Ratiometric surface-enhanced Raman spectroscopy detection of 5-hydroxyindole-3-acetic acid based on Au@MIL-125@MIPs substrates.

5-Hydroxyindole-3-acetic acid (5-HIAA) is a molecular marker that can be used in the early diagnosis of carcinoid tumors, and the development of sophisticated 5-HIAA assays is therefore of great importance. Surface-enhanced Raman spectroscopy (SERS) has been widely used for the rapid and sensitive detection of disease biomarkers. Insufficient specificity for tumor markers and poor spectral reproducibility are the bottlenecks in the practical use of SERS technology. In this study, based on MIL-125 surface-loaded gold nanoparticles (Au@MIL-125), a novel strategy was proposed to obtain Au@MIL-125@molecularly imprinted polymers (MIPs) as functional SERS substrates by wrapping a thin MIP shell around the Au@MIL-125 surface for selective separation followed by a 5-HIAA assay. The Raman peak intensity ratio (I865/I1078) was used to quantify 5-HIAA after a SERS spectral calibration with an embedded internal standard (i.e., 4-aminobenzenethiol) to improve the quantitative accuracy. The linear range was from 10-11 to 10-7 M, and the limit of detection (LOD) was 5.45 × 10-13 M. The method of integrating the MIPs with the metal MOF-based nanocomposites was shown to be useful in the analysis of real samples using SERS. The application of SERS for the selective and quantitative detection of analytes in real sample analysis, therefore, has great potential.

A Highly Sensitive Chitosan-Based SERS Sensor for the Trace Detection of a Model Cationic Dye.

The rapid detection of contaminants in water resources is vital for safeguarding the environment, where the use of eco-friendly materials for water monitoring technologies has become increasingly prioritized. In this context, the role of biocomposites in the development of a SERS sensor is reported in this study. Grafted chitosan was employed as a matrix support for Ag nanoparticles (NPs) for the surface-enhanced Raman spectroscopy (SERS). Chitosan (CS) was decorated with thiol and carboxylic acid groups by incorporating S-acetyl mercaptosuccinic anhydride (SAMSA) to yield CS-SAMSA. Then, Ag NPs were immobilized onto the CS-SAMSA (Ag@CS-SAMSA) and characterized by spectral methods (IR, Raman, NIR, solid state 13C NMR with CP-MAS, XPS, and TEM). Ag@CS-SAMSA was evaluated as a substrate for SERS, where methylene blue (MB) was used as a model dye adsorbate. The Ag@CS-SAMSA sensor demonstrated a high sensitivity (with an enhancement factor ca. 108) and reusability over three cycles, with acceptable reproducibility and storage stability. The Raman imaging revealed a large SERS effect, whereas the MB detection varied from 1-100 µM. The limits of detection (LOD) and quantitation (LOQ) of the biocomposite sensor were characterized, revealing properties that rival current state-of-the-art systems. The dye adsorption profiles were studied via SERS by fitting the isotherm results with the Hill model to yield the ΔG°ads for the adsorption process. This research demonstrates a sustainable dual-function biocomposite with tailored adsorption and sensing properties suitable for potential utility in advanced water treatment technology and environmental monitoring applications.

Rapid detection of African swine fever virus via SERS probe-modified sandwich hybridization assay.

Rapid and reliable detection method for African swine fever virus (ASFV) is proposed by surface-enhanced Raman spectroscopy (SERS). The ASFV target DNA can be specifically captured by sandwich hybridization between nanomagnetic beads and a SERS probe. Experimental results show that the significant Raman signal of the SERS probe with gold nanoparticles and a molecular reporter DTNB (5,5'-dimercapto-bis (2-nitrobenzoic acid)) can be adopted for detecting the hybridization chain reaction of ASFV DNA. The advantage of the SERS sandwich hybridization assay is the large response range from the single molecule level to 108 copies per mL, which not only can overcome the tedious time required for the amplification reaction but also provides a comparative method to polymerase chain reaction. Furthermore, real samples of African swine fever virus were detected from different subjects of swine fever virus including porcine reproductive respiratory syndrome virus and Japanese encephalitis virus. The proposed biosensor method can rapidly detect ASFV correctly within 15 min as a simple, convenient, low-cost detection approach. The biosensor can be used as a platform for the determination in biological, food, and environmental analytical fields.

