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Unravelling Plasma Extracellular Vesicle Diversity With Optimised Spectral Flow Cytometry [PDF]
Journal of Extracellular BiologyExtracellular vesicles (EVs) are crucial for intercellular communication and are found in various biological fluids. The identification and immunophenotyping of such small particles continue to pose significant challenges.
Daniela Boselli +10 more
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The in vitro micronucleus assay using imaging flow cytometry and deep learning
npj Systems Biology and Applications, 2021 The in vitro micronucleus (MN) assay is a well-established assay for quantification of DNA damage, and is required by regulatory bodies worldwide to screen chemicals for genetic toxicity.
Matthew A. Rodrigues +6 more
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Communications Biology, 2021 Combining multi-angle (MA) light scatter detection with time-resolved pulse shape (PS) analysis for flow cytometry (FC), Kage et al. report MAPS-FC method for cell cycle analysis.
Daniel Kage +6 more
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An Early Myelosuppression in the Acute Mouse Sepsis Is Partly Outcome-Dependent
Frontiers in Immunology, 2021 Adult hematopoietic stem and progenitor cells (HSPCs) respond to bacterial infections by expansion to myeloid cells. Sepsis impairs this process by suppressing differentiation of stem cells subsequently contributing to an ineffective immune response ...
Tomasz Skirecki +6 more
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GenePattern flow cytometry suite [PDF]
, 2013 Background: Traditional flow cytometry data analysis is largely based on interactive and time consuming analysis of series two dimensional representations of up to 20 dimensional data.
Barsky, Aaron +13 more
core +4 more sources
Scientific Reports, 2021 In conventional flowcytometry one detector (primary) is dedicated for one fluorochrome. However, photons usually end up in other detectors too (fluorescence spillover).
Debajit Bhowmick +4 more
doaj +1 more source
Engineering in Life Sciences, 2022 Aseptic cell sorting is challenging, especially when a flow‐cytometric cell sorter is not operated in a sterile environment. The sheath fluid system of a cell sorter may be contaminated with germs such as bacteria, yeasts, viruses, or fungi.
Jenny Kirsch +6 more
doaj +1 more source
Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry [PDF]
, 2019 Deep learning has achieved spectacular performance in image and speech recognition and synthesis. It outperforms other machine learning algorithms in problems where large amounts of data are available.
Chen, Claire Lifan +5 more
core +2 more sources
A biology-driven deep generative model for cell-type annotation in cytometry [PDF]
, 2022 Cytometry enables precise single-cell phenotyping within heterogeneous populations. These cell types are traditionally annotated via manual gating, but this method suffers from a lack of reproducibility and sensitivity to batch-effect. Also, the most recent cytometers - spectral flow or mass cytometers - create rich and high-dimensional data whose ...
arxiv +1 more source
Flow cytometric characterization and clinical outcome of CD4+ T-cell lymphoma in dogs: 67 cases. [PDF]
, 2014 BackgroundCanine T-cell lymphoma (TCL) is conventionally considered an aggressive disease, but some forms are histologically and clinically indolent. CD4 TCL is reported to be the most common subtype of TCL.
Avery, AC +8 more
core +2 more sources