Furthermore, intracellular calcium and cell-to-cell calcium transport demonstrate dynamic concentrations in pancreatic beta cells 14, 15, 16. Oxygen and hypoxia, for instance, are closely controlled via hypoxia-inducible factors and exhibit spatial gradients in diabetic tissues (fat and islets) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13. Specifically, oxygen, calcium, insulin, and other signaling molecules play major roles in diabetes-related pathologies. Spatial transport and concentrations of molecules between cells are important in many physiological processes. 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. These results provide evidence to support the current islet oscillator model. We observed an optimum oxygen level between 10 and 12%, which is neither hypoxic nor normoxic in the conventional cell culture sense. Furthermore, by analyzing the spatial detection data dynamically over time, we uncovered a new relationship between oxygen and beta cell oscillations. Specifically, insulin was quantified at levels as low as 25 pg/mL using our imaging technique. Using this device, we demonstrated the in situ detection of calcium, insulin, and ATP (adenosine triphosphate) in response to glucose and oxygen stimulation. This enabled our microfluidics to achieve spatiotemporal detection that is difficult to achieve with traditional microfluidics. 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. However, conventional microfluidics must combat diffusion, which limits the spatial distance and time for molecules traveling through microchannels. Moreover, in situ stimulation and detection eliminates variability between individual bioassays. Microfluidic scaling can be extremely powerful when combining multiple parameters and modalities. One distinct advantage of microfluidic-based cell assays is their scalability for multiple concentrations or gradients.
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