Speciation Analysis of Metals and Metalloids by Surface Enhanced Raman Spectroscopy.

The presence of metalloids and heavy metals in the environment is of critical concern due to their toxicological impacts. However, not all metallic species have the same risk level. Specifically, the physical, chemical, and isotopic speciation of the metal(loids) dictate their metabolism, toxicity, and environmental fate. As such, speciation analysis is critical for environmental monitoring and risk assessment. In the past two decades, surface-enhanced Raman spectroscopy (SERS) has seen significant developments regarding trace metal(loid) sensing due to its ultrahigh sensitivity, readiness for in situ real-time applications, and cost-effectiveness. However, the speciation of metal(loid)s has not been accounted for in the design and application of SERS sensors. In this Perspective, we examine the potential of SERS for metal(loid) speciation analysis and highlight the advantages, progress, opportunities, and challenges of this application.

Yolk-Shell Hierarchical Pore Au@MOF Nanostructures: Efficient Gas Capture and Enrichment for Advanced Breath Analysis.

Surface-enhanced Raman scattering (SERS) offers a promising, cost-effective alternative for the rapid, sensitive, and quantitative analysis of potential biomarkers in exhaled gases, which is crucial for early disease diagnosis. However, a major challenge in SERS is the effective detection of gaseous analytes, primarily due to difficulties in enriching and capturing them within the substrate's "hotspot" regions. This study introduces an advanced gas sensor combining mesoporous gold (MesoAu) and metal-organic frameworks (MOFs), exhibiting high sensitivity and rapid detection capabilities. The MesoAu provides abundant active sites and interconnected mesopores, facilitating the diffusion of analytes for detection. A ZIF-8 shell enveloping MesoAu further enriches target molecules, significantly enhancing sensitivity. A proof-of-concept experiment demonstrated a detection limit of 0.32 ppb for gaseous benzaldehyde, indicating promising prospects for the rapid diagnosis of early stage lung cancer. This research also pioneers a novel approach for constructing hierarchical plasmonic nanostructures with immense potential in gas sensing.

Oppositely-charged silver nanoparticles enable selective SERS molecular enhancement through electrostatic interactions.

Label-free surface-enhanced Raman spectroscopy (SERS) has attracted extensive attention as an emerging technique for molecular phenotyping of biological samples. However, the selective enhancement property of SERS mediated by complicated interactions between substrates and analytes is unfavorable for molecular profiling. The electrostatic force is among the most dominating interactions that can cause selective adsorption of molecules to charged substrates. This means if only negatively- or positively-charged SERS substrates are applied, then considerable SERS information from a portion of analytes would be lost, hindering comprehensive SERS sensing. In this work, we utilize both negatively- and positively-charged colloidal silver (Ag) nanoparticles (NPs) to detect various charged molecules. The negatively-charged citrate-stabilized Ag and the positively-charged Ag prepared via a cetyltrimethyl-ammonium chloride-based charge reversal protocol have been adopted as SERS substrates. The Ag NPs are all relatively well-dispersed with good uniformity. After applying the oppositely-charged NPs to the detection of charged molecules, we find the SERS results explicitly demonstrate the electrostatically-driven SERS selective enhancement, which is further supported and clarified by molecular electrostatic potential calculations. Our work highlights the importance of developing SERS substrates modified with appropriate surface charges for various analytes, and enlightens us that potentially more molecular SERS information can be acquired from complex bio-samples using combinations of oppositely-charged substrates.

Facile Preparation of TiO2NTs/Au@MOF Nanocomposites for High-Sensitivity SERS Sensing of Gaseous VOC.

