Developing a magnetic SERS nanosensor utilizing aminated Fe-Based MOF for ultrasensitive trace detection of organophosphorus pesticides in apple juice

The unreasonable use of organophosphorus pesticides leads to excessive pesticide residues in food, seriously threatening public health, and the potential of surface-enhanced Raman spectroscopy (SERS) technology, incorporating a metal-organic framework, is substantial for the rapid detection of trace pesticide residues. Here, a novel Fe3O4@NH2-MIL-101(Fe)@Ag (FNMA) SERS nanosensor was developed. Results indicated that the FNMA had a high enhancement factor of 1.53 × 108, a low limit of detection (LOD) of 4.55 × 10-12 M, and a relative standard deviation of 7.73 % for 4-nitrothiophenol, demonstrating its good SERS sensitivity and uniformity, and also possessed good storage stability for one month. In quantifying fenthion and methyl parathion in standard solutions and apple juice in the range of 0.05/0.02-20 mg/L, it showed LODs of 3.02 × 10-3 mg/L and 1.43 × 10-3 mg/L, and 0.0407 and 0.0075 mg/L, respectively, demonstrating potentials in ultrasensitive trace detection of pesticides in food.

Label-free plasmonic spectral profiling of serum DNA

Genetic and epigenetic modifications are linked to the activation of oncogenes and inactivation of tumor suppressor genes. Likewise, the associated molecular alternations can best inform precision medicine for personalized tumor treatment. Therefore, performing characterization of genetic and epigenetic alternations at the molecular level represents a crucial step in early diagnosis and/or therapeutics of cancer. However, the prevailing methods for DNA analysis involve a series of tedious and complicated steps, in which important genetic and epigenetic information could be lost or altered. To provide a potential approach for non-invasive, direct, and efficient DNA analysis, herein, we present a promising strategy for label-free molecular profiling of serum DNA in its pristine form by fusing surface-enhanced Raman spectroscopy with machine learning on a superior plasmonic nanostructured platform. Using DNA methylation and single-point mutation as two case studies, the presented strategy allows a well-balanced sensitive and specific detection of epigenetic and genetic changes at the single-nucleotide level in serum. We envision the presented label-free strategy could serve as a versatile tool for direct molecular profiling in pristine forms of a wide range of biological markers and aid biomedical diagnostics as well as therapeutics.

Sandwich-like CuNPs@AgNPs@PSB SERS substrates for sensitive detection of R6G and Forchlorfenuron

The development of a highly sensitive, synthetically simple and economical SERS substrate is technically very important. A fast, economical, sensitive and reproducible CuNPs@AgNPs@ Porous silicon Bragg reflector (PSB) SERS substrate was prepared by electrochemical etching and in situ reduction method. The developed CuNPs@AgNPs@PSB has a large specific surface area and abundant "hot spot" region, which makes the SERS performance excellent. Meanwhile, the successful synthesis of CuNPs@AgNPs can not only modulate the plasmon resonance properties of nanoparticles, but also effectively prolong the time stability of Cu nanoparticles. The basic performance of the substrate was evaluated using rhodamine 6G (R6G). (Detection limit reached 10-15 M, R2 = 0.9882, RSD = 5.3 %) The detection limit of Forchlorfenuron was 10 μg/L. The standard curve with a regression coefficient of 0.979 was established in the low concentration range of 10 μg/L -100 μg/L. This indicates that the prepared substrates can accomplish the detection of pesticide residues in the low concentration range. The prepared high-performance and high-sensitivity SERS substrate have a very promising application in detection technology.

