Method study on determination of total purine content in fish meat by diazotization reaction combined with SERS

Ultrasensitive SERS quantitative detection of antioxidants via diazo derivatization reaction and deep learning for signal fluctuation mitigation

Synthetic antioxidants serve as essential protectors against oxidation and deterioration of edible oils, however, prudent evaluation is necessary regarding potential health risks associated with excessive intake. The direct adsorption of antioxidants onto conventional surface-enhanced Raman scattering (SERS) substrates is challenging due to the presence of phenolic hydroxyl groups in their molecular structures, resulting in weak Raman scattering signals and rendering direct SERS detection difficult. In this study, a diazo derivatization reaction was employed to enhance SERS signals by converting antioxidant molecules into azo derivatives, enabling the amplification of the weak Raman scattering signals through the strong vibrational modes induced by the N = N double bond. The resulting diazo derivatives were characterized using UV-visible absorption and infrared spectroscopy, confirming the occurrence of diazo derivatization of the antioxidants. The proposed method successfully achieved the rapid detection of three commonly used synthetic antioxidants, namely butylated hydroxyanisole (BHA), tert-butylhydroquinone (TBHQ), and propyl gallate (PG) on interfacial self-assembled gold nanoparticles. Furthermore, rapid predictions of BHA, PG, and TBHQ within the concentration range of 1 × 10-6 to 2 × 10-3 mol/L were achieved by integrating a convolutional neural network model. The predictive range of this model surpassed the traditional quantitative method of manually selecting characteristic peaks, with linear coefficients (R2) of 0.9992, 0.9997, and 0.9997, respectively. The recovery of antioxidants in real soybean oil samples ranged from 73.0 % to 126.4 %. Based on diazo derivatization, the proposed SERS method eliminates the need for complex substrates and enables the analysis and determination of synthetic antioxidants in edible oils within 20 min, providing a convenient analytical approach for quality control in the food industry.

Multienzyme-Mediated Dual-Channel Magnetic Relaxation Switching Taste Biosensor (D-MRSTB) for Simultaneous Detection of Umami Compounds and Synergistic Enhancement in Food

Umami substances play a significant role in the evaluation of food quality, and their synergistic enhancement is of great importance in improving and intensifying food flavors and tastes. Current biosensors available for umami detection still confront challenges in simultaneous quantification of multiple umami substances and umami intensities. In this study, an innovative dual-channel magnetic relaxation switching taste biosensor (D-MRSTB) was developed for the quantitative detection of representative umami substances. The multienzyme signal of D-MRSTB specifically catalyzes the umami substances of interest to generate hydrogen peroxide (H2O2), which is then used to oxidate Fe2+ to Fe3+. Such a valence-state transition of paramagnetic ions was utilized as a magnetic relaxation signaling switch to influence the transverse magnetic relaxation time (T2) within the reaction milieu, thus achieving simultaneous detection of monosodium glutamate (MSG) and inosine 5'-monophosphate (IMP). The biosensor showed good linearity (R2 > 0.99) in the concentration range of 50-1000 and 10-1000 μmol/L, with limits of detection (LOD) of 0.61 and 0.09 μmol/L for MSG and IMP, respectively. Furthermore, the biosensor accurately characterized the synergistic effect of the mixed solution of IMP and MSG, where ΔT2 showed a good linear relationship with the equivalent umami concentration (EUC) of the mixed solution (R2 = 0.998). Moreover, the D-MRSTB successfully achieved the quantitative detection of umami compounds in real samples. This sensing technology provides a powerful tool for achieving the detection of synergistic enhancement among umami compounds and demonstrates its potential for application in the food industry.

Quantitative detection of purine from food products with different water activities using needle-based surface-enhanced Raman scattering sensors

Typically, for accurate quantitative tests of molecules, considering the actual solute concentration in the environment with different water activities (Aws) is essential. Accordingly, for effective detection of food substances, this paper proposes a non-destructive pluggable sensor to capture and monitor four free purines based on surface-enhanced Raman scattering characteristics such as sensitivity, uniformity, repeatability, and stability. In particular, we investigate the impact of Aw on the evaluation of purine detection and its deviation corrections. Furthermore, the recoveries of purine from three food products, including fish (Aw: 0.99), ham (Aw: 0.91), and bacon (Aw: 0.73), are subsequently explored to validate the reliability of the proposed method. The results indicate that the proposed non-destructive pluggable sensor performs better when the Aw is considered. Therefore, this strategy for achieving more reliable quantitative detection by rectifying deviations based on the Aw can significantly help monitor food quality.

Application of SERS-based nanobiosensors to metabolite biomarkers of CKD

A clinical diagnosis of chronic kidney disease (CKD) is commonly achieved by estimating the serum levels of urea and creatinine (CR). Given the limitations of the conventional diagnostic assays, it is imperative to seek alternative, economical strategies for the detection of CKD-specific biomarkers with high specificity and selectivity. In this respect, surface-enhanced Raman spectroscopy (SERS) can be regarded as an ideal choice. SERS signals can be greatly amplified by noble metal nanoparticles (e.g., gold nanoparticles (GNPs)) of numerous sizes, shapes, and configurations to help achieve ultra-sensitive single molecule-level detection at 10^-15 M (up to 10 orders of magnitude more sensitive than fluorescence-based detection). The irregular geometry of GNPs with spike-like tips, dimers, and aggregates with small nanogaps (i.e., due to plasmon coupling such as Raman hot spots) play a pivotal role in enhancing the specificity and sensitivity of SERS. This review critically outlines the performance of SERS-based biosensors in the ultrasensitive detection of CKD biomarkers in various body fluids in terms of basic quality assurance parameters (e.g., limit of detection, figure of merit, enhancement factor, and stability of the biosensor). Moreover, the challenges and perspectives are described with respect to the expansion of such sensing techniques in practical clinical settings.

