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Mapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning
Zhigao Yi1, Huxin Gao2,3, Xianglin Ji4
1Department of Chemistry, National University of Singapore, Singapore 117543, Singapore.
Abstract:
Chemotherapy can induce toxicity in the central and peripheral nervous systems and result in chronic adverse reactions that impede continuous treatment and reduce patient quality of life. There is a current lack of research to predict, identify, and offset drug-induced neurotoxicity. Rapid and accurate assessment of potential neuropathy is crucial for cost-effective diagnosis and treatment. Here we report dynamic near-infrared upconversion imaging that allows intraneuronal transport to be traced in real time with millisecond resolution, but without photobleaching or blinking. Drug-induced neurotoxicity can be screened prior to phenotyping, on the basis of subtle abnormalities of kinetic characteristics in intraneuronal transport. Moreover, we demonstrate that combining the upconverting nanoplatform with machine learning offers a powerful tool for mapping chemotherapy-induced peripheral neuropathy and assessing drug-induced neurotoxicity.
Insights
This study introduces a novel imaging technique to detect chemotherapy-induced neurotoxicity early. It enables real-time tracing of nerve transport, aiding in the prediction and management of adverse drug reactions.
Area of Science:
- Biomedical imaging
- Nanotechnology
- Neuroscience
Background:
- Chemotherapy often causes neurotoxicity, impacting treatment and quality of life.
- Predicting and managing chemotherapy-induced neurotoxicity remains a challenge.
- Current diagnostic methods for neuropathy lack speed and accuracy.
Purpose of the Study:
- To develop a rapid and accurate method for assessing drug-induced neurotoxicity.
- To enable real-time monitoring of intraneuronal transport for early detection of neuropathy.
- To combine advanced imaging with machine learning for comprehensive neurotoxicity assessment.
Main Methods:
- Dynamic near-infrared upconversion imaging for real-time intraneuronal transport tracing with millisecond resolution.
- Utilizing upconverting nanoplatforms without photobleaching or blinking.
- Integrating machine learning algorithms for data analysis and neuropathy mapping.
Main Results:
- Demonstrated real-time tracing of intraneuronal transport with high resolution and no photobleaching.
- Successfully screened for drug-induced neurotoxicity by identifying subtle kinetic abnormalities.
- Showcased the combined nanoplatform and machine learning approach for mapping chemotherapy-induced peripheral neuropathy.
Conclusions:
- Dynamic near-infrared upconversion imaging offers a powerful tool for real-time assessment of intraneuronal transport.
- This technology allows for early screening of neurotoxicity before phenotypic changes.
- The integration of upconverting nanoplatforms and machine learning provides a robust method for evaluating drug-induced neurotoxicity.