Surface-enhanced Raman spectroscopy (SERS) is a promising and highly sensitive molecular fingerprint detection technology. However, the development of SERS nanocomposites that are label-free, highly sensitive, selective, stable, and reusable for gaseous volatile organic compounds (VOCs) detection remains a challenge. Here, we report a novel TiO2NTs/AuNPs@ZIF-8 nanocomposite for the ultrasensitive SERS detection of VOCs. The three-dimensional TiO2 nanotube structure with a large specific surface area provides abundant sites for the loading of Au NPs, which possess excellent local surface plasmon resonance (LSPR) effects, further leading to the formation of a large number of SERS active hotspots. The externally wrapped porous MOF structure adsorbs more gaseous VOC molecules onto the noble metal surface. Under the synergistic mechanism of physical and chemical enhancement, a better SERS enhancement effect can be achieved. By optimizing experimental conditions, the SERS detection limit for acetophenone, a common exhaled VOC, is as low as 10-11 M. And the relative standard deviation of SERS signal intensity from different points on the same nanocomposite surface is 4.7%. The acetophenone gas achieves a 1 min response and the signal reaches stability in 4 min. Under UV irradiation, the surface-adsorbed acetophenone can be completely degraded within 40 min. The experimental results demonstrate that this nanocomposite has good detection sensitivity, repeatability, selectivity, response speed, and reusability, making it a promising sensor for gaseous VOCs.

Nanoplasmonic sensors for extracellular vesicles and bacterial membrane vesicles.

Extracellular vesicles (EVs) are promising tools for the early diagnosis of diseases, and bacterial membrane vesicles (MVs) are especially important in health and environment monitoring. However, detecting EVs or bacterial MVs presents significant challenges for the clinical translation of EV-based diagnostics. In this Review, we provide a comprehensive discussion on the basics of nanoplasmonic sensing and emphasize recent developments in nanoplasmonics-based optical sensors to effectively identify EVs or bacterial MVs. We explore various nanoplasmonic sensors tailored for EV or bacterial MV detection, emphasizing the application of localized surface plasmon resonance through gold nanoparticles and their multimers. Additionally, we highlight advanced EV detection techniques based on surface plasmon polaritons using plasmonic thin film and nanopatterned structures. Furthermore, we evaluate the improved detection capability of surface-enhanced Raman spectroscopy in identifying and classifying these vesicles, aided by plasmonic nanostructures. Nanoplasmonic sensing techniques have remarkable precision and sensitivity, making them a potential tool for accurate EV detection in clinical applications, facilitating point-of-care molecular diagnostics. Finally, we summarize the challenges associated with nanoplasmonic EV or bacterial MV sensors and offer insights into potential future directions for this evolving field.

A review on nanomaterial-based SERS substrates for sustainable agriculture.

The agricultural sector plays a pivotal role in driving the economy of many developing countries. Any dent in this economical structure may have a severe impact on a country's population. With rising climate change and increasing pollution, the agricultural sector is experiencing significant damage. Over time this cumulative damage will affect the integrity of food crops and create food security issues around the world. Therefore, an early warning system is needed to detect possible stress on food crops. Here we present a review of the recent developments in nanomaterial-based Surface Enhanced Raman Spectroscopy (SERS) substrates which could be utilized to monitor agricultural crop responses to natural and anthropogenic stress. Initially, our review delves into diverse and cost-effective strategies for fabricating SERS substrates, emphasizing their intelligent utilization across various agricultural scenarios. In the second phase of our review, we spotlight the specific application of SERS in addressing critical food security issues. By detecting nutrients, hormones, and effector molecules in plants, SERS provides valuable insights into plant health. Furthermore, our exploration extends to the detection of contaminants, chemicals, and foodborne pathogens within plants, showcasing the versatility of SERS in ensuring food safety. The cumulative knowledge derived from these discussions illustrates the transformative potential of SERS in bolstering the agricultural economy. By enhancing precision in nutrient management, monitoring plant health, and enabling rapid detection of harmful substances, SERS emerges as a pivotal tool in promoting sustainable and secure agricultural practices. Its integration into agricultural processes not only augments productivity but also establishes a robust defence against potential threats to crop yield and food quality. As SERS continues to evolve, its role in shaping the future of agriculture becomes increasingly pronounced, promising a paradigm shift in how we approach and address challenges in food production and safety.

Machine learning-assisted SERS approach enables the biochemical discrimination in Bcl-2 and Mcl-1 expressing yeast cells treated with ketoconazole and fluconazole antifungals.