Assessing Meat Freshness via Nanotechnology Biosensors: Is the World Prepared for Lightning-Fast Pace Methods?

In the rapidly evolving field of food science, nanotechnology-based biosensors are one of the most intriguing techniques for tracking meat freshness. Purine derivatives, especially hypoxanthine and xanthine, are important signs of food going bad, especially in meat and meat products. This article compares the analytical performance parameters of traditional biosensor techniques and nanotechnology-based biosensor techniques that can be used to find purine derivatives in meat samples. In the introduction, we discussed the significance of purine metabolisms as analytes in the field of food science. Traditional methods of analysis and biosensors based on nanotechnology were also briefly explained. A comprehensive section of conventional and nanotechnology-based biosensing techniques is covered in detail, along with their analytical performance parameters (selectivity, sensitivity, linearity, and detection limit) in meat samples. Furthermore, the comparison of the methods above was thoroughly explained. In the last part, the pros and cons of the methods and the future of the nanotechnology-based biosensors that have been created are discussed.

Sensitive surface-enhanced Raman spectroscopy (SERS) determination of nitrofurazone by β-cyclodextrin-protected AuNPs/γ-Al2O3 nanoparticles

A novel surface-enhanced Raman spectroscopy (SERS) method for the determination of nitrofurazone was developed using AuNPs/γ-Al₂O₃ nanoparticles protected by β-cyclodextrin (β-CD) as substrate prepared in our lab. The optimum experimental conditions were obtained from single factor procedure and response surface modeling. A linear relationship (I_SERS = 508.96c + 31987.87, c: nmol L^-1, R² = 0.996) between SERS intensity and the concentration of nitrofurazone in the range of 3.3 - 667.0 nmol L^-1 was established, the limit of detection (LOD) was found at nmol L^-1 level (0.37 nmol L^-1 by 3S₀/S). The selectivity for the method was studied by the influences of foreign substances on the determination. The recoveries and RSD (n = 5) for the six meat samples were 95.1 % - 104.5% and 2.4 % - 4.8% respectively, which suggesting that the new SERS method was successfully to detecting nitrofurazone.

Plasmonic Paper based Flexible SERS Biosensor for Highly Sensitive Detection of Lactic and Uric Acid

Selective detection and quantification of biomarkers related to human diseases are essential for preventive healthcare. Surface-enhanced Raman scattering (SERS) spectroscopy is a powerful analytical tool offering high sensitivity. However, the success of this promising analytical tool relies on the ability to effectively fabricate SERS substrate. Herein we have demonstrated a plasmonic paper-based flexible substrate (PPFS) for SERS sensing. In situ growth of silver nanostructures (AgNS) on the paper-based substrate was achieved by using a simple one-step silver mirror reaction (SMR). FESEM and TEM results depicts that the increasing silver ion content influences the morphology (growth of multifacets), as well as size of AgNS. Further, the PPFS substrate was tested with Rhodamine-6G (Rh-6G) dye and an attomole sensitivity with a LOD of 4.54 x 10-18 M was achieved. Further, two biomarkers, lactic acid (LA) and uric acid (UA) were detected on the PPFS substrate, with μM and pM sensitivity, having LOD values of 0.6 x 10-6 and 0.3 x 10-12 M respectively. Above detection levels for UA on PPFS is two orders better than reported values, whereas for LA it is comparable with reported substrates. Finally, UA, LA and their mixtures were tested on PPFS and results compared with commercial substrate. The performance of PPFS were found better in all cases, thus, multifaceted AgNS paper based PPFS offers the potential to be used as a biosensor for detection of various biomarkers from body fluids, responsible for the detection of the critical disease for preventive health care.

Ethanol-extraction SERS strategy for highly sensitive detection of poisons in oily matrix

The sensitive detection and identification of toxicants in oily matrices have suffered from difficulty in poisoning incidents, therefore it is necessary to develop the rapid and efficient analytical method to realize the on-site screening and analyzing. In this report, the surface-enhanced Raman spectroscopy (SERS) method was used to detect paraquat and diquat poisons in various oily matrix coupled with solvent extraction. The solvent extraction not only remove interfering impurities of oily substrates, but also can enrich and separate the poisons from oily matrix. It was demonstrated that the ethanol as the extractant was suitable for the rapid separation of poisons such as paraquat (PQ) and diquat (DQ) in oily matrix (soy sauce, pasta sauce, sesame oil, chili oil). Moreover, combined with a handheld Raman spectrometer, the entire detection process was completed within 8 min with the level of 10 ppb PQ and 100 ppb DQ. Furthermore, double-blind experiments verify the reliability of this method. The results demonstrate that this rapid and convenient method could be used for the effective enrichment and sensitive detection of poisons in several oily matrix and has the grate potential application in emergency response and public safety.