Cell Holograms
Cell Holograms - Related Videos
09:04
Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display
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Cited by 3 •
2020
We present a protocol to record a set of ultra-realistic full-color analog holograms, showing the same brightness, transparency, and homogeneous colors, on ultra-fine-grain silver-halide holographic emulsions for the fabrication of a dynamic holographic 3D display.
08:19
Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics
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Cited by 24 •
2009
Lensfree on-chip imaging and characterization of cells is illustrated. This on-chip cell imaging approach provides a compact and cost-effective tool for medical diagnostics and high-throughput cell biology applications, making it especially suitable for resource poor settings.
04:37
Three-Dimensional Quantitative Phase Imaging for Characterizing Lymphocyte Subtypes
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2025
This video demonstrates label-free identification of lymphocyte morphology and biochemistry through 3D quantitative phase imaging. This technique allows for a thorough analysis of lymphocytes, uncovering their internal structures and properties without the need for labeling procedures.
09:31
Measurement of Tension Release During Laser Induced Axon Lesion to Evaluate Axonal Adhesion to the Substrate at Piconewton and Millisecond Resolution
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Cited by 1 •
2013
We measured the tension release in an axon that was partially lesioned with a laser dissector by simultaneous force spectroscopy measurement performed on an optically-trapped probe adhered to the membrane of the axon. The developed experimental protocol evaluates the axon adhesion to the culture substrate.
10:04
Tractable In Vivo Reprogramming of Tumor Cells to Type 1 Conventional Dendritic Cell-like Cells
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2025
This protocol describes the in vivo reprogramming of mouse cancer cells into type 1 dendritic-like cells within the tumor microenvironment through enforced expression of the transcription factors PU.1, IRF8, and BATF3.
FAQs
During acquisition, light associated with the cell is combined with a reference beam, producing an interference pattern that encodes wave information. Computational reconstruction processes that pattern to recover quantitative optical phase and related cellular maps. This conversion lets researchers examine cell shape and thickness from recorded light behavior while preserving information about the cell’s structure.
Optical phase provides a quantitative signal for representing how the cell affects the recorded light. After reconstruction, phase information contributes to maps of cellular shape and thickness, allowing researchers to follow structural changes. Because these maps are quantitative, they support analysis of morphology over time rather than relying only on a qualitative visual assessment.
Using cell holograms without fluorescent labels can support noninvasive observation of living cells while minimizing phototoxicity and preparation artifacts. This is useful when researchers need to monitor morphology, growth, movement, or viability over time, because the approach can follow biological behavior while reducing effects associated with labeling or sample preparation.
A typical workflow starts by illuminating the cell with a laser or another coherent light source. Light associated with the cell forms an object beam, which interferes with a reference beam. The recorded interference pattern is then computationally reconstructed, producing quantitative maps that can be used to examine cellular shape, thickness, and optical phase.
These measurements can support longitudinal observation of cell morphology, growth, movement, and viability. Researchers can use the resulting information to monitor living cells, assess how they respond to treatments, and investigate dynamic cellular processes. The value lies in following several aspects of cellular behavior over time without requiring fluorescent labels.
Researchers can record cellular behavior before and after a treatment, then use reconstructed measurements to examine changes in morphology, growth, movement, or viability. This approach links the treatment condition to observable cellular responses while preserving a noninvasive, time-dependent view of living cells. It therefore supports biological studies of dynamic responses.