A Gold Nanoparticle-Based Cortisol Aptasensor for Non-Invasive Detection of Fish Stress.

Cortisol is a key stress biomarker in humans and animals, including fishes. In aquafarming, stress monitoring using cortisol quantification can help to optimize aquaculture practices for welfare and productivity enhancement. However, most current methods for cortisol detection rely on invasive tissue sampling. In this work, we developed a gold nanoparticle (AuNP)-based cortisol sensor to address the demand of detecting picomolar ranges of cortisol from complex fish tank water matrices as a non-invasive alternative for more effective stress monitoring. We first identified a DNA aptamer with effective binding to cortisol and then conjugated the thiol-labelled aptamer to AuNPs together with a blocker molecule (CALNN) to form an Au-Apt-CALNN conjugate that is stable in fish tank water. The cortisol detection principle is based on magnesium chloride (MgCl2)-induced particle aggregation, where the cortisol-bound aptamer on the AuNPs folds into a tertiary structure and provides greater protection for Au-Apt-CALNN against MgCl2-induced aggregation due to steric stabilization. At an optimum MgCl2 concentration, the differential stability of particles with and without cortisol binding offers a limit of detection (LOD) of 100 pM for cortisol within a 35 min reaction. The aptasensor has been validated on recirculating aquaculture system (RAS) fish tank water samples by the HPLC method and was able to detect changes in water cortisol induced by two different stress paradigms. This on-site deployable and non-invasive sensor offers opportunities for more efficient and real-time fish stress monitoring for the optimization of aquaculture practices.

Battery-free and AI-enabled multiplexed sensor patches for wound monitoring.

Wound healing is a dynamic process with multiple phases. Rapid profiling and quantitative characterization of inflammation and infection remain challenging. We report a paper-like battery-free in situ AI-enabled multiplexed (PETAL) sensor for holistic wound assessment by leveraging deep learning algorithms. This sensor consists of a wax-printed paper panel with five colorimetric sensors for temperature, pH, trimethylamine, uric acid, and moisture. Sensor images captured by a mobile phone were analyzed by neural network-based machine learning algorithms to determine healing status. For ex situ detection via exudates collected from rat perturbed wounds and burn wounds, the PETAL sensor can classify healing versus nonhealing status with an accuracy as high as 97%. With the sensor patches attached on rat burn wound models, in situ monitoring of wound progression or severity is demonstrated. This PETAL sensor allows early warning of adverse events, which could trigger immediate clinical intervention to facilitate wound care management.

A portable SERS sensor for pyocyanin detection in simulated wound fluid and through swab sampling.

A portable surface-enhanced Raman spectroscopy (SERS) sensor for detecting pyocyanin (PYO) in simulated wound fluid and from bacteria samples was developed. Solution-phase SERS detection protocols are designed to be compatible with two different clinical practices for wound exudate collection, namely negative pressure liquid collection and swabbing. For citrate-coated metal nanoparticles of three different compositions, i.e. gold (AuNPs), alloyed silver/gold (AgAuNPs), and silver (AgNPs), we firstly confirmed their interaction with PYO in the complex wound fluid, using fluorescence quenching experiments, which rationalized the Raman enhancement effects. We then demonstrated the Raman enhancement effects of the metal nanoparticles in the order of AgNPs > AgAuNPs > AuNPs. The limit of detection (LOD) achieved for PYO is 1.1 µM (in a linear range of 0.1-25 µM by the AgNPs), 10.9 µM (in a linear range of 5-100 µM, by the AgAuNPs), and 17.7 µM (in a linear range of 10-100 µM by the AuNPs). The AgNP and AgAuNP sensors together cover the sensitivity and dynamic range requirements for the clinical detection of wound infection, where PYO is present at a concentration of 1-50 µM. In addition, sterilized cotton swabs were used to collect wound fluid and transfer samples into AgNP solution for SERS measurements. This detection protocol was completed within 5 minutes with a LOD of 23.1 µM (in a linear range of 15-100 µM). The SERS sensing protocol was validated by its successful detection of PYO in cultured Pseudomonas aeruginosa bacteria. The findings presented in this work pave the way towards point-of-care diagnostics of wound infections.