SERS-based AI diagnosis of lung and gastric cancer via exhaled breath

Distinct diagnosis between Lung cancer (LC) and gastric cancer (GC) according to the same biomarkers (e.g. aldehydes) in exhaled breath based on surface-enhanced Raman spectroscopy (SERS) remains a challenge in current studies. Here, an accurate diagnosis of LC and GC is demonstrated, using artificial intelligence technologies (AI) based on SERS spectrum of exhaled breath in plasmonic metal organic frameworks nanoparticle (PMN) film. In the PMN film with optimal structure parameters, 1780 SERS spectra are collected, in which 940 spectra come from healthy people (n = 49), another 440 come from LC patients (n = 22) and the rest 400 come from GC patients (n = 8). The SERS spectra are trained through artificial neural network (ANN) model with the deep learning (DL) algorithm, and the result exhibits a good identification accuracy of LC and GC with an accuracy over 89 %. Furthermore, combined with information of SERS peaks, the data mining in ANN model is successfully employed to explore the subtle compositional difference in exhaled breath from healthy people (H) and L/GC patients. This work achieves excellent noninvasive diagnosis of multiple cancer diseases in breath analysis and provides a new avenue to explore the feature of disease based on SERS spectrum.

Exploring the effect of high pressure in the denaturation of casein micelles by in-situ SERS

To investigate the structural changes of casein in response to the pressurization process under varying pressure levels, this study carried out both ex-situ and in-situ high-pressure experiments. In the in-situ experiments, the surface-enhanced Raman scattering (SERS) technique was combined with a diamond anvil cell (DAC). The high-pressure experiments indicated that significant dissociation of casein occurred at 200 MPa. Over the range of 0-302 MPa, casein exhibited both dissociation and aggregation behaviors. However, casein tended towards aggregation at pressures of 302-486 MPa, with a further increase observed beyond 486 MPa.

Rapid and accurate SERS assay of disease-related nucleic acids based on isothermal cascade signal amplifications of CRISPR/Cas13a system and catalytic hairpin assembly

Developing rapid, accurate and convenient nucleic acid diagnostic techniques is essential for the prevention and control of contagious diseases that are prone to gene mutations and may have homologous sequences, especially emerging infectious diseases such as the SARS-CoV-2 pandemic. Herein, a one-pot SERS assay integrating isothermal cascade signal amplification strategy (i.e., CRISPR/Cas13a system (Cas13a) and catalytic hairpin assembly (CHA), Cas13a-CHA) and SERS-active silver nanorods (AgNRs) sensing chips was proposed for rapid and accurate detection of disease-related nucleic acids. Taking SARS-CoV-2 RNA assay as a model, the Cas13a-CHA based SERS sensing strategy can achieve ultra-high sensitivity low to 5.18 × 102 copies·mL-1 within 60 min, and excellent specificity, i.e., not only the ability to identify SARS-CoV-2 RNA from gene mutations, but also incompatibility with coronaviruses such as severe acute respiratory syndrome (SARS-CoV), Middle East respiratory syndrome (MERS-CoV), and other respiratory viruses. The proposed Cas13a-CHA based SERS assay for SARS-CoV-2 RNA has satisfactory sensitivity, specificity, uniformity, and repeatability, and can be easily expanded and universalized for screening different viruses, which is expected to promise as a crucial role for diagnosis of disease-related nucleic acids in various medical application scenarios.

Quantitative detecting low concentration polystyrene nanoplastics in aquatic environments via an Ag/Nb2CTx (MXene) SERS substrate

In this study, the plasmonic Ag nanoparticles (Ag NPs) were uniformly anchored on the high conductivity Nb2CTx (MXene) nanosheets to construct an Ag/Nb2CTx substrate for surface-enhanced Raman spectroscopy (SERS) detection of polystyrene (PS) nanoplastics. The KI addition (0.15 mol/L), the volume ratio between substrate colloid and nanoplastic suspension (2:1), and the mass ratio of Nb2CTx in substrate (14%) on SERS performance were optimized. The EM hot spots of Ag/Nb2CTx are significantly enlarged and enhanced, elucidated by FDFD simulation. Then, the linear relationship between the PS nanoplastics concentration with three different sizes (50, 300, and 500 nm) and the SERS intensity was obtained (R2 > 0.976), wherein, the detection limit was as low as 10-4 mg/mL for PS nanoplastic. Owing to the fingerprint feature, the Ag/Nb2CTx-14% substrate successfully discerns the mixtures from two-component nanoplastics. Meanwhile, it exhibits excellent stability of PS nanoplastics on different detection sites. The recovery rates of PS nanoplastics with different sizes in lake water ranged from 94.74% to 107.29%, with the relative standard deviation (RSD) ranging from 2.88% to 8.30%. Based on this method, the expanded polystyrene (EPS) decomposition behavior was evaluated, and the PS concentrations in four water environments were analyzed. This work will pave the way for the accurate quantitative detection of low concentration of nanoplastics in aquatic environments.

