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Abstract One distinct advantage of microfluidic-based cell assays is their scalability for multiple concentrations or gradients. Microfluidic scaling can be extremely powerful when combining multiple parameters and modalities. Moreover, in situ stimulation and detection eliminates variability between individual bioassays. However, conventional microfluidics must combat diffusion, which limits the spatial distance and time for molecules traveling through microchannels. Here, we leveraged a multilayered microfluidic approach to integrate a novel oxygen gradient (0–20%) with an enhanced hydrogel sensor to study pancreatic beta cells. This enabled our microfluidics to achieve spatiotemporal detection that is difficult to achieve with traditional microfluidics. Using this device, we demonstrated the in situ detection of calcium, insulin, and ATP (adenosine triphosphate) in response to glucose and oxygen stimulation. Specifically, insulin was quantified at levels as low as 25 pg/mL using our imaging technique. Furthermore, by analyzing the spatial detection data dynamically over time, we uncovered a new relationship between oxygen and beta cell oscillations. We observed an optimum oxygen level between 10 and 12%, which is neither hypoxic nor normoxic in the conventional cell culture sense. These results provide evidence to support the current islet oscillator model. In future applications, this spatial microfluidic technique can be adapted for discrete protein detection in a robust platform to study numerous oxygen-dependent tissue dysfunctions. 

Microfluidics has earned a reputation for providing numerous transformative but disconnected devices and techniques. Active research seeks to address this challenge by integrating microfluidic components, including embedded miniature pumps. However, a significant portion of existing microfluidic integration relies on the time-consuming manual fabrication that introduces device variations. We put forward a framework for solving this disconnect by combining new pumping mechanics and 3D printing to demonstrate several novel, integrated and wirelessly driven microfluidics. First, we characterized the simplicity and performance of printed microfluidics with a minimum feature size of 100 µm. Next, we integrated a microtesla (µTesla) pump to provide non-pulsatile flow with reduced shear stress on beta cells cultured on-chip. Lastly, the integration of radio frequency (RF) device and a hobby-grade brushless motor completed a self-enclosed platform that can be remotely controlled without wires. Our study shows how new physics and 3D printing approaches not only provide better integration but also enable novel cell-based studies to advance microfluidic research.