshaping remain unclear. Using atomic force spectroscopy, time-lapse fluorescence microscopy and shape change analysis tools, we determined the nuclear size, deformability, morphology and shape change of HT1080 fibrosarcoma cells expressing the Fucci cell cycle indicator or being pre-treated with chromatin-decondensating agent TSA. We show oscillating peak accelerations during migration through 3D collagen matrices and microdevices that occur during shape reversion of deformed nuclei (recoil), and increase with confinement. During G1 cell-cycle phase, nucleus stiffness was increased and yielded further increased speed fluctuations together with sustained cell migration rates in confinement when compared to interphase populations or to periods of intrinsic nuclear softening in the S/G2 cell-cycle phase. Likewise, nuclear softening by pharmacological chromatin decondensation or after lamin A/C depletion reduced peak oscillations in confinement. In conclusion, deformation and recoil of the stiff nucleus contributes to saltatory locomotion in dense tissues. This article is part of a discussion meeting issue 'Forces in cancer: interdisciplinary approaches in tumour mechanobiology'.
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http://dx.doi.org/10.1098/rstb.2018.0225DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6627020PMC
August 2019

A computational framework for particle and whole cell tracking applied to a real biological dataset.

J Biomech 2016 05 15;49(8):1290-1304. Epub 2016 Feb 15.

Department of Mathematics, University of Sussex, UK. Electronic address:

Cell tracking is becoming increasingly important in cell biology as it provides a valuable tool for analysing experimental data and hence furthering our understanding of dynamic cellular phenomena. The advent of high-throughput, high-resolution microscopy and imaging techniques means that a wealth of large data is routinely generated in many laboratories. Due to the sheer magnitude of the data involved manual tracking is often cumbersome and the development of computer algorithms for automated cell tracking is thus highly desirable. In this work, we describe two approaches for automated cell tracking. Firstly, we consider particle tracking. We propose a few segmentation techniques for the detection of cells migrating in a non-uniform background, centroids of the segmented cells are then calculated and linked from frame to frame via a nearest-neighbour approach. Secondly, we consider the problem of whole cell tracking in which one wishes to reconstruct in time whole cell morphologies. Our approach is based on fitting a mathematical model to the experimental imaging data with the goal being that the physics encoded in the model is reflected in the reconstructed data. The resulting mathematical problem involves the optimal control of a phase-field formulation of a geometric evolution law. Efficient approximation of this challenging optimal control problem is achieved via advanced numerical methods for the solution of semilinear parabolic partial differential equations (PDEs) coupled with parallelisation and adaptive resolution techniques. Along with a detailed description of our algorithms, a number of simulation results are reported on. We focus on illustrating the effectivity of our approaches by applying the algorithms to the tracking of migrating cells in a dataset which reflects many of the challenges typically encountered in microscopy data.
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http://dx.doi.org/10.1016/j.jbiomech.2016.02.008DOI Listing
May 2016

Protease-activated receptor (PAR)1, PAR2 and PAR4 expressions in esophageal squamous cell carcinoma.

Dongwuxue Yanjiu 2014 Sep;35(5):420-5

Kunming Medical University, Kunming 650500, China.

Here, we used reverse transcription-PCR (RT-PCR) and western blot to detect protease-activated receptor (PAR) 1, PAR 2 and PAR 4 expression in cancer tissues and cell lines of esophageal squamous cell carcinoma, and investigated the co-relationship between PAR expression and clinic-pathological data for esophageal cancer. The methylation of PAR4 gene promoter involved in esophageal carcinoma was also analyzed. By comparing the mRNA expressions of normal esophageal tissue and human esophageal epithelial cells (HEEpiC), we found that among the 28 cases of esophageal squamous cell carcinoma, PAR1 (60%) and PAR2 (71%) were elevated in 17 and 20 cases, respectively, and PAR4 (68%) expression was lowered in 19 cases. Whereas, in human esophageal squamous cells (TE-1 and TE-10), PAR1 and PAR2 expression was increased but PAR4 was decreased. Combined with clinical data, the expression of PAR1 in poorly differentiated (P=0.016) and middle and lower parts of the esophagus (P=0.016) was higher; expression of PAR4 in poorly differentiated carcinoma was lower (P=0.049). Regarding TE-1 and TE-10 protein expression, we found that in randomized esophageal carcinoma, PAR1 (P=0.027) and PAR2 (P=0.039) expressions were increased, but lowered for PAR4 (P=0.0001). In HEEpiC, TE-1, TE-10, esophageal and normal esophagus tissue samples (case No. 7), the frequency of methylation at the 19 CpG loci of PAR4 was 35.4%, 95.2%, 83.8%, 62.6% and 48.2%, respectively. Our results indicate that the expression of PAR1 and PAR2 in esophageal squamous cell carcinoma is increased but PAR4 is decreased. Hypermethylation of the promoter of the PAR4 gene may contribute to reduced expression of PAR4 in esophageal squamous cell carcinoma.
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http://dx.doi.org/10.13918/j.issn.2095-8137.2014.5.420DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4790359PMC
September 2014
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