Antifungal medications are important due to their potential application in cancer treatment either on their own or with traditional treatments. The mechanisms that prevent the effects of these medications and restrict their usage in cancer treatment are not completely understood. The evaluation and discrimination of the possible protective effects of the anti-apoptotic members of the Bcl-2 family of proteins, critical regulators of mitochondrial apoptosis, against antifungal drug-induced cell death has still scientific uncertainties that must be considered. Novel, simple, and reliable strategies are highly demanded to identify the biochemical signature of this phenomenon. However, the complex nature of cells poses challenges for the analysis of cellular biochemical changes or classification. In this study, for the first time, we investigated the probable protective activities of Bcl-2 and Mcl-1 proteins against cell damage induced by ketoconazole (KET) and fluconazole (FLU) antifungal drugs in a yeast model through surface-enhanced Raman spectroscopy (SERS) approach. The proposed SERS platform created robust Raman spectra with a high signal-to-noise ratio. The analysis of SERS spectral data via advanced unsupervised and supervised machine learning methods enabled unquestionable differentiation (100 %) in samples and biomolecular identification. Various SERS bands related to lipids and proteins observed in the analyses suggest that the expression of these anti-apoptotic proteins reduces oxidative biomolecule damage induced by the antifungals. Also, cell viability assay, Annexin V-FITC/PI double staining, and total oxidant and antioxidant status analyses were performed to support Raman measurements. We strongly believe that the proposed approach paves the way for the evaluation of various biochemical structures/changes in various cells.

Investigation of Melphalan interaction as an alkylating agent with nucleotides by using surface enhanced Raman spectroscopy (SERS).

SERS (Surface Enhanced Raman Spectroscopy) is a new Raman spectroscopy which relies on Surface Plasmon Resonance (SPR) of metal nanoparticles. We have applied colloidal silver and gold nanoparticles as amplifier agents to enhance nucleotide Raman signals. It is observed that without these enhancing agents, it is impossible to investigate nucleotide spectrum due to weak Raman signals. Interaction mechanism of Melphalan, an anticancer drug with four nucleotides (Adenine, Cytosine, Guanine, Thymine) was investigated using SERS to detect and identify changes due to alkylating process in Raman spectra. After incubating Melphalan drug with nucleotides for 24 h at 37 °C, some changes occurred in SERS spectrum and interpretation of SERS spectra revealed the influence of the alkyl substitution on peaks and Raman shifts. After incubation of Melphalan with each nucleotide, intensity of relevant SERS signals assigned to Amid III group of Cytosine and Amid I of Thymine decreased significantly, confirming alkylating taking place. In this study, we also investigated the effect of nanoparticles type on nucleotide spectrum. We could not obtain useful information in the cases of guanine nucleotide. The SERS spectrum of Cytosine as an example of nucleotides in aqueous solution compared to solid state and results demonstrated that in solid state better signals were obtained than in liquid state.

Diagnosis of neuropsychiatric systemic lupus erythematosus by label-free serum microsphere-coupled SERS fingerprints with machine learning.

Surface-enhanced Raman spectroscopy (SERS) is a powerful optical technique for non-invasive and label-free bioanalysis of liquid biopsy, facilitating to diagnosis of potential diseases. Neuropsychiatric systemic lupus erythematosus (NPSLE) is one of the subgroups of systemic lupus erythematosus (SLE) with serious manifestations for a high mortality rate. Unfortunately, lack of well-established gold standards results in the clinical diagnosis of NPSLE being a challenge so far. Here we develop a novel Raman fingerprinting machine learning (ML-) assisted diagnostic method. The microsphere-coupled SERS (McSERS) substrates are employed to acquire Raman spectra for analysis via convolutional neural network (CNN). The McSERS substrates demonstrate better performance to distinguish the Raman spectra from serums between SLE and NPSLE, attributed to the boosted signal-to-noise ratio of Raman intensities due to the multiple optical regulation in microspheres and AuNPs. Eight statistically-significant (p-value <0.05) Raman shifts are identified, for the first time, as the characteristic spectral markers. The classification model established by CNN algorithm demonstrates 95.0% in accuracy, 95.9% in sensitivity, and 93.5% in specificity for NPSLE diagnosis. The present work paves a new way achieving clinical label-free serum diagnosis of rheumatic diseases by enhanced Raman fingerprints with machine learning.

