Microfluidic technologies for enhancing the potency, predictability and affordability of adoptive cell therapies
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Artificial intelligence-enabled microfluidic cytometer using gravity-driven slug flow for rapid CD4+ T cell quantification in whole blood
The quantification of immune cell subpopulations in blood is important for the diagnosis, prognosis and management of various diseases and medical conditions. Flow cytometry is currently the gold standard technique for cell quantification; however, it is laborious, time-consuming and relies on bulky/expensive instrumentation, limiting its use to laboratories in high-resource settings. Microfluidic cytometers offering enhanced portability have been developed that are capable of rapid cell quantification; however, these platforms involve tedious sample preparation and processing protocols and/or require the use of specialized/expensive instrumentation for flow control and cell detection. Here, we report an artificial intelligence-enabled microfluidic cytometer for rapid CD4+ T cell quantification in whole blood requiring minimal sample preparation and instrumentation. CD4+ T cells in blood are labeled with anti-CD4 antibody-coated microbeads, which are driven through a microfluidic chip via gravity-driven slug flow, enabling pump-free operation. A video of the sample flowing in the chip is recorded using a microscope camera, which is analyzed using a convolutional neural network-based model that is trained to detect bead-labeled cells in the blood flow. The functionality of this platform was evaluated by analyzing fingerprick blood samples obtained from healthy donors, which revealed its ability to quantify CD4+ T cells with similar accuracy as flow cytometry (<10% deviation between both methods) while being at least 4× faster, less expensive, and simpler to operate. We envision that this platform can be readily modified to quantify other cell subpopulations in blood by using beads coated with different antibodies, making it a promising tool for performing cell count measurements outside of laboratories and in low-resource settings.
Design and developing a robot-assisted cell batch microinjection system for zebrafish embryo
The microinjection of Zebrafish embryos is significant to life science and biomedical research. In this article, a novel automated system is developed for cell microinjection. A sophisticated microfluidic chip is designed to transport, hold, and inject cells continuously. For the first time, a microinjector with microforce perception is proposed and integrated within the enclosed microfluidic chip to judge whether cells have been successfully punctured. The deep learning model is employed to detect the yolk center of zebrafish embryos and locate the position of the injection needle within the yolk, which enables enhancing the precision of cell injection. A prototype is fabricated to achieve automatic batch microinjection. Experimental results demonstrated that the injection efficiency is about 20 seconds per cell. Cell puncture success rate and cell survival rate are 100% and 84%, respectively. Compared to manual operation, this proposed system improves cell operation efficiency and cell survival rate. The proposed microinjection system has the potential to greatly reduce the workload of the experimenters and shorten the relevant study period.
Anionic lipids direct efficient microfluidic encapsulation of stable and functionally active proteins in lipid nanoparticles
Because proteins do not efficiently pass through the plasma membrane, protein therapeutics are limited to target ligands located at the cell surface or in serum. Lipid nanoparticles can facilitate delivery of polar molecules across a membrane. We hypothesized that because most proteins are amphoteric ionizable polycations, proteins would associate with anionic lipids, enabling microfluidic chip assembly of stable EP-LNPs (Encapsulated Proteins in Lipid NanoParticles). Here, by employing anionic lipids we were able to efficiently load proteins into EP-LNPs at protein:lipid w:w ratios of 1:20. Several proteins with diverse molecular weights and isoelectric points were encapsulated at efficiencies of 70 75%–90% and remained packaged for several months. Proteins packaged in EP-LNPs efficiently entered mammalian cells and fungal cells with cell walls. The proteins delivered intracellularly were functional. EP-LNPs technology should improve cellular delivery of medicinal antibodies, enzymes, peptide antimetabolites, and dominant negative proteins, opening new fields of protein therapeutics
Toolkit for integrating millimeter-sized microfluidic biomedical devices with multiple membranes and electrodes
In recent years, microfluidic systems have evolved to incorporate increasingly complex multi-layer and multi-material structures. While conventional 2-dimensional microfluidic systems are typically fabricated with lithographic techniques, the increase in system complexity necessitates a more versatile set of fabrication techniques. Similarly, although 3D printing can easily produce intricate microfluidic geometries, integrating multiple membranes and electrode components remains challenging. This study proposes a toolkit for fabricating free-standing 3-dimensional microfluidic systems for biomedical devices, incorporating flow channels, electrodes, and membranes. The fabrication techniques include molding separation using 3D printed molds, laser-based processing, and component assembly, each achieving micron resolution. Here, we introduce a novel approach to integrate membranes into microfluidics by directly curing elastomer-based microfluidics with the membrane through replica molding, while preserving membrane functionality by effectively removing elastomer residues through reactive ion etching. The resulting membrane-elastomer microfluidic component significantly simplifies the assembly of intricate microfluidic systems, reducing the device size to millimeter dimensions, suitable for implantable applications. The toolkit’s versatility is demonstrated by a redox flow iontophoretic drug delivery prototype at the millimeter scale, featuring two electrodes, four membranes, and four microfluidic channels.
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