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Published on: February 16, 2024
Intelligent microfluidics: A deep learning-integrated platform for high-accuracy oocyte membrane permeability
Kashan Memon1, Bing Zhang1, Muhammad Azam Fareed1
1Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui, China.
Background:
Oocyte cryopreservation remains constrained by the limited efficiency of water and cryoprotective agent (CPA) transport across the cell membrane largely due to the absence of automated, high-throughput tools capable of quantifying key permeability parameters such as hydraulic conductivity (Lp) and CPA permeability (Ps). Accurate, reproducible measurement of these parameters is essential for optimizing cryopreservation protocols, yet current approaches rely heavily on manual analysis, resulting in low throughput and variability. This study addresses the critical need for a scalable analytical framework to characterize membrane transport phenomena in a robust and systematic manner.
Results:
We present CryoSIM, an integrated microfluidic-AI platform for automated, parallel quantification of oocyte membrane permeability. The microfluidic chip employs Y-shaped and zigzag perfusion channels with parabolic micropillar arrays to establish stable CPA gradients while minimizing hydrodynamic shear. A deep learning model (MLSNet) performs high-precision oocyte segmentation with 98.7% pixel-level accuracy, enabling real-time analysis of multiple cells simultaneously. A custom Python-based interface implements Two-Parameter and Kedem-Katchalsky transport models to calculate Lp and Ps across a range of CPA concentrations and thermal conditions (4-37 °C). CryoSIM achieves a >90% increase in analytical throughput over manual methods and demonstrates consistent, reproducible performance across biological replicates and experimental groups.
Significance:
CryoSIM offers a unified, high-throughput analytical workflow that integrates microfluidics, deep learning, and transport modeling for precise characterization of cell membrane permeability. This platform represents a significant advancement in cryopreservation analytics and provides a broadly applicable tool for biophysical transport studies, fertility preservation research, and bioanalytical assay development.