Green and sustainable self-cleaning flexible SERS base: Utilized for cyclic-detection of residues on apple surface

Advances in flexible SERS substrates has made it possible to approach the ultimate goal of rapid in-situ monitoring of fruit and vegetable safety, but its vulnerability under laser ablation results in low utilization. In order to solve this problem, a 3D framework of TiO2-doped PVDF\PVP polymer was utilized to self-assemble gold-silver core-shell nanorods (Au@Ag NRs) to prepare a flexible SERS substrate with good physical stability and self-cleaning properties. This substrate showed excellent detection limit and recyclability after the detection of three pesticide residues in apple peel. The LOD of methyl-parathion (MP) was as low as 0.037 ng/cm2, with an RSD of 5.61 % for 5 cycle-detection. The recoveries of two additional pesticides thiram (TMTD) and chlorpyrifos (CPF) were 86.32 %-112.47 %. We hoped that this research will contribute to providing a recyclable and facile method for in-situ analysis of fruit and vegetable surface residues and functional manufacture of flexible SERS substrates.

Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinach

This study introduces an innovative strategy for the rapid and accurate identification of pesticide residues in agricultural products by combining surface-enhanced Raman spectroscopy (SERS) with a state-of-the-art transformer model, termed SERSFormer. Gold-silver core-shell nanoparticles were synthesized and served as high-performance SERS substrates, which possess well-defined structures, uniform dispersion, and a core-shell composition with an average diameter of 21.44 ± 4.02 nm, as characterized by TEM-EDS. SERSFormer employs sophisticated, task-specific data processing techniques and CNN embedders, powered by an architecture features weight-shared multi-head self-attention transformer encoder layers. The SERSFormer model demonstrated exceptional proficiency in qualitative analysis, successfully classifying six categories, including five pesticides (coumaphos, oxamyl, carbophenothion, thiabendazole, and phosmet) and a control group of spinach data, with 98.4% accuracy. For quantitative analysis, the model accurately predicted pesticide concentrations with a mean absolute error of 0.966, a mean squared error of 1.826, and an R2 score of 0.849. This novel approach, which combines SERS with machine learning and is supported by robust transformer models, showcases the potential for real-time pesticide detection to improve food safety in the agricultural and food industries.

An in-situ method for SERS substrate preparation and optimization based on galvanic replacement reaction

BACKGROUND

Various surface-enhanced Raman spectroscopy (SERS) substrate preparation methods have been reported, however, how to tune the "gap" between nanostructures to make more "hot spots" is still a barrier that restricts their application. The gap between nanostructures is usually fixed when the substrates are prepared. In other words, it is hard to tune interparticle distances for maximum electromagnetic coupling during substrate preparation process. Therefore, an in-situ substrate optimization method that could monitor the SERS signal intensity changes, i.e., to find the optimum gap width and particle size, during substrate preparation process is needed.

