In situ SERS monitoring of intracellular H2O2 in single living cells based on label-free bifunctional Fe3O4@Ag nanoparticles

Rapid construction of interfacial plasmonic nanoarray for SERS sensing of flavonoids

A rapid, low-cost and reliable interfacial plasmonic nanoarray is presented as surface-enhanced Raman scattering (SERS) sensing platform for preliminary quantification and identification of flavonoids. Here, CTAB-modified Au colloidal nanoparticles self-assemble at the cyclohexane/acetone-water interface to form a uniform interfacial plasmonic nanoarray. The target hydrophobic analytes including organic dye methyl red and water-insoluble flavonoids, are effectively captured at the air-water interface and enter the "hot spots" between nanoparticles during the evaporation of the oil phase, which contributes to sensitive and reproducible SERS signals. Furthermore, this remarkable SERS performance enables the quantitative determination of water-insoluble flavonoids such as kaempferol, luteolin and naringenin with low detection limits of 10-10 M, and an approximately linear correlation between SERS signals and analytical concentrations, as well as rapid multiplex analysis of flavonoids with similar structural characteristics. Additionally, directly relative content detection of crude extracts from lingonberry (Vaccinium vitis-idaea L.) is achieved on the plasmonic nanoarray, serving as a proof-of-concept demonstration for practical applications. Compared to conventional analyses of flavonoids, the proposed SERS platform circumvents complex and time-consuming pretreatments, thereby opening avenues for the analysis of oil-soluble samples and other secondary metabolites, which will facilitate widespread evaluation of quality and medical value.

Three-dimensional NTF-Ag composites for ultrasensitive SERS-based detection of malachite green on crucian carp skin

Three-dimensional (3D) Na2Ti3O7 flower (NTF) systems were synthesized, followed by sputter coating with silver (Ag) nanoparticles to increase surface-enhanced Raman scattering (SERS) activity. By varying the sputtering time, SERS activity of the Ag-decorated NTF (NTF-Ag) structures was optimized. Furthermore, the theoretical evidence from finite difference time domain (FDTD) simulations confirmed that an appropriate density of Ag particles increased the electromagnetic field contribution. The electromagnetic field contribution is high because the special petal-shaped structure can promote multiple reflections and scattering, thus providing efficient resonance absorption for charge-transfer (CT) and exciton enhancements. Highly SERS-active NTF-Ag composites were developed and exploited for the detection of malachite green (MG), a model contaminant in the food industry. The detection limit of this method for MG reached 3.78 × 10-10 M, with a standard deviation of homogeneity of 6.83 %. This method was successfully applied to detect MG on crucian carp skin, and it showed high recovery, indicating that it can serve as a practical method for MG evaluation. All results demonstrated that the prepared NTF-Ag composite has great potential in the application of SERS-based contamination assessment in the food industry.

Differential Diagnosis of Urinary Cancers by Surface-Enhanced Raman Spectroscopy and Machine Learning

Bladder, kidney, and prostate cancers are prevalent urinary cancers, and developing efficient detection methods is of significance for the early diagnosis of them. However, noninvasive and sensitive detection of urinary cancers still challenges traditional techniques. In this study, we developed a SERS-based method to analyze serum samples from patients with urinary cancers. Rapid, label-free, and highly sensitive detection of human sera is achieved by cleaning and aggregating silver nanoparticles. Furthermore, a long short-term memory deep learning algorithm is used to distinguish serum spectra, and the performance of the model is evaluated by comparing the accuracy, sensitivity, specificity, and receiver operating characteristic curves. Taking advantage of SERS and machine learning in sensitivity and data processing, the three urinary cancers are clearly classified. This is the first attempt to exploit the SERS-machine learning strategy to discriminate multiple urinary cancers with clinical serum samples, and our results showed the potential application of this method in the early diagnosis and screening of cancers.

