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Point‐of‐care testing (POCT) of clinical biomarkers is critical to health monitoring and timely treatment, yet biosensing assays capable of detecting biomarkers without the need for costly external equipment and reagents are limited. Blood‐based assays are, specifically, challenging as blood collection is invasive and follow‐upprocessing is required. Here, we report a versatile assay that employs hydrogel microneedles (HMNs) to extract interstitial fluid (ISF), in a minimally invasive manner integrated with graphene oxide‐nucleic acid (GO.NA)‐based fluorescence biosensor to sense the biomarkers of interest in situ. The HMN‐GO.NA assay is supplemented with a portable detector, enabling a complete POCT procedure. Our system could successfully measure four clinically important biomarkers (glucose, uric acid (UA), insulin, and serotonin) ex vivo, in addition, to accurately detecting glucose and UA in vivo.

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This paper describes the 2DEG properties of InGaN/InN/InGaN double channel high electron mobility transistor (DHEMT). These include an in‐depth theoretical investigation of 2DEG sheet carrier concentration and mobility. The 2DEG mobility is calculated using ensemble Monte Carlo taking into account all relevant scatterings. The calculated sheet carrier concentration reaches as high as 1.77×1014 cm‐2 for DHEMT. While for single channel high electron mobility transistor (SHEMT) the calculated sheet carrier concentration was found to be 7.06×1013 cm‐2. The maximum total 2DEG mobility is found to be around 12×104 and 8×104 cm2V‐1s‐1, respectively, for DHEMT and SHEMT for a sheet carrier concentration of ns = 5×1012 cm‐2 at 77 K. Thus, the 2DEG sheet carrier concentration and mobility for dual channel is higher than conventional single channel HEMTs. The high values of 2DEG sheet carrier concentration and mobility strongly suggest that the InGaN/InN/InGaN based double channel HEMT is very promising for the fabrication of high performance high speed device (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

The combination of mid-infrared and photoacoustic spectroscopy has shown promising developments as a substitute for invasive glucose detection technology. A dual single-wavelength quantum cascade laser system has been developed using photoacoustic spectroscopy for noninvasive glucose monitoring. Biomedical skin phantoms with similar properties to human skin have been prepared with blood components at different glucose concentrations as test models for the setup. The detection sensitivity of the system has been improved to ± 12.5 mg/dL in the hyperglycemia blood glucose ranges. An ensemble machine learning classifier has been developed to predict the glucose level in the presence of blood components. The model, which was trained with 72,360 unprocessed datasets, achieved a 96.7% prediction accuracy with 100% of the predicted data located in zones A and B of Clarke’s error grid analysis. These findings fulfill both the US Food and Drug Administration and Health Canada requirements for glucose monitors.