Ascorbic acid (AA), melatonin (Mel), glutathione (GSH), tea polyphenols (TPP), and uric acid (UA) were distinguished in this experiment by three analyses: heat map, hierarchical cluster, and linear discriminant.
A study out of the Key Laboratory of Bio-Inspired Smart Interfacial Science and Technology of Ministry of Education, within the School of Chemistry at Beihang University in Beijing, China, describes a novel platform for the simultaneous determination of five antioxidants with surface-enhanced Raman spectroscopy (SERS) that applies a sensor array based on the inverse etching of gold nanorods (AuNRs) and nanostars (AuNSs) (1).
The target antioxidants, ascorbic acid (AA), melatonin (Mel), glutathione (GSH), tea polyphenols (TPP), and uric acid (UA), are among those that are able to scavenge free radicals—in other words, generated from the same initiators used for free radical polymerization and copolymerization (1). According to the authors, whose study was published in the journal Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, too many free radicals can cause oxidative stress on the body, manifesting in potential cancers, diabetes, or cardiovascular or neurodegenerative diseases. But the correct balance of antioxidants matters just as much: too little AA can lead to scurvy, and too much UA causes gout.
For those reasons, a need for high-throughput discrimination of the five antioxidants resulted in the devised method described in this study. The compound 3,3′,5,5′-tetramethylbenzidine (TMB) is oxidized to TMB+ or TMB2+ in the presence of hydrogen peroxide (H2O2) and horseradish peroxidase (HRP), which react with each other to release oxygen free radicals and, in turn, react with TMB (1). But the authors point out that antioxidants can prevent the further oxidation of TMB+ to TMB2+, while also circumventing the etching of gold (Au) in the catalytic oxidation process—the aforementioned inverse etching, the end goal of which was to enhance the Raman SERS signal with regard to the antioxidants being studied. The antioxidants were then analyzed in three ways: heat map, hierarchical cluster, and linear discriminant analysis.
Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique in which target analytes are adsorbed onto metallic nanostructures such as silver or gold, greatly enhancing the Raman scattering signal. This allows for the ultrasensitive detection of various biomolecules. By analyzing the unique Raman spectra that are obtained, SERS can provide valuable information about chemical compositions and the presence of specific substances. SERS is nondestructive by nature, and therefore is suitable for repeated measurements on small sample volumes, enabling rapid and accurate analysis.
The relationship of Au to the two-dimensional (2D) SERS sensor array proposed here is crucial, as both AuNRs and AuNSs demonstrate high electromagnetic field enhancement performances at their tips; therefore, they are seen as excellent substrates in Raman applications (1). With AuNRs and AuNSs as the sensing elements, the peak Raman intensity of TMB+ for the identification of the five antioxidants was set at 1605 cm−1 for response mode.
The authors found that the novel platform was effective in simultaneously identifying the five antioxidants intended in the study, reporting distinct SERS responses and patterns for each, all based on their individual abilities to scavenge free radicals (1). And because of the speed and sensitivity of the method, the study pointed to potential future applications of this SERS sensor array in food safety and overall human health and well-being.
(1) Xi, H.; Shi, Z.; Wu, P.; et al. A Novel SERS Sensor Array Based on AuNRs and AuNSs Inverse-Etching for the Discrimination of Five Antioxidants. Spectrochim. Acta, Part A 2023, 302, 123082. DOI: 10.1016/j.saa.2023.123082
Best of the Week: Chewing Gum with SERS, Soil Carbon Analysis, Lithium-Ion Battery Research
January 17th 2025Top articles published this week include a Q&A interview that discussed using surface-enhanced Raman spectroscopy (SERS) to investigate microplastics released from chewing gum and an article about Agilent’s Solutions Innovation Research Award (SIRA) winners.
New SERS-Microfluidic Platform Classifies Leukemia Using Machine Learning
January 14th 2025A combination of surface-enhanced Raman spectroscopy (SERS) and machine learning on microfluidic chips has achieved an impressive 98.6% accuracy in classifying leukemia cell subtypes, offering a fast, highly sensitive tool for clinical diagnosis.
Machine Learning-Enhanced SERS Technology Advances Cancer Detection
January 13th 2025Researchers at the Chinese Academy of Sciences have developed an optical detection strategy for circulating tumor cells (CTCs), combining machine learning (ML) and dual-modal surface-enhanced Raman spectroscopy (SERS). This approach offers high sensitivity, specificity, and efficiency, potentially advancing early cancer diagnosis.
Surface-Enhanced Transmission Raman Spectroscopy (SETRS) Enhances Pharmaceutical Quality Control
January 7th 2025Researchers from the University of Liege have demonstrated the potential of surface-enhanced transmission Raman spectroscopy (SETRS) for detecting impurities in pharmaceuticals. The study highlights SETRS’s superior sensitivity, precision, and efficiency in quantifying toxic impurities like 4-aminophenol (4-AP), offering a promising alternative to traditional methods.
Edible Oil Testing: Handheld Raman Spectroscopy Offers Quick, Reagent-Free Answers
January 6th 2025Researchers have developed a rapid, reagent-free method to estimate the saponification value (SV) of edible oils using handheld Raman spectroscopy. This innovative approach simplifies oil quality testing, cutting time and costs while enhancing accuracy and portability.