SERS-Based Aptamer Sensing Strategy for Diabetes Biomarker Detection

Accurate detection of glucose and insulin is crucial for early diagnosis, classification, and timely prevention of diabetes. In this study, we present a novel surface-enhanced Raman scattering (SERS) aptasensor for glucose and insulin detection. The SERS aptasensor is composed of gold bipyramidal nanoparticles (Au BPs), SH-aptamer-methylene blue (MB), and thiolated polyethylene glycol (SH-PEG). As a SERS substrate, the Au BPs provide abundant "hot spots" for the aptasensor to detect target molecules with reasonable sensitivity. One end of the aptamer is modified with a thiol group to facilitate chemical immobilization of SH-aptamer-MB via the Au-S bond, while the other end is functionalized with MB as a probe molecule. SH-PEG is used to block nonspecific adsorption. Glucose and insulin are specifically trapped by SH-aptamer-MB and cause conformational changes in SH-aptamer-MB, which in turn induce changes in the SERS signal of the modified MB, allowing detection of glucose and insulin. Finally, we validated the usefulness of this method on saliva samples and obtained satisfactory results. The proposed aptasensor exhibits strong selectivity and reliable sensitivity and provides an effective strategy for using SERS in disease biomarkers detection.

Light-dependent electron transfer mechanism on a Z-scheme MIL-100(Fe)/AgCl/Ag heterostructure for photocatalytic degradation

Research on the changes in material properties caused by different light sources and the various photocatalytic mechanisms generated is of great significance for exploring new catalysts and improving catalytic efficiency. In this study, a novel composite of MIL-100(Fe)/AgCl/Ag was synthesized for photocatalytic degradation of organic pollutants. Techniques such as ultraviolet (UV)-visible spectroscopy and surface-enhanced Raman spectroscopy (SERS) were employed to monitor the degradation process of small molecule organic pollutants in real-time under different light sources. The research found that the catalytic efficiency of the catalyst under visible light is markedly higher than that under UV light. This phenomenon can attributed to the dynamic changes in the material's properties, particularly the adjustment of the interface electric field under different light sources. Specifically, under UV light irradiation, the catalyst follows a Z-scheme electron transfer pathway to achieve interband transitions. In contrast, under visible light irradiation, it operates through a Z-scheme electron transfer mechanism related to surface plasmon resonance (SPR), which effectively promotes separation of electrons and holes. As a results, the apparent reaction rate is approximately 2.5 times higher compared to that under UV light conditions. This study contributes to a deeper understanding of charge transfer mechanisms in photocatalytic reactions under different wavelength light sources, and could provide valuable insights for designing new light-responsive catalysts to improve their efficiency.

Parallel Monitoring of Glucose, Free Amino Acids, and Vitamin C in Fruits Using a High-Throughput Paper-Based Sensor Modified with Poly(carboxybetaine acrylamide)

Herein, a cost-effective and portable microfluidic paper-based sensor is proposed for the simultaneous and rapid detection of glucose, free amino acids, and vitamin C in fruit. The device was constructed by embedding a poly(carboxybetaine acrylamide) (pCBAA)-modified cellulose paper chip within a hydrophobic acrylic plate. We successfully showcased the capabilities of a filter paper-based microfluidic sensor for the detection of fruit nutrients using three distinct colorimetric analyses. Within a single paper chip, we simultaneously detected glucose, free amino acids, and vitamin C in the vivid hues of cyan blue, purple, and Turnbull's blue, respectively, in three distinctive detection zones. Notably, we employed more stable silver nanoparticles for glucose detection, replacing the traditional peroxidase approach. The detection limits for glucose reached a low level of 0.049 mmol/L. Meanwhile, the detection limits for free amino acids and vitamin C were found to be 0.236 mmol/L and 0.125 mmol/L, respectively. The feasibility of the proposed sensor was validated in 13 different practical fruit samples using spectrophotometry. Cellulose paper utilizes capillary action to process trace fluids in tiny channels, and combined with pCBAA, which has superior hydrophilicity and anti-pollution properties, it greatly improves the sensitivity and practicality of paper-based sensors. Therefore, the paper-based colorimetric device is expected to provide technical support for the nutritional value assessment of fruits in the field of rapid detection.