Exploring the nanoscale: AFM-IR visualization of cysteine adsorption on gold nanoparticles.

This study focuses on the adsorption process of L-cysteine (Cys), a sulfur-containing amino acid, onto monolayers of gold nanoparticles (AuNPs) prepared through distinct protocols on mica substrates. Two types of AuNPs were prepared using two different methods: the first employed a physical approach, which combined the Inert Gas Condensation (IGC) technique with the magnetron sputtering method, while the second utilized a chemical method involving the reduction of tetrachloroauric acid with trisodium citrate (TC). The characterization of AuNPs was performed using transmission electron microscopy (TEM) and atomic force microscopy (AFM), of up to 5 ± 1.3 nm for bare AuNPs obtained through vacuum techniques, and up to 12 ± 5 nm for negatively charged, citrate-stabilized TCAuNPs(-). The application of spectroscopic techniques based on the surface-enhanced effects allows for describing the adsorption process in both micro- and nanoscale systems: Cys/bare AuNPs and Cys/ TCAuNPs(-). The commonly used surface-enhanced Raman spectroscopy (SERS) technique provided insights into adsorption behaviours at the microscale level. In the case of TCAuNPs(-), an interaction involving the lone electron pair of sulfur (S) atom and metal surface, while on the bare AuNPs, S is adsorbed on the surface, but the cleavage of the SH group is not discernible. Nanoscale analysis was complemented using AFM combined with the surface-enhanced infrared absorption spectroscopy (AFM-SEIRA) technique. AFM-SEIRA map indicated the formation of hot spot which were predominantly located between aggregated TCAuNPs(-) and on specific NPs surfaces (area between NPs and gold-coated tip). Results from the SERS and AFM-SEIRA techniques were in good agreement, underscoring the comprehensive understanding achieved through the chosen experimental approach regarding the Cys interactions with layers of AuNPs.

Quantitative analysis of four PAHs in oily sludge by surface-enhanced Raman spectroscopy (SERS) combined with partial least squares regression (PLS) based on a novel nano-silver-silicon coupling substrate.

Polycyclic aromatic hydrocarbons (PAHs) present in oily sludge generated by the petroleum and petrochemical industries have emerged as a prominent concern within the realm of environmental conservation. The precise determination of PAHs holds immense significance in both petroleum geochemistry and environmental protection. In this study, a combination of surface-enhanced Raman spectroscopy (SERS) and solid-liquid extraction was employed for the screening of PAHs in oily sludge. Methanol was utilized as the extraction solvent for PAHs, while nanosilver-silicon coupling substrates were employed for their detection. The SERS spectrum was acquired using a portable Raman spectrometer. The nano silver-silicon coupling substrate exhibits excellent uniformity, with relative standard deviations (RSDs) of Phenanthrene, Fluoranthrene, Fluorene and Naphthalene (Phe, Flt, Flu and Nap) being 2.8%, 1.08%, 1.41%, and 5.44% respectively. Moreover, the limits of detection (LODs) achieved remarkable values of 0.542 µg/g, 0.342 µg/g, 0.541 µg/g, and 5.132 µg/g. The quantitative analysis of PAHs in oily sludge was investigated using SERS technology combined with partial least squares (PLS). The optimal PLS calibration model was optimized by combining spectral preprocessing methods and using the SiPLS (Synergy interval partial least squares)-VIP (Variable Importance in Projection) hybrid variable selection strategy. The prediction performance of the D1st (First derivative)-WT (Wavelet transform)-SiPLS-VIP-PLS model was deemed satisfactory, as evidenced by high R2P values of 0.9851, 0.9917, and 0.9925 for Phe, Flt, and Flu respectively; additionally, the corresponding MREP values were found to be 0.0580, 0.0668, and 0.0669 respectively. However, for Nap analysis, the D1st-WT-PLS model proved to be a better calibration model with an R2P value of 0.9864 and an MREP (Mean relative error of prediction) value of 0.0713. In summary, SERS technology combined with PLS based on different spectral pretreatment methods and mixed variable selection strategies is a promising method for quantitative analysis of PAHs in oily sludge, which will provide new ideas and methods for the quantitative analysis of PAHs in oily sludge.