RESULTS

A method based on the galvanic replacement reaction (GRR) is proposed for the in-situ gap width tuning between nanostructures as well as for the optimization of SERS substrates. Noble metal nanoparticles (NPs) form and grow on the sacrificial templates' surface while noble metal ions are reduced by sacrificial metal (oxides) in GRR. Along with the fresh and clean NPs' surface generated, the gap between two noble metal NPs decreases with the growth of the NPs. To demonstrate this strategy, cuprous oxide/Ti (Cu2O/Ti) sacrificial templates were prepared, and then a GRR was carried out with HAuCl4. The real-time SERS detection during GRR show that the optimum reaction time (ORT) is 300 ± 30 s. Furthermore, SERS performance testing was conducted on the optimized substrate, revealing that the detection limit for crystal violet can reach 1.96 × 10-11 M, confirming the feasibility of this method.

SIGNIFICANCE AND NOVELTY

By monitoring the in-situ SERS signal of probes during GRR will obtain an "optimal state" of the SERS substrate with optimal gap width and particle size. The SERS substrate preparation and optimization strategy proposed in this article not only provides a simple, efficient, and low-cost method to fabricate surface-clean noble NPs but also paves the way for the in-situ optimization of NPs size and gap width between NPs which could achieve wider applications of SERS.

SERS substrate based on COF@Ag for detecting amoxicillin in honey and lake water

This study presents the design of a Surface-enhanced Raman scattering (SERS) substrate, COF@Ag, for the sensitive detection of Amoxicillin (AMX) in lake water and honey. Furthermore, the study investigates the role of covalent organic frameworks (COFs) in SERS detection. The characterization results demonstrate the capability of COFs to efficiently enrich Ag nanoparticles (AgNPs), resulting in a more concentrated distribution of hotspots and an enhanced electromagnetic field on the substrate. By employing density functional theory (DFT) simulation, the frontier electronic orbitals of COFs and AMX were analyzed, and the chemical bonds and weak interactions in the system were examined using the Interaction Region Indicator (IRI) method to propose potential enhancement mechanisms. In aqueous solutions, the linear range is 1 μg/L-30 μg/L, with a limit of detection (LOD) 0.279 μg/L. In lake water, the linear range span from 100 μg/L to 500 μg/L, with a detection limit of 8.244 μg/L. For honey, the linear range extend from 20 ng/g to 100 ng/g, with a detection limit of 2.917 ng/g. This method holds key significance in facilitating the rapid detection of amoxicillin and advancing the application of COFs in SERS.

Quantitative and rapid detection of nanoplastics labeled by luminescent metal phenolic networks using surface-enhanced Raman scattering

The escalating prevalence of nanoplastics contamination in environmental ecosystems has emerged as a significant health hazard. Conventional analytical methods are suboptimal, hindered by their inefficiency in analyzing nanoplastics at low concentrations and their time-intensive processes. In this context, we have developed an innovative approach that employs luminescent metal-phenolic networks (L-MPNs) coupled with surface-enhanced Raman spectroscopy (SERS) to separate and label nanoplastics, enabling rapid, sensitive and quantitative detection. Our strategy utilizes L-MPNs composed of zirconium ions, tannic acid, and rhodamine B to uniformly label nanoplastics across a spectrum of sizes (50-500 nm) and types (e.g., polystyrene, polymethyl methacrylate, polylactic acid). Rhodamine B (RhB) functions as a Raman reporter within these L-MPNs-based SERS tags, providing the requisite sensitivity for trace measurement of nanoplastics. Moreover, the labeling with L-MPNs aids in the efficient separation of nanoplastics from liquid media. Utilizing a portable Raman instrument, our methodology offers cost-effective, swift, and field-deployable detection capabilities, with excellent sensitivity in nanoplastic analysis and a detection threshold as low as 0.1 μg/mL. Overall, this study proposes a highly promising strategy for the robust and sensitive analysis of a broad spectrum of particle analytes, underscored by the effective labeling performance of L-MPNs when coupled with SERS techniques.

