scholarly journals Biometric Image Analysis for Quantitation of Dividing Platelets

Micromachines ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Hyun-Jeong Kim ◽  
Yejin Song ◽  
Jaewoo Song
Keyword(s):  
Image Analysis ◽  
Cell Tracking ◽  
Relative Number ◽  
Future Application ◽  
Semisolid Medium ◽  
Color Combination ◽  
Dye Dilution ◽  
Flow Cytometric ◽  
Dilution Assay ◽  
Diffusive Movement

(1) Background: Quantification of platelet division is challenging because automated Coulter cell counters produce equivocal platelet counts. (2) Methods: We applied the flow cytometric cell tracking dye dilution assay as a popular immunological method to evaluate lymphocyte proliferation to prove and quantitate platelet division. We also devised a method relying on platelet culture in a semisolid medium which enabled dividing platelets to be identified by limiting the diffusive movement of platelets. Mixing platelets of different labeling colors in semisolid medium and counting the platelet doublets of each color combination enabled us to prove and quantitate platelet division. (3) Results: The tracking dye dilution assay revealed that 75.5 to 85.6% of platelets were dividing after 20 hours in culture. Platelets labeled with two different tracking dyes were mixed and cultured in semisolid medium for differential doublet counting. We counted platelet singlets and doublets of each color and color combination using confocal microscopy after six hours of culture and compared the relative number of two-colored doublets with binomial prediction to prove platelet division (P < 0.01). Division was suppressed by taxol, nocodazole, or cytochalasin D treatment. We derived a formula for determining the fraction of dividing platelets using the numbers of singlets and doublets of each color and color combination. The platelet division fraction ranged from 8.8 to 17.5%. (4) Conclusion: We successfully measured platelet division using a simple biometric image analysis method with possible future application to microfluidic devices.

scholarly journals Application of Digital Image Analysis and Flow Cytometry To Enumerate Marine Viruses Stained with SYBR Gold

2001 ◽  
Vol 67 (2) ◽  
pp. 539-545 ◽  
Author(s):  
Feng Chen ◽  
Jing-rang Lu ◽  
Brian J. Binder ◽  
Ying-chun Liu ◽  
Robert E. Hodson
Keyword(s):  
Flow Cytometry ◽  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Flow Cytometric Analysis ◽  
Epifluorescence Microscopy ◽  
Flow Cytometric ◽  
Viral Particles ◽  
Sybr Gold ◽  
Nucleic Acid Stain

ABSTRACT A novel nucleic acid stain, SYBR Gold, was used to stain marine viral particles in various types of samples. Viral particles stained with SYBR Gold yielded bright and stable fluorescent signals that could be detected by a cooled charge-coupled device camera or by flow cytometry. The fluorescent signal strength of SYBR Gold-stained viruses was about twice that of SYBR Green I-stained viruses. Digital images of SYBR Gold-stained viral particles were processed to enumerate the concentration of viral particles by using digital image analysis software. Estimates of viral concentration based on digitized images were 1.3 times higher than those based on direct counting by epifluorescence microscopy. Direct epifluorescence counts of SYBR Gold-stained viral particles were in turn about 1.34 times higher than those estimated by the transmission electron microscope method. Bacteriophage lysates stained with SYBR Gold formed a distinct population in flow cytometric signatures. Flow cytometric analysis revealed at least four viral subpopulations for a Lake Erie sample and two subpopulations for a Georgia coastal sample. Flow cytometry-based viral counts for various types of samples averaged 1.1 times higher than direct epifluorescence microscopic counts. The potential application of digital image analysis and flow cytometry for rapid and accurate measurement of viral abundance in aquatic environments is discussed.

Characterization of the Morphological State of a Culture of Filamentous Microorganisms Using Digital Image Analysis

2015 ◽  
Vol 18 ◽  
pp. 192-198
Author(s):  
Ema Hrbková ◽  
Ludvik Hasal ◽  
Jan Náhlík ◽  
Jan Mareš ◽  
Pavel Hrnčiřík
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Morphological Changes ◽  
Future Application ◽  
Filamentous Microorganisms ◽  
Pharmaceutical Production ◽  
The Given ◽  
Morphological State

The paper examines the potential of the application of digital image analysis for the monitoring of morphological changes in cultures of filamentous microorganisms used in pharmaceutical production processes. First, an overview of selected methods and techniques used in digital image analysis is given with respect to their possible application in this project. This section also includes the description of corresponding software tools used in the presented study. The potential of the proposed approach is then demonstrated using a set of microscopic images from two typical productive cultivations. Finally, the obtained results are discussed within the context of a potential future application of these techniques for advanced monitoring of the given productive bioprocess.

scholarly journals Quantitative analysis of cell proliferation by a dye dilution assay: Application to cell lines and cocultures

2017 ◽  
Vol 91 (7) ◽  
pp. 704-712 ◽  
Author(s):  
Soobin Chung ◽  
Seol-Hee Kim ◽  
Yuri Seo ◽  
Sook-Kyung Kim ◽  
Ji Youn Lee
Keyword(s):  
Cell Proliferation ◽  
Quantitative Analysis ◽  
Cell Lines ◽  
Dye Dilution ◽  
Dilution Assay

scholarly journals Cell Tracking Profiler – a user-driven analysis framework for evaluating 4D live-cell imaging data

2020 ◽  
Vol 133 (22) ◽  
pp. jcs241422
Author(s):  
Claire Mitchell ◽  
Lauryanne Caroff ◽  
Jose Alonso Solis-Lemus ◽  
Constantino Carlos Reyes-Aldasoro ◽  
Alessandra Vigilante ◽  
...  
Keyword(s):  
Image Analysis ◽  
Cell Tracking ◽  
Cell Function ◽  
Ground Truth ◽  
Time Lapse ◽  
Automated Image Analysis ◽  
Imaging Data ◽  
Cell Behaviour ◽  
Muscle Stem Cell

ABSTRACTAccurate measurements of cell morphology and behaviour are fundamentally important for understanding how disease, molecules and drugs affect cell function in vivo. Here, by using muscle stem cell (muSC) responses to injury in zebrafish as our biological paradigm, we established a ‘ground truth’ for muSC behaviour. This revealed that segmentation and tracking algorithms from commonly used programs are error-prone, leading us to develop a fast semi-automated image analysis pipeline that allows user-defined parameters for segmentation and correction of cell tracking. Cell Tracking Profiler (CTP) is a package that runs two existing programs, HK Means and Phagosight within the Icy image analysis suite, to enable user-managed cell tracking from 3D time-lapse datasets to provide measures of cell shape and movement. We demonstrate how CTP can be used to reveal changes to cell behaviour of muSCs in response to manipulation of the cell cytoskeleton by small-molecule inhibitors. CTP and the associated tools we have developed for analysis of outputs thus provide a powerful framework for analysing complex cell behaviour in vivo from 4D datasets that are not amenable to straightforward analysis.

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