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Microfluidic Chip for Axonal Injury Models Construction and Enabling Multi-Omics Analysis

Microfluidic Chip for Axonal Injury Models Construction and Enabling Multi-Omics Analysis

Published on: October 14, 2025

Interactive image analysis programs for quantifying injury-induced axonal beading and microtubule disruption.

Devrim Kilinc¹, Gianluca Gallo, Kenneth A Barbee

¹School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA.

Computer Methods and Programs in Biomedicine

|March 17, 2009

Summary

This study introduces novel Matlab-based image analysis tools to objectively quantify axonal beading and microtubule disruption after traumatic axonal injury. These programs successfully detected injury-induced increases in axonal beading.

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Area of Science:

Neuroscience
Cell Biology
Biomedical Engineering

Background:

Traumatic axonal injury (TAI) is characterized by focal axonal beading and microtubule disruption.
Previous research reproduced TAI-like changes in an in vitro model, highlighting the need for objective quantification.
Establishing a causal link between cytoskeletal damage and beading requires quantitative co-localization analysis.

Purpose of the Study:

To develop observer-independent image analysis programs for quantifying axonal beading.
To create a tool for measuring the co-localization of axonal beads and microtubule disruptions.
To objectively assess TAI-induced changes in an in vitro model.

Main Methods:

Development of Matlab-based interactive image analysis software.
Implementation of algorithms for axonal beading quantification.
Implementation of algorithms for co-localization analysis of axonal beads and microtubule disruptions.

Main Results:

The developed bead analysis program successfully detected injury-induced increases in axonal beading.
The image analysis tools provide objective and quantitative measures for TAI research.
The co-localization analysis enables establishing causal relationships between cytoskeletal damage and beading.

Conclusions:

Matlab-based image analysis programs offer objective quantification of axonal beading and microtubule disruption.
These tools are crucial for advancing the understanding of traumatic axonal injury mechanisms.
The developed methods facilitate causal relationship establishment in TAI research.