Diffusion Mapping of Eosinophil‐Activation State
| Autor: | Justyna Piasecka, Paul Rees, Catherine A. Thornton, Huw D. Summers |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Eotaxin Histology Cell Endogeny Pathology and Forensic Medicine Leukocyte Count 03 medical and health sciences 0302 clinical medicine Eosinophil activation medicine Humans eosinophil diffusion maps Chemistry Original Articles Cell Biology imaging flow cytometry Eosinophil Flow Cytometry Cell biology Eosinophils multivariate analysis 030104 developmental biology medicine.anatomical_structure 030220 oncology & carcinogenesis Original Article Cell activation Cytometry Intracellular |
| Zdroj: | Cytometry |
| ISSN: | 1552-4930 1552-4922 |
| DOI: | 10.1002/cyto.a.23884 |
| Popis: | Eosinophils are granular leukocytes that play a role in mediating inflammatory responses linked to infection and allergic disease. Their activation during an immune response triggers spatial reorganization and eventual cargo release from intracellular granules. Understanding this process is important in diagnosing eosinophilic disorders and in assessing treatment efficacy; however, current protocols are limited to simply quantifying the number of eosinophils within a blood sample. Given that high optical absorption and scattering by the granular structure of these cells lead to marked image features, the physical changes that occur during activation should be trackable using image analysis. Here, we present a study in which imaging flow cytometry is used to quantify eosinophil activation state, based on the extraction of 85 distinct spatial features from dark‐field images formed by light scattered orthogonally to the illuminating beam. We apply diffusion mapping, a time inference method that orders cells on a trajectory based on similar image features. Analysis of exogenous cell activation using eotaxin and endogenous activation in donor samples with elevated eosinophil counts shows that cell position along the diffusion‐path line correlates with activation level (99% confidence level). Thus, the diffusion mapping provides an activation metric for each cell. Assessment of activated and control populations using both this spatial image‐based, activation score and the integrated side‐scatter intensity shows an improved Fisher discriminant ratio r d = 0.7 for the multivariate technique compared with an r d = 0.47 for the traditional whole‐cell scatter metric. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry. |
| Databáze: | OpenAIRE |
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