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A Programmable, 3D Neuron-On-Chip Platform Integrating Near Real-Time Biosensing and Multiaxial Loading for

Sultan Khetani1,2, Kar Wey Yong1,2,3, Mawafag F Alhasadi4

  • 1BioMEMS and Bioinspired Microfluidic Laboratory, Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.

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|October 8, 2025
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Summary
This summary is machine-generated.

A novel Neuron-Injury-on-a-Chip (NIOC) platform precisely simulates central nervous system (CNS) trauma. This system reveals load-specific molecular injury mechanisms and potential biomarkers for brain injury.

Keywords:
central nervous system injuryelectrochemical biosensorsmechanical loadingneuron filament light proteinneuron‐injury‐on‐a‐chiptotal‐tau protein

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Area of Science:

  • Neuroscience
  • Biomaterials Science
  • Biomedical Engineering

Background:

  • Mechanical forces cause complex central nervous system (CNS) injuries.
  • Molecular mechanisms linking physical trauma to biomarker responses are not well understood.
  • Existing models lack the ability to precisely control mechanical loading and simultaneously monitor molecular responses.

Purpose of the Study:

  • To develop a programmable 3D microfluidic platform, Neuron-Injury-on-a-Chip (NIOC), for simulating CNS trauma.
  • To integrate multiaxial mechanical loading with real-time biosensing capabilities.
  • To investigate the molecular mechanisms and biomarker responses to defined mechanical insults.

Main Methods:

  • A 3D microfluidic system using a polydimethylsiloxane (PDMS) tube coated with polydopamine to culture differentiated neurons (CAD cells).
  • Application of controlled extension, torsion, and combined mechanical loads to simulate CNS trauma.
  • Integration of electrochemical biosensors for real-time detection of biomarkers like total tau (T-Tau) and neurofilament light chain (NFL).
  • Validation of cellular and molecular responses using qPCR and immunostaining for genes (Mapt, Gap-43) and apoptosis markers (Caspase-3).

Main Results:

  • Finite element modeling confirmed uniform strain transmission under applied loads.
  • Near real-time detection of T-Tau and NFL at picogram levels was achieved.
  • Load-specific biomarker trajectories and apoptotic thresholds were identified.
  • Synergistic injury responses were observed under combined loading conditions.
  • Gene-level responses and apoptosis were validated.

Conclusions:

  • The NIOC platform enables precise simulation of CNS mechanical trauma.
  • It facilitates the decoding of mechanobiological injury pathways.
  • The platform offers opportunities for biomarker discovery, injury stratification, and screening of neuroprotective agents.