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Published on: March 28, 2014
Illuminating Immunity: A Systematic Review of Immune Cell Autofluorescence.
Aline Knab1, Caroline Giardina2,3, Shane T Grey3,4
1Graduate School of Biomedical Engineering, University of New South Wales, Sydney, New South Wales, Australia.
Autofluorescence, a label-free method, offers insights into cell identity for immunophenotyping. Further research is needed to standardize methods for clinical applications.
Area of Science:
- Immunology
- Cell Biology
- Biophysics
Background:
- Immunophenotyping is crucial for diagnosis and prognosis but is complex and costly.
- Autofluorescence provides label-free cellular information, but its use in immunophenotyping is inconsistently researched.
- A systematic review is needed to consolidate evidence on autofluorescence for immunophenotyping.
Purpose of the Study:
- To systematically review and synthesize existing evidence on the application of autofluorescence in immunophenotyping.
- To identify immune cell types most frequently studied using autofluorescence.
- To highlight challenges and recommendations for translating autofluorescence findings into clinical practice.
Main Methods:
- Systematic literature search and review of full-text articles.
- Inclusion of 83 full texts reporting on autofluorescence for immunophenotyping.
- Categorization of studies based on immune cell populations investigated.
Main Results:
- Neutrophils (20 papers) and macrophages (22 papers) were the most studied cell types.
- Evidence spans various immune cells including monocytes, microglia, dendritic cells, mast cells, granulocytes, eosinophils, NK cells, and uncategorized populations.
- Significant heterogeneity exists in research methodologies and reporting.
Conclusions:
- Autofluorescence shows potential as a label-free tool for immunophenotyping.
- Standardization of reproducible methods, clear reporting of optical parameters, and focus on clinical samples are essential for clinical translation.
- Further research is required to overcome heterogeneity and establish robust clinical applications.
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