Label-Free Detection of Virus-like Particles with Surface-Enhanced Raman Spectroscopy through Analyte Localization and Polymer-Enabled Capture.

Virus detection is highly important; the last several years, since the onset of the SARS-CoV-2 pandemic, have highlighted a weakness in the field: the need for highly specialized and complex methodology for sensitive virus detection, which also manifests as sacrifices in limits of detection made to achieve simple and rapid sensing. Surface-enhanced Raman spectroscopy (SERS) has the potential to fill this gap, and two novel approaches to the development of a detection scheme are presented in this study. First, the physical entrapment of vesicular stomatitis virus (VSV) and additional virus-like particles through substrate design to localize virus analytes into SERS hotspots is explored.

Recent Advances in the Development and Characterization of Electrochemical and Electrical Biosensors for Small Molecule Neurotransmitters.

Neurotransmitters act as chemical messengers, determining human physiological and psychological function, and abnormal levels of neurotransmitters are related to conditions such as Parkinson's and Alzheimer's disease. Biologically and clinically relevant concentrations of neurotransmitters are usually very low (nM), so electrochemical and electronic sensors for neurotransmitter detection play an important role in achieving sensitive and selective detection. Additionally, these sensors have the distinct advantage to potentially be wireless, miniaturized, and multichannel, providing remarkable opportunities for implantable, long-term sensing capabilities unachievable by spectroscopic or chromatographic detection methods.

Investigation of Charged Small Molecule-Aptamer Interactions with Surface Plasmon Resonance.

Investigating the interactions between small, charged molecules and aptamers using surface plasmon resonance (SPR) is limited by the inherent low response of small molecules and difficulties with nonspecific electrostatic interactions between the aptamer, analyte, and sensor surface. However, aptamers are increasingly being used in sensors for small molecule detection in critical areas like healthcare and environmental safety. The ability to probe these interactions through simple, direct SPR assays would be greatly beneficial and allow for the development of improved sensors without the need for complicated signal enhancement.

Machine Learning-Assisted Carbon Dot Synthesis: Prediction of Emission Color and Wavelength.

Carbon dots (CDs) have attracted great attention in a range of applications due to their bright photoluminescence, high photostability, and good biocompatibility. However, it is challenging to design CDs with specific emission properties because the syntheses involve many parameters, and it is not clear how each parameter influences the CD properties. To help bridge this gap, machine learning, specifically an artificial neural network, is employed in this work to characterize the impact of synthesis parameters on and make predictions for the emission color and wavelength for CDs.