An Imaging Flow Cytometry Protocol for Studying Immunoregulatory Receptor-Mediated Regulation of Phagocytosis

2021 ◽  
pp. 201-216
Author(s):  
Myron A. Zwozdesky ◽  
Chenjie Fei ◽  
James L. Stafford
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yersultan Mirasbekov ◽  
Adina Zhumakhanova ◽  
Almira Zhantuyakova ◽  
Kuanysh Sarkytbayev ◽  
Dmitry V. Malashenkov ◽  
...  

AbstractA machine learning approach was employed to detect and quantify Microcystis colonial morphospecies using FlowCAM-based imaging flow cytometry. The system was trained and tested using samples from a long-term mesocosm experiment (LMWE, Central Jutland, Denmark). The statistical validation of the classification approaches was performed using Hellinger distances, Bray–Curtis dissimilarity, and Kullback–Leibler divergence. The semi-automatic classification based on well-balanced training sets from Microcystis seasonal bloom provided a high level of intergeneric accuracy (96–100%) but relatively low intrageneric accuracy (67–78%). Our results provide a proof-of-concept of how machine learning approaches can be applied to analyze the colonial microalgae. This approach allowed to evaluate Microcystis seasonal bloom in individual mesocosms with high level of temporal and spatial resolution. The observation that some Microcystis morphotypes completely disappeared and re-appeared along the mesocosm experiment timeline supports the hypothesis of the main transition pathways of colonial Microcystis morphoforms. We demonstrated that significant changes in the training sets with colonial images required for accurate classification of Microcystis spp. from time points differed by only two weeks due to Microcystis high phenotypic heterogeneity during the bloom. We conclude that automatic methods not only allow a performance level of human taxonomist, and thus be a valuable time-saving tool in the routine-like identification of colonial phytoplankton taxa, but also can be applied to increase temporal and spatial resolution of the study.


Cell Reports ◽  
2021 ◽  
Vol 34 (10) ◽  
pp. 108824
Author(s):  
Gregor Holzner ◽  
Bogdan Mateescu ◽  
Daniel van Leeuwen ◽  
Gea Cereghetti ◽  
Reinhard Dechant ◽  
...  

Biomedicines ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 124
Author(s):  
Jaco Botha ◽  
Haley R. Pugsley ◽  
Aase Handberg

Flow cytometry remains a commonly used methodology due to its ability to characterise multiple parameters on single particles in a high-throughput manner. In order to address limitations with lacking sensitivity of conventional flow cytometry to characterise extracellular vesicles (EVs), novel, highly sensitive platforms, such as high-resolution and imaging flow cytometers, have been developed. We provided comparative benchmarks of a conventional FACS Aria III, a high-resolution Apogee A60 Micro-PLUS and the ImageStream X Mk II imaging flow cytometry platform. Nanospheres were used to systematically characterise the abilities of each platform to detect and quantify populations with different sizes, refractive indices and fluorescence properties, and the repeatability in concentration determinations was reported for each population. We evaluated the ability of the three platforms to detect different EV phenotypes in blood plasma and the intra-day, inter-day and global variabilities in determining EV concentrations. By applying this or similar methodology to characterise methods, researchers would be able to make informed decisions on choice of platforms and thereby be able to match suitable flow cytometry platforms with projects based on the needs of each individual project. This would greatly contribute to improving the robustness and reproducibility of EV studies.


2009 ◽  
Vol 347 (1-2) ◽  
pp. 79-86 ◽  
Author(s):  
Fariyal Ahmed ◽  
Sherree Friend ◽  
Thaddeus C. George ◽  
Natasha Barteneva ◽  
Judy Lieberman

2015 ◽  
Vol 87 (12) ◽  
pp. 1070-1078 ◽  
Author(s):  
Matus Durdik ◽  
Pavol Kosik ◽  
Jan Gursky ◽  
Lenka Vokalova ◽  
Eva Markova ◽  
...  

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