Differentiating Live Versus Dead Gram-Positive and Gram-Negative Bacteria With and Without Oxidative Stress Using Buoyant Mass Measurements.

Expeditious and accurate determination of pathogenic bacteria cell viability is of great importance to public health for numerous areas including medical diagnostics, food safety, and environmental monitoring. In this work a cell buoyant mass classifier approach is presented to assess bacteria cell viability in real time. Buoyant mass measurements for live and dead Gram-positive and Gram-negative bacteria populations were acquired with a commercial suspended microchannel resonator, Archimedes, to generate receiver operating characteristic (ROC) curves. To quantitatively assess the difference in buoyant mass for live and dead bacteria populations, ROC curves were generated to demonstrate cell viability determination. The results are presented as a binary classifier with a decision boundary, above which cells are considered live and below which cells are considered dead. A decision threshold value is evaluated with consideration that a certain true positive rate (correct classification of a live cell) is maintained with an acceptable false positive rate. The potential for this approach to monitor cell viability in real time is significant, especially when considering multiple classifier dimensions such as buoyant mass and density. This classifier approach represents a next generation technique for rapid and label-free diagnostics based on cell feature measurements.

3D printed self-supporting elastomeric structures for multifunctional microfluidics.

Microfluidic devices fabricated via soft lithography have demonstrated compelling applications such as lab-on-a-chip diagnostics, DNA microarrays, and cell-based assays. These technologies could be further developed by directly integrating microfluidics with electronic sensors and curvilinear substrates as well as improved automation for higher throughput. Current additive manufacturing methods, such as stereolithography and multi-jet printing, tend to contaminate substrates with uncured resins or supporting materials during printing. Here, we present a printing methodology based on precisely extruding viscoelastic inks into self-supporting microchannels and chambers without requiring sacrificial materials. We demonstrate that, in the submillimeter regime, the yield strength of the as-extruded silicone ink is sufficient to prevent creep within a certain angular range. Printing toolpaths are specifically designed to realize leakage-free connections between channels and chambers, T-shaped intersections, and overlapping channels. The self-supporting microfluidic structures enable the automatable fabrication of multifunctional devices, including multimaterial mixers, microfluidic-integrated sensors, automation components, and 3D microfluidics.

Graphene Nanoplatelet-Polymer Chemiresistive Sensor Arrays for the Detection and Discrimination of Chemical Warfare Agent Simulants.

A cross-reactive array of semiselective chemiresistive sensors made of polymer-graphene nanoplatelet (GNP) composite coated electrodes was examined for detection and discrimination of chemical warfare agents (CWA). The arrays employ a set of chemically diverse polymers to generate a unique response signature for multiple CWA simulants and background interferents. The developed sensors' signal remains consistent after repeated exposures to multiple analytes for up to 5 days with a similar signal magnitude across different replicate sensors with the same polymer-GNP coating. An array of 12 sensors each coated with a different polymer-GNP mixture was exposed 100 times to a cycle of single analyte vapors consisting of 5 chemically similar CWA simulants and 8 common background interferents. The collected data was vector normalized to reduce concentration dependency, z-scored to account for baseline drift and signal-to-noise ratio, and Kalman filtered to reduce noise. The processed data was dimensionally reduced with principal component analysis and analyzed with four different machine learning algorithms to evaluate discrimination capabilities. For 5 similarly structured CWA simulants alone 100% classification accuracy was achieved. For all analytes tested 99% classification accuracy was achieved demonstrating the CWA discrimination capabilities of the developed system. The novel sensor fabrication methods and data processing techniques are attractive for development of sensor platforms for discrimination of CWA and other classes of chemical vapors.

Impedimetric Immunosensing in a Porous Volumetric Microfluidic Detector.

A sensitive and rapid impedemetric immunosensor is demonstrated utilizing porous volumetric microfluidic detection elements and silver enhanced gold nanoparticle probes. The porous detection elements significantly increase capture probe density and decrease diffusion length scales compared to conventional planar sensors to improve target capture efficiency and enhance impedance signal. In this work, a packed bed of silica beads functionalized with antibody probes serves as a porous sensor element within a thermoplastic microchannel, with an interdigitated gold electrode microarray used to measure impedance changes caused by the concentration dependent formation of silver aggregates. The measured impedance change is independent of electrode spacing, enabling a device with low resolution electrodes to achieve a sandwich immunoassay detection limit between 1-10 ng/mL with a 4-log dynamic range, with a total assay time of 75 min.