scholarly journals Time-lapse lens-free imaging of cell migration in diverse physical microenvironments

Lab on a Chip ◽  
2016 ◽  
Vol 16 (17) ◽  
pp. 3304-3316 ◽  
Author(s):  
Evelien Mathieu ◽  
Colin D. Paul ◽  
Richard Stahl ◽  
Geert Vanmeerbeeck ◽  
Veerle Reumers ◽  
...  
Keyword(s):  
Cell Migration ◽  
Live Cell Imaging ◽  
Phase Contrast ◽  
Cell Imaging ◽  
Time Lapse ◽  
Live Cell ◽  
Phase Contrast Microscopy ◽  
Contrast Microscopy ◽  
Coherent Illumination

Lens-free imaging using coherent illumination is established as an inexpensive and reliable alternative to conventional phase contrast microscopy for live-cell imaging applications.

Autofocusing in digital holographic phase contrast microscopy on pure phase objects for live cell imaging

2008 ◽  
Vol 47 (19) ◽  
pp. D176 ◽  
Author(s):  
Patrik Langehanenberg ◽  
Björn Kemper ◽  
Dieter Dirksen ◽  
Gert von Bally
Keyword(s):  
Live Cell Imaging ◽  
Phase Contrast ◽  
Cell Imaging ◽  
Live Cell ◽  
Phase Contrast Microscopy ◽  
Pure Phase ◽  
Contrast Microscopy

In vitro Time-lapse Live-Cell Imaging to Explore Cell Migration toward the Organ of Corti

10.3791/61947 ◽  
2020 ◽  
Author(s):  
Jeong-Eun Park ◽  
Su Hoon Lee ◽  
Dong Jun Park ◽  
Young Joon Seo ◽  
Sung Kyun Kim
Keyword(s):  
Cell Migration ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Organ Of Corti ◽  
Time Lapse ◽  
Live Cell

scholarly journals Deep learning pipeline for cell edge segmentation of time-lapse live cell images

2017 ◽  
Author(s):  
Chuangqi Wang ◽  
Xitong Zhang ◽  
Hee June Choi ◽  
Bolun Lin ◽  
Yudong Yu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Live Cell Imaging ◽  
Phase Contrast ◽  
Deep Neural Networks ◽  
Cell Imaging ◽  
Time Lapse ◽  
Live Cell ◽  
Live Cells ◽  
Quantitative Analyses

AbstractQuantitative live cell imaging has been widely used to study various dynamical processes in cell biology. Phase contrast microscopy is a popular imaging modality for live cell imaging since it does not require labeling and cause any phototoxicity to live cells. However, phase contrast images have posed significant challenges for accurate image segmentation due to complex image features. Fluorescence live cell imaging has also been used to monitor the dynamics of specific molecules in live cells. But unlike immunofluorescence imaging, fluorescence live cell images are highly prone to noise, low contrast, and uneven illumination. These often lead to erroneous cell segmentation, hindering quantitative analyses of dynamical cellular processes. Although deep learning has been successfully applied in image segmentation by automatically learning hierarchical features directly from raw data, it typically requires large datasets and high computational cost to train deep neural networks. These make it challenging to apply deep learning in routine laboratory settings. In this paper, we evaluate a deep learning-based segmentation pipeline for time-lapse live cell movies, which uses small efforts to prepare the training set by leveraging the temporal coherence of time-lapse image sequences. We train deep neural networks using a small portion of images in the movies, and then predict cell edges for the entire image frames of the same movies. To further increase segmentation accuracy using small numbers of training frames, we integrate VGG16 pretrained model with the U-Net structure (VGG16-U-Net) for neural network training. Using live cell movies from phase contrast, Total Internal Reflection Fluorescence (TIRF), and spinning disk confocal microscopes, we demonstrate that the labeling of cell edges in small portions (5∼10%) can provide enough training data for the deep learning segmentation. Particularly, VGG16-U-Net produces significantly more accurate segmentation than U-Net by increasing the recall performance. We expect that our deep learning segmentation pipeline will facilitate quantitative analyses of challenging high-resolution live cell movies.

scholarly journals Time-Lapse, Live-Cell Imaging of Potassium Efflux in Cell Exposed to Nanosecond Pulsed Electric Fields

2021 ◽  
Vol 120 (3) ◽  
pp. 223a
Author(s):  
Flavia Mazzarda ◽  
Esin B. Sozer ◽  
Julia L. Pittaluga ◽  
Claudia Muratori ◽  
P. Thomas Vernier
Keyword(s):  
Electric Fields ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Pulsed Electric Fields ◽  
Time Lapse ◽  
Live Cell ◽  
Potassium Efflux ◽  
Nanosecond Pulsed Electric Fields

Dye selection for live cell imaging of intact siRNA

2012 ◽  
Vol 393 (1-2) ◽  
pp. 23-35 ◽  
Author(s):  
Markus Hirsch ◽  
Dennis Strand ◽  
Mark Helm
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Fluorescent Dyes ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Time Lapse ◽  
Live Cell ◽  
High Yield ◽  
Ph Variation ◽  
Rnai Efficiency

Abstract Investigations into the fate of small interfering RNA (siRNA) after transfection may unravel new ways to improve RNA interference (RNAi) efficiency. Because intracellular degradation of RNA may prevent reliable observation of fluorescence-labeled siRNA, new tools for fluorescence microscopy are warranted to cover the considerable duration of the RNAi effect. Here, the characterization and application of new fluorescence resonance energy transfer (FRET) dye pairs for sensing the integrity of duplex siRNA is reported, which allows an assessment of the degradation status of an siRNA cell population by live cell imaging. A panel of high-yield fluorescent dyes has been investigated for their suitability as FRET pairs for the investigation of RNA inside the cell. Nine dyes in 13 FRET pairs were evaluated based on the performance in assays of photostability, cross-excitation, bleed-through, as well as on quantified changes of fluorescence as a consequence of, e.g., RNA strand hybridization and pH variation. The Atto488/Atto590 FRET pair has been applied to live cell imaging, and has revealed first aspects of unusual trafficking of intact siRNA. A time-lapse study showed highly dynamic movement of siRNA in large perinuclear structures. These and the resulting optimized FRET labeled siRNA are expected to have significant impact on future observations of labeled RNAs in living cells.

scholarly journals Time-lapse live cell imaging to monitor doxorubicin release from DNA origami nanostructures

2018 ◽  
Vol 6 (11) ◽  
pp. 1605-1612 ◽  
Author(s):  
Yun Zeng ◽  
Jiajun Liu ◽  
Shuo Yang ◽  
Wenyan Liu ◽  
Liang Xu ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Time Lapse ◽  
Dna Origami ◽  
Live Cell ◽  
Doxorubicin Release

DNA origami nanostructures can serve as a promising carrier for drug delivery due to the outstanding programmability and biocompatibility.

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