Blood quality evaluation via on-chip classification of cell morphology using a deep learning algorithm

A microfluidic microalgae detection system for cellular physiological response based on an object detection algorithm

The composition of species and the physiological status of microalgal cells serve as significant indicators for monitoring marine environments. Symbiotic with corals, Symbiodiniaceae are more sensitive to the environmental response. However, current methods for evaluating microalgae tend to be population-based indicators that cannot be focused on single-cell level, ignoring potentially heterogeneous cells as well as cell state transitions. In this study, we proposed a microalgal cell detection method based on computer vision and microfluidics, which combined microscopic image processing, microfluidic chip and convolutional neural network to achieve label-free, sheathless, automated and high-throughput microalgae identification and cell state assessment. By optimizing the data import, training process and model architecture, we solved the problem of identifying tiny objects at the micron scale, and the optimized model was able to perform the tasks of cell multi-classification and physiological state assessment with more than 95% mean average precision. We discovered a novel transition state and explored the thermal sensitivity of three clades of Symbiodiniaceae, and discovered the phenomenon of cellular heat shock at high temperatures. The evolution of the physiological state of Symbiodiniaceae cells is very important for directional cell evolution and early warning of coral ecosystem health.

Diseased Erythrocyte Enrichment Based on I-Shaped Pillar DLD Arrays

Enrichment of erythrocytes is a necessary step in the diagnosis of blood diseases. Due to the high deformability and viscosity of erythrocytes, they cannot be regarded as stable point-like solids, so the influence of their deformability on fluid dynamics must be considered. Therefore, by using the special effect of an I-shaped pillar (I-pillar) on erythrocytes, erythrocytes with different deformability can be made to produce different provisional distances in the chip, so as to achieve the separation of the two kinds of erythrocytes. In this study, a microfluidic chip was designed to conduct a control test between erythrocytes stored for a long time and fresh erythrocytes. At a specific flow rate, the different deformable erythrocytes in the chip move in different paths. Then, the influence of erythrocyte deformability on its movement trajectory was analyzed by two-dimensional finite element flow simulation. DLD sorting technology provides a new method for the sorting and enrichment of diseased erythrocytes.