Material-level countermeasures for securing microfluidic biochips.

Flow-based microfluidic biochips (FMBs) have been rapidly commercialized and deployed in recent years for biological computing, clinical diagnostics, and point-of-care-tests (POCTs). However, outsourcing FMBs makes them susceptible to material-level attacks by malicious actors for illegitimate monetary gain. The attacks involve deliberate material degradation of an FMB's polydimethylsiloxane (PDMS) components by either doping with reactive solvents or altering the PDMS curing ratio during fabrication. Such attacks are stealthy enough to evade detection and deteriorate the FMB's function. Furthermore, material-level attacks can become prevalent in attacks based on intellectual property (IP) theft, such as counterfeiting, overbuilding, etc., which involve unscrupulous third-party manufacturers. To address this problem, we present a dynamic material-level watermarking scheme for PDMS-based FMBs with microvalves using a perylene-labeled fluorescent dye. The dyed microvalves show a unique excimer intensity peak under 405 nm laser excitation. Moreover, when pneumatically actuated, the peak shows a predetermined downward shift in intensity as a function of mechanical strain. We validated this protection scheme experimentally using fluorescence microscopy, which showed a high correlation (R2 = 0.971) between the normalized excimer intensity change and the maximum principal strain of the actuated microvalves. To detect curing ratio-based attacks, we adapted machine learning (ML) models, which were trained on the force-displacement data obtained from a mechanical punch test method. Our ML models achieved more than 99% accuracy in detecting curing ratio anomalies. These countermeasures can be used to proactively safeguard FMBs against material-level attacks in the era of global pandemics and diagnostics based on POCTs.

Structural Attacks and Defenses for Flow-Based Microfluidic Biochips.

Flow-based microfluidic biochips (FMBs) have seen rapid commercialization and deployment in recent years for point-of-care and clinical diagnostics. However, the outsourcing of FMB design and manufacturing makes them susceptible to susceptible to malicious physical level and intellectual property (IP)-theft attacks. This work demonstrates the first structure-based (SB) attack on representative commercial FMBs. The SB attacks maliciously decrease the heights of the FMB reaction chambers to produce false-negative results. We validate this attack experimentally using fluorescence microscopy, which showed a high correlation ( R2 = 0.987) between chamber height and related fluorescence intensity of the DNA amplified by polymerase chain reaction. To detect SB attacks, we adopt two existing deep learning-based anomaly detection algorithms with  âˆ¼ 96% validation accuracy in recognizing such deliberately introduced microstructural anomalies. To safeguard FMBs against intellectual property (IP)-theft, we propose a novel device-level watermarking scheme for FMBs using intensity-height correlation. The countermeasures can be used to proactively safeguard FMBs against SB and IP-theft attacks in the era of global pandemics and personalized medicine.

Quantitative fluorescence imaging of mitochondria in body wall muscles of Caenorhabditis elegans under hyperglycemic conditions using a microfluidic chip.

Type 2 diabetes is the most common metabolic disease, and insulin resistance plays a role in the pathogenesis of the disease. Because completely functional mitochondria are necessary to obtain glucose-stimulated insulin from pancreatic beta cells, dysfunction of mitochondrial oxidative pathway could be involved in the development of diabetes. As a simple animal model, Caenorhabditis elegans renders itself to investigate such metabolic mechanisms because it possesses insulin/insulin-like growth factor-1 signaling pathway similar to that in humans. Currently, the widely spread agarose pad-based immobilization technique for fluorescence imaging of the mitochondria in C. elegans is laborious, batchwise, and does not allow for facile handling of the worm. To overcome these technical challenges, we have developed a single-channel microfluidic device that can trap a C. elegans and allow to image the mitochondria in body wall muscles accurately and in higher throughput than the traditional approach. In specific, our microfluidic device took advantage of the proprioception of the worm to rotate its body in a microfluidic channel with an aspect ratio above one to gain more space for its undulation motion that was favorable for quantitative fluorescence imaging of mitochondria in the body wall muscles. Exploiting this unique feature of the microfluidic chip-based immobilization and fluorescence imaging, we observed a significant decrease in the mitochondrial fluorescence intensity under hyperglycemic conditions, whereas the agarose pad-based approach did not show any significant change under the same conditions. A machine learning model trained with these fluorescence images from the microfluidic device could classify healthy and hyperglycemic worms at high accuracy. Given this significant technological advantage, its easiness of use and low cost, our microfluidic imaging chip could become a useful immobilization tool for quantitative fluorescence imaging of the body wall muscles in C. elegans.