Literature DB >> 33895013

Toward Deep Biophysical Cytometry: Prospects and Challenges.

Kelvin C M Lee1, Jochen Guck2, Keisuke Goda3, Kevin K Tsia4.   

Abstract

The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  biomolecular basis; biophysical cytometry; deep learning; multimodal cytometry; standardization

Mesh:

Substances:

Year:  2021        PMID: 33895013     DOI: 10.1016/j.tibtech.2021.03.006

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN: 0167-7799            Impact factor:   19.536


  3 in total

1.  Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry.

Authors:  Carlos Honrado; Armita Salahi; Sara J Adair; John H Moore; Todd W Bauer; Nathan S Swami
Journal:  Lab Chip       Date:  2022-09-27       Impact factor: 7.517

2.  Modified Red Blood Cells as Multimodal Standards for Benchmarking Single-Cell Cytometry and Separation Based on Electrical Physiology.

Authors:  Armita Salahi; Carlos Honrado; Aditya Rane; Federica Caselli; Nathan S Swami
Journal:  Anal Chem       Date:  2022-02-02       Impact factor: 6.986

3.  Multi-angle pulse shape detection of scattered light in flow cytometry for label-free cell cycle classification.

Authors:  Claudia Giesecke-Thiel; Toralf Kaiser; Daniel Kage; Kerstin Heinrich; Konrad V Volkmann; Jenny Kirsch; Kristen Feher
Journal:  Commun Biol       Date:  2021-09-30
  3 in total

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