Quaternary-Ammonium-Modulated Surface-Enhanced Raman Spectroscopy Effect: Discovery, Mechanism, and Application for Highly Sensitive In Vitro Sensing of Acetylcholine

Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience

Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.

Spectroscopic Determination of Acetylcholine (ACh): A Representative Review

Acetylcholine (ACh) is one of the most crucial neurotransmitters of the cholinergic system found in vertebrates and invertebrates and is responsible for many processes in living organisms. Disturbances in ACh transmission are closely related to dementia in Alzheimer's and Parkinson's disease. ACh in biological samples is most often determined using chromatographic techniques, radioenzymatic assays, enzyme-linked immunosorbent assay (ELISA), or potentiometric methods. An alternative way to detect and determine acetylcholine is applying spectroscopic techniques, due to low limits of detection and quantification, which is not possible with the methods mentioned above. In this review article, we described a detailed overview of different spectroscopic methods used to determine ACh with a collection of validation parameters as a perspective tool for routine analysis, especially in basic research on animal models on central nervous system. In addition, there is a discussion of examples of other biological materials from clinical and preclinical studies to give the whole spectrum of spectroscopic methods application. Descriptions of the developed chemical sensors, as well as the use of flow technology, were also presented. It is worth emphasizing the inclusion in the article of multi-component analysis referring to other neurotransmitters, as well as the description of the tested biological samples and extraction procedures. The motivation to use spectroscopic techniques to conduct this type of analysis and future perspectives in this field are briefly discussed.

Surface-Enhanced Raman Spectroscopic Probing in Digital Microfluidics through a Microspray Hole

We report a novel approach for surface-enhanced Raman spectroscopy (SERS) detection in digital microfluidics (DMF). This is made possible by a microspray hole (μSH) that uses an electrostatic spray (ESTAS) for sample transfer from inside the chip to an external SERS substrate. To realize this, a new ESTAS-compatible stationary SERS substrate was developed and characterized for sensitive and reproducible SERS measurements. In a proof-of-concept study, we successfully applied the approach to detect various analyte molecules using the DMF chip and achieved micro-molar detection limits. Moreover, this technique was exemplarily employed to study an organic reaction occurring in the DMF device, providing vibrational spectroscopic data.