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Imaging Biological Samples with Optical Microscopy

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

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Related Experiment Video

Updated: May 1, 2026

Murine Endoscopy for In Vivo Multimodal Imaging of Carcinogenesis and Assessment of Intestinal Wound Healing and Inflammation

Murine Endoscopy for In Vivo Multimodal Imaging of Carcinogenesis and Assessment of Intestinal Wound Healing and Inflammation

Published on: August 26, 2014

A modular fluorescent camera unit for wound imaging.

Maryam Tebyani^1,2, Gordon Keller³, Wan Shen Hee³

¹Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA. mtebyani@ucsc.edu.

Communications Biology

|July 5, 2025

Summary

This summary is machine-generated.

A new handheld microscope maps pH and nitric oxide (NO) in wounds, revealing healing patterns. Machine learning analysis predicts wound healing progression and informs future treatment strategies.

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Fluorescence Lifetime Macro Imager for Biomedical Applications

Fluorescence Lifetime Macro Imager for Biomedical Applications

Published on: April 7, 2023

Area of Science:

Biomedical Engineering
Medical Imaging
Wound Healing Research

Background:

Advanced imaging is crucial for understanding disease and live cell behavior.
Biophysical markers and real-time analysis are key to monitoring medical conditions.
Current methods for wound assessment lack real-time, high-resolution biomarker mapping.

Purpose of the Study:

To develop and apply a novel modular, hand-held fluorescent microscope for real-time biological analysis.
To map pH and nitric oxide (NO) in subcutaneous wounds to understand healing dynamics.
To utilize machine learning for analyzing biomarker spatiotemporal trends and predicting healing outcomes.

Main Methods:

Development of a modular, hand-held fluorescent microscope with sub-millimeter resolution.
Application of the microscope to map pH and nitric oxide (NO) in subcutaneous wounds.
Employing machine learning algorithms for clustering biomarker data and identifying healing patterns.

Main Results:

Spatiotemporal pH mapping revealed a concentric gradient and stabilization at the wound edge.
Nitric oxide (NO) clustering demonstrated dynamic changes in concentration and size during wound healing.
Machine learning analysis enabled prediction of wound healing day and re-epithelialization based on biomarker trends.

Conclusions:

The developed imaging system provides unprecedented insights into wound healing biomarkers.
Biomarker mapping and machine learning analysis can inform future wound healing studies and treatment strategies.
This technology paves the way for integrating imaging with bioelectronic devices for closed-loop wound management.