Label-Free Three-Dimensional Morphological Characterization of Cell Death Using Holographic Tomography

This study presents a novel label-free approach for characterizing cell death states, eliminating the need for complex molecular labeling that may yield artificial or ambiguous results due to technical limitations in microscope resolution. The proposed holographic tomography technique offers a label...

Full description

Saved in:
Bibliographic Details
Published inSensors (Basel, Switzerland) Vol. 24; no. 11; p. 3435
Main Authors Huang, Chung-Hsuan, Lai, Yun-Ju, Chen, Li-Nian, Hung, Yu-Hsuan, Tu, Han-Yen, Cheng, Chau-Jern
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 26.05.2024
MDPI
Subjects
Antibodies
Apoptosis
Autophagy
Biochemistry
Cadmium telluride
Cell Death
Cells
Cytoplasm
Ferroptosis
Flow cytometry
holographic tomography
Holography - methods
Humans
Imaging, Three-Dimensional - methods
Microscopy
Morphology
Neuroblastoma
Quantitative analysis
Quantum dots
Refractometry - methods
Stains & staining
three-dimensional morphology
Tomography
Tomography - methods
Germany
Taiwan
Canada
United States > US
cell death
three-dimensional morphology
holographic tomography
Online AccessGet full text

Cover

More Information
Summary:This study presents a novel label-free approach for characterizing cell death states, eliminating the need for complex molecular labeling that may yield artificial or ambiguous results due to technical limitations in microscope resolution. The proposed holographic tomography technique offers a label-free avenue for capturing precise three-dimensional (3D) refractive index morphologies of cells and directly analyzing cellular parameters like area, height, volume, and nucleus/cytoplasm ratio within the 3D cellular model. We showcase holographic tomography results illustrating various cell death types and elucidate distinctive refractive index correlations with specific cell morphologies complemented by biochemical assays to verify cell death states. These findings hold promise for advancing single cell state identification and diagnosis applications.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
These authors contributed equally to this work.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24113435