scholarly journals Re‐evaluation of physical interaction between plant peroxisomes and other organelles using live‐cell imaging techniques

2019 ◽  
Author(s):  
Kazusato Oikawa ◽  
Makoto Hayashi ◽  
Yasuko Hayashi ◽  
Mikio Nishimura
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Imaging Techniques ◽  
Live Cell ◽  
Physical Interaction

scholarly journals Holotomography: refractive index as an intrinsic imaging contrast for 3-D label-free live cell imaging

2017 ◽  
Author(s):  
Doyeon Kim ◽  
SangYun Lee ◽  
Moosung Lee ◽  
JunTaek Oh ◽  
Su-A Yang ◽  
...  
Keyword(s):  
Refractive Index ◽  
Cell Biology ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Imaging Techniques ◽  
Live Cell ◽  
Label Free ◽  
Essential Information ◽  
Research Fields ◽  
Intrinsic Imaging

AbstractLive cell imaging provides essential information in the investigation of cell biology and related pathophysiology. Refractive index (RI) can serve as intrinsic optical imaging contrast for 3-D label-free and quantitative live cell imaging, and provide invaluable information to understand various dynamics of cells and tissues for the study of numerous fields. Recently significant advances have been made in imaging methods and analysis approaches utilizing RI, which are now being transferred to biological and medical research fields, providing novel approaches to investigate the pathophysiology of cells. To provide insight how RI can be used as an imaging contrast for imaging of biological specimens, here we provide the basic principle of RI-based imaging techniques and summarize recent progress on applications, ranging from microbiology, hematology, infectious diseases, hematology, and histopathology.

Mitochondria- and nucleolus-targeted copper(i) complexes with pyrazole-linked triphenylphosphine moieties for live cell imaging

The Analyst ◽  
2020 ◽  
Vol 145 (1) ◽  
pp. 83-90 ◽  
Author(s):  
Mayank Mayank ◽  
Richa Rani ◽  
Ashutosh Singh ◽  
Neha Garg ◽  
Navneet Kaur ◽  
...  
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Imaging Techniques ◽  
Live Cell ◽  
Single Experiment ◽  
Highly Efficient

We developed C1 and C2 metallo-complexes as highly efficient cell imaging tools. These complexes enabled us to visualize mitochondria and nucleolus in a single experiment via live cell imaging techniques.

Live Cell-Imaging Techniques for Analyses of Microtubules in Dictyostelium

2010 ◽  
pp. 341-357 ◽  
Author(s):  
Matthias Samereier ◽  
Irene Meyer ◽  
Michael P. Koonce ◽  
Ralph Gräf
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Imaging Techniques ◽  
Live Cell

Long-term live-cell imaging techniques for visualizing pavement cell morphogenesis

2020 ◽  
pp. 365-380
Author(s):  
Kumar Seerangan ◽  
Ruben van Spoordonk ◽  
Arun Sampathkumar ◽  
Ryan Christopher Eng
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Imaging Techniques ◽  
Live Cell ◽  
Cell Morphogenesis ◽  
Pavement Cell

scholarly journals PHi-C: deciphering Hi-C data into polymer dynamics

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Soya Shinkai ◽  
Masaki Nakagawa ◽  
Takeshi Sugawara ◽  
Yuichi Togashi ◽  
Hiroshi Ochiai ◽  
...  
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Simulation Method ◽  
Live Cell ◽  
Polymer Dynamics ◽  
Interaction Parameters ◽  
Physical Interaction ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Genome Features

Abstract Genomes are spatiotemporally organized within the cell nucleus. Genome-wide chromosome conformation capture (Hi-C) technologies have uncovered the 3D genome organization. Furthermore, live-cell imaging experiments have revealed that genomes are functional in 4D. Although computational modeling methods can convert 2D Hi-C data into population-averaged static 3D genome models, exploring 4D genome nature based on 2D Hi-C data remains lacking. Here, we describe a 4D simulation method, PHi-C (polymer dynamics deciphered from Hi-C data), that depicts 4D genome features from 2D Hi-C data by polymer modeling. PHi-C allows users to interpret 2D Hi-C data as physical interaction parameters within single chromosomes. The physical interaction parameters can then be used in the simulations and analyses to demonstrate dynamic characteristics of genomic loci and chromosomes as observed in live-cell imaging experiments. PHi-C is available at https://github.com/soyashinkai/PHi-C.

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