SERS analysis, DFT, and solution effects regarding the structural and optical characteristics of folic acid biomolecule adsorbed on a Cu3 metal cluster

The optical characteristics of folic acid (ABP) and metal clusters of copper (Cu3) at various locations were investigated by means of density functional theory (DFT) computations. Mulliken charge analysis and molecular electrostatic potential (MEP) surface show how charge moves from Cu3 to ABP through the various groups. The peak in the UV-Vis spectra of ABP-Cu3 is caused by bonding and anti-bonding orbitals. In both vacuum and aqueous conditions, the polarizability values of ABP-Cu3 cluster are significantly higher than those of pure ABP, indicating a possible enhancement of the nonlinear optical (NLO) effect. Our research investigates the possibility of using ABP adsorbed metal clusters for NLO materials. Surface enhanced Raman scattering (SERS) in the ABP adsorbed metal clusters enhances the vibrational modes of ABP. Adsorption energies are found to be in the range -17.08 to -58.52 kcal/mol in vacuum and -53.34 to -93.44 kcal/mol in aqueous medium for the different configurations for ABP-Cu3. It indicates that metal clusters adsorbed by ABP are stable in the aqueous media. Experimental IR and UV-Vis of ABP is in agreement with theoretically predicted ones.

Construction of SERS output-signal aptasensor using MOF/noble metal nanoparticles based nanozyme for sensitive histamine detection

Herein, a signal output SERS aptasensor for Histamine (HA) detection is designed. MIL-100(Fe) was loaded with gold nanoparticles (AuNPs) to form composite nanozyme MIL-100(Fe)@AuNPs, which was used in the reaction system TMB/H2O2. Silver nanoparticles (AgNPs) were synthesized as "amplifier" for the SERS signal of ox TMB. After nucleic acid functionalization, the two parts were assembled to form the multifunctional substrate with both high catalytic and SERS efficiency. In the detection system, the specific binding effect of HA aptamer toward HA induced a decrease in the assembly of AgNPs on MIL-100(Fe)@AuNPs which caused a decrease in ox TMB SERS signals. The linear relation of HA ranged from 10-11 M to 5 × 10-3 M with LOD as low as 3.9 × 10-12 M. Recovery ratio in fermented soybean products (94.42-105.75 %) proved the real sample applicability. The fabricated SERS aptasensor will provide technical support for the safety during food processing and storage.

Self-assembled C-Ag hybrid nanoparticle on nanoporous GaN enabled ultra-high enhancement factor SERS sensor for sensitive thiram detection

Considering pesticide residues cause significant harm to public health and the environment, developing a simple, sensitive, and reliable approach to pesticide residue detection to address this issue is necessary. In this study, an ultrasensitive and reliable surface-enhanced Raman scattering (SERS) sensor was developed using cetylpyridinium chloride as a protecting and reducing agent for the in situ synthesis and self-assembly of C-Ag nanoparticles on nanoporous GaN for the quantitative detection of thiram. A systematic investigation of the performance of the SERS sensor revealed that the SERS sensor delivered a limit of detection (LOD) of 10-14 M and an enhancement factor of up to 1.80 × 1011 with reasonable uniformity and reproducibility, with the stability of the SERS sensor demonstrated via long-term storage for up to 22 weeks in air. The enhancement mechanism of the SERS sensor was verified using a finite-difference time-domain simulation. The SERS sensor successfully detected thiram in real samples with an LOD of 10-10 M. Hence, this study provides an effective platform for monitoring food safety and the environment.

Reliable quantitative detection of uric acid in urine by surface-enhanced Raman spectroscopy with endogenous internal standard