Colorimetric and SERS dual-mode detection of GSH in human serum based on AuNPs@Cu-porphyrin MOF nanozyme.

BACKGROUND: Rapid and accurate detection of glutathione content in human blood plays an important role in real-time tracking of related diseases. Currently, surface-enhanced Raman scattering/spectroscopy (SERS) combined with nanozyme material has been proven to have excellent properties in the detection applications compared to many other methods because of it combines the advantages of trace detection capability of SERS and efficient catalytic activity of nanozymes. However, there are still existing problems in real sample detection, and to achieve quantitative detection is still challenging. RESULTS: In this study, gold nanoparticles (AuNPs) were synthesized in situ on the surface of two-dimensional Cu-porphyrin metal-organic framework (MOF) nanosheets to produce the AuNPs@Cu-porphyrin MOF nanozyme, which exhibited both oxidase-like activity and SERS detection ability. On one hand, the intrinsic oxidase-like activity of the nanozyme could be inhibited due to the chelation of glutathione (GSH) and Cu, which thus led to the visual color change of the solution. On the other hand, the abundant Raman "hot spots" at the nanogap generated by Au NPs and the internal standard (IS) signal provided by Cu-meso-tetra (4-carboxyphenyl) porphine (Cu-TCPP) MOF improved the sensitivity and quantitative accuracy of detection. SIGNIFICANCE AND NOVELTY: A dual-mode signal output sensor based on the nanozyme was thus established, which could be used in the trace detection of GSH. Such a dual-mode sensor possesses excellent detection performance, with the advantage of both wide detection range from 1 to 300 µM in the colorimetric detection mode and high sensitivity with LOD of 5 nM in the SERS detection mode, and can be applied to GSH detection in actual serum samples with reliable results.

Plasmonic-mediated SC arylation and SS coupling on nanostructured silver electrodes monitored by in situ surface-enhanced Raman spectroscopy.

Plasmon-mediated chemical reaction (PMCR) is a highly attractive field of research. Here we report in situ surface-enhanced Raman spectroscopic (SERS) monitoring of plasmonic-mediated SS bond-forming reaction. The reaction is thought to be a self-coupling reaction proceeding by photoinduced aromatic SC bond arylation. Surprisingly, the SC arylation and SS coupling are found to be occurred on both partially oxidized silver and silver nanoparticles. The results demonstrated that silver oxide or hydroxide and small molecule donor sacrifice agent played a crucial role in the reaction. This work facilitates the in-situ manipulation and characterization of the active silver electrode interface in conjunction with electrochemistry, and also establishes a promising new guideline for surface plasmon resonance photocatalytic reactions on metal nanostructures with high efficiency.

Surface-Enhanced Raman Spectroscopy (SERS) for Identifying Traces of Adenine in Organic-Bearing Extraterrestrial Dust Analogs Captured in the Tanpopo Aerogel after Hypervelocity Impacts.

Raman spectroscopy is a non-destructive analytical technique for characterizing organic and inorganic materials with spatial resolution in the micrometer range. This makes it a method of choice for space-mission sample characterization, whether on return or in situ. To enhance its sensitivity, we use signal amplification via interaction with plasmonic silver-based colloids, which corresponds to surface-enhanced Raman scattering (SERS). In this study, we focus on the analysis of biomolecules of prebiotic interest on extraterrestrial dust trapped in silica aerogel, jointly with the Japanese Tanpopo mission. The aim is twofold: to prepare samples as close as possible to the real ones, and to optimize analysis by SERS for this specific context. Serpentinite was chosen as the inorganic matrix and adenine as the target biomolecule. The dust was projected at high velocity into the trapping aerogel and then mechanically extracted. A quantitative study shows effective detection even for adenine doping from a 5·10-9mol/L solution. After the dust has been expelled from the aerogel using a solvent, SERS mapping enables unambiguous adenine detection over the entire dust surface. This study shows the potential of SERS as a key technique not only for return samples, but also for upcoming new explorations.

Recent Studies on Metal-Embedded Silica Nanoparticles for Biological Applications.

