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.

Computer vision meets microfluidics: a label-free method for high-throughput cell analysis.

In this paper, we review the integration of microfluidic chips and computer vision, which has great potential to advance research in the life sciences and biology, particularly in the analysis of cell imaging data. Microfluidic chips enable the generation of large amounts of visual data at the single-cell level, while computer vision techniques can rapidly process and analyze these data to extract valuable information about cellular health and function. One of the key advantages of this integrative approach is that it allows for noninvasive and low-damage cellular characterization, which is important for studying delicate or fragile microbial cells. The use of microfluidic chips provides a highly controlled environment for cell growth and manipulation, minimizes experimental variability and improves the accuracy of data analysis. Computer vision can be used to recognize and analyze target species within heterogeneous microbial populations, which is important for understanding the physiological status of cells in complex biological systems. As hardware and artificial intelligence algorithms continue to improve, computer vision is expected to become an increasingly powerful tool for in situ cell analysis. The use of microelectromechanical devices in combination with microfluidic chips and computer vision could enable the development of label-free, automatic, low-cost, and fast cellular information recognition and the high-throughput analysis of cellular responses to different compounds, for broad applications in fields such as drug discovery, diagnostics, and personalized medicine.

Design and Modeling of a Microfluidic Coral Polyps Culture Chip with Concentration and Temperature Gradients.

Traditional methods of cultivating polyps are costly and time-consuming. Microfluidic chip technology makes it possible to study coral polyps at the single-cell level, but most chips can only be analyzed for a single environmental variable. In this work, we addressed these issues by designing a microfluidic coral polyp culture chip with a multi-physical field for multivariable analyses and verifying the feasibility of the chip through numerical simulation. This chip used multiple serpentine structures to generate the concentration gradient and used a circuit to form the Joule effect for the temperature gradient. It could generate different temperature gradients at different voltages for studying the growth of polyps in different solutes or at different temperatures. The simulation of flow field and temperature showed that the solute and heat could be transferred evenly and efficiently in the chambers, and that the temperature of the chamber remained unchanged after 24 h of continuous heating. The thermal expansion of the microfluidic chip was low at the optimal culture temperature of coral polyps, which proves the feasibility of the use of the multivariable microfluidic model for polyp culture and provides a theoretical basis for the actual chip processing.