Abnormal levels of uric acid (UA) in urine serve as warning signs for gout and metabolic cardiovascular diseases, necessitating the monitoring of UA levels for early prevention. However, the current analytical methods employed suffer from limitations in terms of inadequate suitability for home-based applications and the requirement of non-invasive procedures. In this approach, creatinine, a metabolite with a constant excretion rate, was incorporated as an endogenous internal standard (e-IS) for calibration, presenting a rapid, pretreatment-free, and accurate strategy for quantitative determination of UA concentrations. By utilizing urine creatinine as an internal reference value to calibrate the signal fluctuation of surface-enhanced Raman spectroscopy (SERS) of UA, the quantitative accuracy can be significantly improved without the need for an external internal standard. Due to the influence of the medium, UA, which carries a negative charge, is selectively adsorbed by Au@Ag nanoparticles functionalized with hexadecyltrimethylammonium chloride (CTAC) in this system. Furthermore, a highly convenient detection method was developed, which eliminates the need for pre-processing and minimizes matrix interference by simple dilution. The method was applied to the urine detection of different volunteers, and the results were highly consistent with those obtained using the UA colorimetric kit (UACK). The detection time of SERS was only 30 s, which is 50 times faster than UACK. This quantitative strategy of using urinary creatinine as an internal standard to correct the SERS intensity of uric acid is also expected to be extended to the quantitative detection needs of other biomarkers in urine.

SERS-based detection of the antibiotic ceftriaxone in spiked fresh plasma and microdialysate matrix by using silver-functionalized silicon nanowire substrates

Therapeutic drug monitoring (TDM) is an important tool in precision medicine as it allows estimating pharmacodynamic and pharmacokinetic effects of drugs in clinical settings. An accurate, fast and real-time determination of the drug concentrations in patients ensures fast decision-making processes at the bedside to optimize the clinical treatment. Surface-enhanced Raman spectroscopy (SERS), which is based on the application of metallic nanostructured substrates to amplify the inherent weak Raman signal, is a promising technique in medical research due to its molecular specificity and trace sensitivity accompanied with short detection times. Therefore, we developed a SERS-based detection scheme using silicon nanowires decorated with silver nanoparticles, fabricated by means of top-down etching combined with chemical deposition, to detect the antibiotic ceftriaxone (CRO) in spiked fresh plasma and microdialysis samples. We successfully detected CRO in both matrices with an LOD of 94 μM in protein-depleted fresh plasma and 1.4 μM in microdialysate.

Magnetic-Plasmonic Nanocomposites as Versatile Substrates for Surface-enhanced Raman Scattering (SERS) Spectroscopy

Surface-enhanced Raman scattering (SERS) spectroscopy, a highly sensitive technique for detecting trace-level analytes, relies on plasmonic substrates. The choice of substrate, its morphology, and the excitation wavelength are crucial in SERS applications. To address advanced SERS requirements, the design and use of efficient nanocomposite substrates have become increasingly important. Notably, magnetic-plasmonic (MP) nanocomposites, which combine magnetic and plasmonic properties within a single particle system, stand out as promising nanoarchitectures with versatile applications in nanomedicine and SERS spectroscopy. In this review, we present an overview of MP nanocomposite fabrication methods, explore surface functionalization strategies, and evaluate their use in SERS. Our focus is on how different nanocomposite designs, magnetic and plasmonic properties, and surface modifications can significantly influence their SERS-related characteristics, thereby affecting their performance in specific applications such as separation, environmental monitoring, and biological applications. Reviewing recent studies highlights the multifaceted nature of these materials, which have great potential to transform SERS applications across a range of fields, from medical diagnostics to environmental monitoring. Finally, we discuss the prospects of MP nanocomposites, anticipating favorable developments that will make substantial contributions to various scientific and technological areas.

Artificial Intelligence-driven Platform: Unveiling Critical Hepatic Molecular Alterations in Hepatocellular Carcinoma Development

Since most Hepatocellular Carcinoma (HCC) typically arises as a consequence of long-term liver damage, the hepatic molecular characteristics are closely related to the occurrence of HCC. Gaining comprehensive information about the location, morphology, and hepatic molecular alterations related to HCC is essential for accurate diagnosis. However, there is a dearth of technological advancements capable of concurrently providing precise HCC diagnosis and discerning the accompanying hepatic molecular alterations. In this study, We have developed an integrated information system for the pathological-level diagnosis of HCC and the revelation of critical molecular alterations in the liver. This system utilizes computed tomography/Surface-enhanced Raman scattering combined with an artificial intelligence strategy to establish connections between the occurrence of HCC and alterations in hepatic biomolecules. Employing artificial intelligence techniques, the SERS spectra from both healthy and HCC groups were successfully classified into two distinct categories with a remarkable accuracy rate of 91.38%. Based on molecular profiling, we have identified that the nucleotide-to-lipid signal ratio holds significant potential as a reliable indicator for the occurrence of HCC, thereby serving as a promising tool for prevention and therapeutic surveillance. This article is protected by copyright. All rights reserved.

