Multi-purpose machine vision platform for different microfluidics applications

Advances in Microfluidics for Single Red Blood Cell Analysis

The utilizations of microfluidic chips for single RBC (red blood cell) studies have attracted great interests in recent years to filter, trap, analyze, and release single erythrocytes for various applications. Researchers in this field have highlighted the vast potential in developing micro devices for industrial and academia usages, including lab-on-a-chip and organ-on-a-chip systems. This article critically reviews the current state-of-the-art and recent advances of microfluidics for single RBC analyses, including integrated sensors and microfluidic platforms for microscopic/tomographic/spectroscopic single RBC analyses, trapping arrays (including bifurcating channels), dielectrophoretic and agglutination/aggregation studies, as well as clinical implications covering cancer, sepsis, prenatal, and Sickle Cell diseases. Microfluidics based RBC microarrays, sorting/counting and trapping techniques (including acoustic, dielectrophoretic, hydrodynamic, magnetic, and optical techniques) are also reviewed. Lastly, organs on chips, multi-organ chips, and drug discovery involving single RBC are described. The limitations and drawbacks of each technology are addressed and future prospects are discussed.

Vision-Based Performance Analysis of an Active Microfluidic Droplet Generation System Using Droplet Images

This paper discusses an active droplet generation system, and the presented droplet generator successfully performs droplet generation using two fluid phases: continuous phase fluid and dispersed phase fluid. The performance of an active droplet generation system is analysed based on the droplet morphology using vision sensing and digital image processing. The proposed system in the study includes a droplet generator, camera module with image pre-processing and identification algorithm, and controller and control algorithm with a workstation computer. The overall system is able to control, sense, and analyse the generation of droplets. The main controller consists of a microcontroller, motor controller, voltage regulator, and power supply. Among the morphological features of droplets, the diameter is extracted from the images to observe the system performance. The MATLAB-based image processing algorithm consists of image acquisition, image enhancement, droplet identification, feature extraction, and analysis. RGB band filtering, thresholding, and opening are used in image pre-processing. After the image enhancement, droplet identification is performed by tracing the boundary of the droplets. The average droplet diameter varied from ~3.05 mm to ~4.04 mm in the experiments, and the average droplet diameter decrement presented a relationship of a second-order polynomial with the droplet generation time.

Characterization of Mechanical Signature of Eutopic Endometrial Stromal Cells of Endometriosis Patients

Endometriosis affects 5-10% of women in reproductive age and causes pelvic pain and subfertility. Exact etiology of the disease is unknown. Here, we present a microfluidic platform for characterizing mechanical properties of eutopic endometrial stromal cells of endometriosis patients based on cellular deformability inside narrow microchannels. Primary human endometrial stromal cells were isolated from eutopic endometrium of endometriosis patients (4407 cells, from 7 endometriosis patients) and from disease-free women (4541 cells, from 6 control women) and were pumped through microchannels (formed of polydimethylsiloxane (PDMS) by standard soft lithography, with dimensions of 8 × 20 × 150 μm, as width × height × length) at a constant flow rate of 2 μL/min. High-speed imaging was used to capture videos of cells as they flow inside microchannels, and a computer vision code was used to track cells, measure their area, and calculate the time each cell takes to pass through the microchannel. Compared with their counterparts from control women, eutopic endometrial stromal cells from endometriosis patients showed significantly increased deformation index (1.65 ± 0.2 versus 1.43 ± 0.19, respectively, P value < 0.001), and higher velocity in travelling through narrow microchannels (96.530 ± 0.710 mm/s versus 57.518 ± 0.585 mm/s, respectively, P value < 0.001). The same difference in velocities between the two cell types was maintained after controlling for cell area. Eutopic endometrial stromal cells of endometriosis patients showed a mechanical phenotype characterized by high deformability and reduced stiffness. This mechanical signature can represent basis of a mechanical biomarker of endometriosis.