Recently, silica nanoparticles (NPs) have attracted considerable attention as biocompatible and stable templates for embedding noble metals. Noble-metal-embedded silica NPs utilize the exceptional optical properties of novel metals while overcoming the limitations of individual novel metal NPs. In addition, the structure of metal-embedded silica NPs decorated with small metal NPs around the silica core results in strong signal enhancement in localized surface plasmon resonance and surface-enhanced Raman scattering. This review summarizes recent studies on metal-embedded silica NPs, focusing on their unique designs and applications. The characteristics of the metal-embedded silica NPs depend on the type and structure of the embedded metals. Based on this progress, metal-embedded silica NPs are currently utilized in various spectroscopic applications, serving as nanozymes, detection and imaging probes, drug carriers, photothermal inducers, and bioactivation molecule screening identifiers. Owing to their versatile roles, metal-embedded silica NPs are expected to be applied in various fields, such as biology and medicine, in the future.

Magnetic solid-phase extraction-based surface-enhanced Raman spectroscopy for label-free therapeutic drug monitoring of carbamazepine and clozapine in human serum.

Determination of antiepileptic drugs and antipsychotics in human serum is significant in individualized drug administration and therapeutic drug monitoring (TDM). In this study, we developed a rapid label-free TDM method for the antiepileptic drug carbamazepine (CBZ) and the antipsychotic clozapine (CLO) in human serum. This detection strategy is based on the combination of surface-enhanced Raman scattering (SERS) and magnetic solid-phase extraction (MSPE). Initially, Fe3O4@SiO2@MIL-101(Fe) nanocomposites were synthesized by the layer-by-layer self-assembly method and characterized using scanning electron microscopy, transmission electron microscopy, X-ray diffraction, Brunauer-Emmett-Teller, ultraviolet-visible, and Fourier transform infrared analyses. Subsequently, CBZ and CLO were detected in human serum using Fe3O4@SiO2@MIL-101(Fe) as the solid-phase extraction adsorbent and Ag nanoparticles as SERS substrates. The potential of the MSPE-SERS method for the label-free TDM of CBZ and CLO was then investigated. Fe3O4@SiO2@MIL-101(Fe) prevents magnetic particle aggregation and demonstrates rapid magnetic separation capability that simplifies the pretreatment process and reduces interference from complex matrices. Its large surface area can effectively enrich targets in complex matrices, thereby improving the SERS detection sensitivity. The linearity between CBZ and CLO was excellent over the concentration range of 0.1-100 µg/mL (calculated as the intensity of the SERS characteristic peaks of CBZ and CLO at 728 cm and 1054 cm-1, respectively), with correlation coefficients (R2) of 0.9987 and 0.9957, and detection limits of 0.072 and 0.12 µg/mL, respectively. The recoveries of CBZ with CLO ranged from 94.0 % to 105.0 %, and their relative standard deviations were <6.8 %. Compared to other assays, the developed MSPE-SERS method has the advantages of simple sample pretreatment, rapid detection, and good reproducibility, which provides a novel approach for the TDM of other drugs.

Plasmonic Dodecahedral-Walled Elongated Nanoframes for Surface-Enhanced Raman Spectroscopy.

Here, elongated pseudohollow nanoframes composed of four rectangular plates enclosing the sides and two open-frame ends with four ridges pointing at the tips for near-field focusing are reported. The side facets act as light-collecting domains and transfer the collected light to the sharp tips for near-field focusing. The nanoframes are hollow inside, allowing the gaseous analyte to penetrate through the entire architecture and enabling efficient detection of gaseous analytes when combined with Raman spectroscopy. The resulting nanostructures are named Au dodecahedral-walled nanoframes. Synthesis of the nanoframes involves shape transformation of Au nanorods with round tips to produce Au-elongated dodecahedra, followed by facet-selective Pt growth, etching of the inner Au, and regrowth steps. The close-packed assembly of Au dodecahedral-walled nanoframes exhibits an attomolar limit of detection toward benzenethiol. This significant enhancement in SERS is attributed to the presence of a flat solid terrace for a large surface area, sharp edges and vertices for strong electromagnetic near-field collection, and open frames for effective analyte transport and capture. Moreover, nanoframes are applied to detect chemical warfare agents, specifically mustard gas simulants, and 20 times higher sensitivity is achieved compared to their solid counterparts.