Core-Shell Gold Nanoparticles@Pd-Loaded Covalent Organic Framework for In Situ Surface-Enhanced Raman Spectroscopy Monitoring of Catalytic Reactions

A core-shell nanostructure of gold nanoparticles@covalent organic framework (COF) loaded with palladium nanoparticles (AuNPs@COF-PdNPs) was designed for the rapid monitoring of catalytic reactions with surface-enhanced Raman spectroscopy (SERS). The nanostructure was prepared by coating the COF layer on AuNPs and then in situ synthesizing PdNPs within the COF shell. With the respective SERS activity and catalytic performance of the AuNP core and COF-PdNPs shell, the nanostructure can be directly used in the SERS study of the catalytic reaction processes. It was shown that the confinement effect of COF resulted in the high dispersity of PdNPs and outstanding catalytic activity of AuNPs@COF-PdNPs, thus improving the reaction rate constant of the AuNPs@COF-PdNPs-catalyzed hydrogenation reduction by 10 times higher than that obtained with Au/Pd NPs. In addition, the COF layer can serve as a protective shell to make AuNPs@COF-PdNPs possess excellent reusability. Moreover, the loading of PdNPs within the COF layer was found to be in favor of avoiding intermediate products to achieve a high total conversion rate. AuNPs@COF-PdNPs also showed great catalytic activities toward the Suzuki-Miyaura coupling reaction. Taken together, the proposed core-shell nanostructure has great potential in monitoring and exploring catalytic processes and interfacial reactions.

Differentiating Structurally Similar Fentanyl Analogs by Comparing Density Functional Theory (DFT) Calculations and Surface-Enhanced Raman Spectroscopy (SERS) Results

Fentanyl and fentanyl analogs are the main cause of recent overdose deaths in the United States. The presence of fentanyl analogs in illicit drugs makes it difficult to estimate their potencies. This makes the detection and differentiation of fentanyl analogs critically significant. Surface-enhanced Raman spectroscopy (SERS) can differentiate structurally similar fentanyl analogs by yielding spectroscopic fingerprints for the detected molecules. In previous years, five fentanyl analogs, carfentanil, furanyl fentanyl, acetyl fentanyl, 4-fluoroisobutyryl fentanyl (4-FIBF), and cyclopropyl fentanyl (CPrF), gained popularity and were found in 76.4% of the fentanyl analogs trafficked. In this study, we focused on 4-FIBF, CPrF, and structurally similar fentanyl analogs. We developed methods to differentiate these fentanyl analogs using theoretical and experimental methods. To do this, a set of fentanyl analogs were examined using density functional theory (DFT) calculations. The DFT results obtained in this project permitted the assignment of spectral bands. These results were then compared with normal Raman and SERS techniques. Structurally similar fentanyl analogs show important differences in their spectra, and they have been visually differentiated from each other both theoretically and experimentally. Additional results using principal component analysis and soft independent modeling of class analogy show they can be distinguished using this technique. The limit of detection values for FIBF and CPrF were determined to be 0.35 ng/mL and 4.4 ng/mL, respectively, using SERS. Experimental results obtained in this project can be readily implemented in field applications and smaller laboratories, where inexpensive portable Raman spectrometers are often present and used in drug analysis.