Research Progress of SERS Sensors Based on Hydrogen Peroxide and Related Substances

Hydrogen peroxide (H2O2) has an important role in living organisms, and its detection is of great importance in medical, chemical, and food safety applications. This review provides a comparison of different types of Surface-enhanced Raman scattering (SERS) sensors for H2O2 and related substances with respect to their detection limits, which are of interest due to high sensitivity compared to conventional sensors. According to the latest research report, this review focuses on the sensing mechanism of different sensors and summarizes the linear range, detection limits, and cellular applications of new SERS sensors, and discusses the limitations in vivo and future prospects of SERS technology for the detection of H2O2.

Competitive Ratiometric Aptasensing with Core-Internal Standard-Shell Structure Based on Surface-Enhanced Raman Scattering

Reproducibility and stability are important indicators for the evaluation of quantitative sensing methods based on surface-enhanced Raman scattering (SERS) technology. Developing a SERS substrate with self-calibration capabilities is vital for effectively quantifying targets. In this work, a competitive ratiometric SERS aptasensor was developed. 4-Aminothiophenol as an internal standard (IS) was embedded in the substrate followed by gradually loading with the aptamer and methylene blue functionalizing of the complementary sequences of the aptamer (MB-cDNA). Recognition and binding of the target to the aptamer resulted in the shedding of MB-cDNA after magnetic separation reducing the SERS signal of MB, allowing for the ratiometric determination of the target based on the constant intensity from the IS. For the selective detection of okadaic acid (OA), a good negative correlation was achieved between the SERS ratiometric intensity and OA concentration in the range of 0.5-100 ng/mL. The magnetic separation strategy effectively simplifies the production steps of the aptasensor, and the ratiometric strategy effectively improved the reproducibility and stability of the OA sensing. This ratiometric aptasensor has been successfully employed to detect OA in food and environmental samples and is expected to be extended to detect other targets.

Rapid and sensitive SERS detection of opioids in solutions based on the solid chip Au-coated Si nano-cone array

Rapid and flexible detection or accurate recognition of trace drugs is of great importance in cracking down on drug crimes, but it remains to be expected. Here, a solid chip is presented for the efficient detection and recognition of trace opioids (typically morphine) in aqueous solutions based on surface-enhanced Raman spectroscopy (SERS). Firstly, a Au-coated Si nano-cone array (Au-SNCA) is designed and fabricated via Si-based organic colloidal template etching and Au deposition. This Au-SNCA shows three-dimensional nanostructure with high densities of nanotips and deep nanogaps as well as high structural consistency, which exhibits strong SERS activity to morphine and outstanding stability. Then, such Au-SNCA is used as solid SERS chip to detect morphine in aqueous solutions. It has been demonstrated that using such solid chip, trace morphine in solutions could be recognized and detected within 1 min, and the detection limit is 10^-5 mg/mL (∼10 ppb), showing rapid and sensitive detection, which is much better than the previous reports. Meanwhile, the Au-SNCA chip also can be utilized to detect trace morphine in tap water and reservoir water, the recoveries range from 90.4% to 102.4%. Such excellent SERS performance of this Au-SNCA chip is attributed to its special structure which enhances not only local electromagnetic field but also molecular adsorption. The experimental results about the effects of immersion time and concentration show that the adsorption behavior of morphine molecules on such Au-SNCA chip can be explained by the pseudo-second-order kinetic model and Freundlich adsorption mode. Moreover, the Au-SNCA chip is also suitable for the identification of morphine homologues and the broad-spectrum detection of various common drugs. This study presents a practical solid chip and a simple approach for the efficient SERS detection and recognition of trace drugs in solutions. This is of significance to on-site detect drugs in forensic science.