Organophosphate-based compounds (OPs) represent a significant threat to warfighters (nerve agents) and civilian populations (pesticides). There is a pressing need to develop in vitro brain models that correlate to the in vivo brain to rapidly study OPs for neurotoxicity. Here we report on a microfluidic-based three-dimensional, four-cell tissue construct consisting of 1) a blood-brain barrier that has dynamic flow and membrane-free culture of the endothelial layer, and 2) an extracellular matrix (ECM)-embedded tissue construct with neuroblastoma, microglia, and astrocytes. We demonstrated this platform’s utility by measuring OP effects on barrier integrity, acetylcholinesterase (AChE) inhibition, viability and residual OP concentration with four model OPs. The results show that the OPs penetrate the blood brain barrier (BBB) and rapidly inhibit AChE activity, and that in vitro toxicity was correlated with available in vivo data. This paper demonstrates the potential utility of a membrane-free tetra-cultured brain on chip that can be scaled to high throughput as a cost-effective alternative method to animal testing.

This paper proposes a smartphone-based colorimetric pH detection method using a color adaptation algorithm for point-of-care applications. Although a smartphone camera can be utilized to measure the color information of colorimetric sensors, ambient light changes and unknown built-in automatic image correction operations make it difficult to obtain stable color information. This paper utilizes a 3D printed mini light box and performs a calibration procedure with a paper-printed comparison chart and a reference image which overcomes the drawbacks of smartphone cameras and the difficulty in preparing for the calibration procedure. The color adaptation is performed in the CIE 1976 u’v’ color space by using the reference paper in order to stabilize the color variations. Non-rigid u’v’ curve interpolation is used to produce the high-resolution pH estimate. The final pH value is estimated by using the best-matching method to handle the nonlinear curve properties of multiple color patches. The experimental results obtained using a pH indicator paper show that the proposed algorithm provides reasonably good estimation of pH detection. With paper-printed accurate color comparison charts and smart color adaptation techniques, superior estimation is achieved in the smartphone-based colorimetric pH detection system for point-of-care application.