Au@Ag Dendritic Nanoforests for Surface-Enhanced Raman Scattering Sensing

Identifying Surface-Enhanced Raman Spectra with a Raman Library Using Machine Learning

Since its discovery, surface-enhanced Raman spectroscopy (SERS) has shown outstanding promise of identifying trace amounts of unknown molecules in rapid, portable formats. However, the many different types of nanoparticles or nanostructured metallic SERS substrates created over the past few decades show substantial variability in the SERS spectra they provide. These inconsistencies have even raised speculation that substrate-specific SERS spectral libraries must be compiled for practical use of this type of spectroscopy. Here, we report a machine learning (ML) algorithm that can identify chemicals by matching their SERS spectra to those of a standard Raman spectral library. We use an approach analogous to facial recognition that utilizes feature extraction in the presence of multiple nuisance variables for spectral recognition. The key element is a metric we call "Characteristic Peak Similarity" (CaPSim) that focuses on the characteristic peaks in the SERS spectra. It has the flexibility to accommodate substrate-specific variability when quantifying the degree of similarity to a Raman spectrum. Analysis shows that CaPSim substantially outperforms existing spectral matching algorithms in terms of accuracy. This ML-based approach could greatly facilitate the spectroscopic identification of molecules in fieldable SERS applications.

SERS Determination of Oxidative Stress Markers in Saliva Using Substrates with Silver Nanoparticle-Decorated Silicon Nanowires

Glutathione and malondialdehyde are two compounds commonly used to evaluate the oxidative stress status of an organism. Although their determination is usually performed in blood serum, saliva is gaining ground as the biological fluid of choice for oxidative stress determination at the point of need. For this purpose, surface-enhanced Raman spectroscopy (SERS), which is a highly sensitive method for the detection of biomolecules, could offer additional advantages regarding the analysis of biological fluids at the point of need. In this work, silicon nanowires decorated with silver nanoparticles made by metal-assisted chemical etching were evaluated as substrates for the SERS determination of glutathione and malondialdehyde in water and saliva. In particular, glutathione was determined by monitoring the reduction in the Raman signal obtained from substrates modified with crystal violet upon incubation with aqueous glutathione solutions. On the other hand, malondialdehyde was detected after a reaction with thiobarbituric acid to produce a derivative with a strong Raman signal. The detection limits achieved after optimization of several assay parameters were 50 and 3.2 nM for aqueous solutions of glutathione and malondialdehyde, respectively. In artificial saliva, however, the detection limits were 2.0 and 0.32 μM for glutathione and malondialdehyde, respectively, which are, nonetheless, adequate for the determination of these two markers in saliva.

Enhanced Photoluminescence of R6G Dyes from Metal Decorated Silicon Nanowires Fabricated through Metal Assisted Chemical Etching

In this study, we developed active substrates consisting of Ag-decorated silicon nanowires on a Si substrate using a single-step Metal Assisted Chemical Etching (MACE) process, and evaluated their performance in the identification of low concentrations of Rhodamine 6G using surface-enhanced photoluminescence spectroscopy. Different structures with Ag-aggregates as well as Ag-dendrites were fabricated and studied depending on the etching parameters. Moreover, the addition of Au nanoparticles by simple drop-casting on the MACE-treated surfaces can enhance the photoluminescence significantly, and the structures have shown a Limit of Detection of Rhodamine 6G down to 10-12 M for the case of the Ag-dendrites enriched with Au nanoparticles.

In Vitro Carcinogenicity Test of a Copper-Containing Intrauterine Device

The aim is to study the cellular carcinogenicity of a copper-containing intrauterine device (IUD). So we analyzed the chemical elements of copper-containing IUDs. After that, we used Bhas42 cells in initiation and promotion assays to evaluate the leaching solution that extracted from the copper-containing IUDs at serial dilutions. In the cell carcinogenic experiment, the number of cell foci with malignant transformation was calculated. Although we uncovered no significant differences between the leaching solution at different concentrations and the negative control in the initiation assay, the sample at four concentrations showed significant differences relative to the negative control in the promotion assay (chi-squared test, p < 0.01). Therefore, we preliminarily evaluated that copper-containing IUDs are nongenotoxic carcinogen. Impact statement For the first time, we executed two-stage transformation assays with Bhas42 cells to assess the potential carcinogenicity of a copper-containing intrauterine device (IUD). In this study, we demonstrated that the copper-containing IUD manifested nongenotoxic carcinogenicity, making this the first-ever published report regarding this type of IUD's nongenotoxic carcinogenicity and revealing that its use carries a cancer risk.