A Scaffold-Assisted 3D Cancer Cell Model for Surface-Enhanced Raman Scattering-Based Real-Time Sensing and Imaging

Despite recent advances in the development of scaffold-based three-dimensional (3D) cell models, challenges persist in imaging and monitoring cell behavior within these complex structures due to their heterogeneous cell distribution and geometries. Incorporating sensors into 3D scaffolds provides a potential solution for real-time, in situ sensing and imaging of biological processes such as cell growth and disease development. We introduce a 3D printed hydrogel-based scaffold capable of supporting both surface-enhanced Raman scattering (SERS) biosensing and imaging of 3D breast cancer cell models. The scaffold incorporates plasmonic nanoparticles and SERS tags, for sensing and imaging, respectively. We demonstrate the scaffold's adaptability and modularity in supporting breast cancer spheroids, thereby enabling spatial and temporal monitoring of tumor evolution.

Potential of a deep eutectic solvent in silver nanoparticle fabrication for antibiotic residue detection

Deep eutectic solvents (DESs) have recently emerged as an alternative solvent for nanoparticle synthesis. There have been numerous advancements in the fabrication of silver nanoparticles (Ag NPs), but the potential of DESs in Ag NP synthesis was neither considered nor studied carefully. In this study, we present a novel strategy to fabricate Ag NPs in a DES (Ag NPs-DES). The DES composed of ᴅ-glucose, urea, and glycerol does not contain any anions to precipitate with Ag+ cations. Our Ag NPs-DES sample is used in a surface-enhanced Raman scattering (SERS) sensor. The two analytes for SERS quantitation are nitrofurantoin (NFT) and sulfadiazine (SDZ) whose residues can be traced down to 10-8 M. The highest enhancement factors (EFs) are competitive at 6.29 × 107 and 1.69 × 107 for NFT and SDZ, respectively. Besides, the linearity coefficients are extremely close to 1 in the range of 10-8 to 10-3 M of concentration, and the SERS substrate shows remarkable uniformity along with great selectivity. This powerful SERS performance indicates that DESs have tremendous potential in the synthesis of nanomaterials for biosensor substrate construction.

Highly sensitive detection of tryptophan based on Schiff base reaction and surface-enhanced Raman spectroscopy

In this study, a simple, rapid and sensitive method combining surface-enhanced Raman spectroscopy and Schiff base reaction was developed for the detection of tryptophan. This method does not require product separation to obtain a significant Raman signal of the derivatized product, and the derivatization reaction can be controlled by experimental parameters such as reaction temperature, time, concentration of derivatization reagent and concentration of sodium nitrite. The characteristic peak of the derivative of tryptophan (1620 cm-1) was selected for quantitative analysis, and the intensity of the characteristic Raman spectrum peak showed a linear relationship with the concentration of tryptophan (10-8-10-4 mol/L) in the range of with a correlation coefficient R2 of 0.9922. This assay combines surface-enhanced Raman spectroscopy and Schiff base reaction, which is characterized by high sensitivity and easy operation, and has good application prospects in the detection of tryptophan in food.

Vapor phase detection of explosives by surface enhanced Raman scattering under ambient conditions with metal nanogap structures

Non-invasive and passive detection of explosives in the vapor phase is advantageous for military, counter-terrorism, and homeland security applications. Detection of explosives using SERS has been an active research topic. However, the vapor pressures of most explosives are low at room temperature, and consequently, the vapor phase detection by SERS is highly challenging without intentionally heating explosive powder to increase the vapor pressure. In this work, we report the rapid and sensitive detection of 2,4,6-trinitrotoluene (TNT) and 2,4-dinitrotoluene (2,4-DNT) in the vapor phase, using a gold nanogap (AuNG) SERS substrate. The AuNG SERS substrate was fabricated with electron beam evaporation, rapid thermal annealing, and wet etching. SERS measurements were carried out with an incident power as low as 0.56 mW at 785 nm. To prevent the condensation effect, the TNT and 2,4-DNT powders inside the cuvette were taken out before inserting the nanogap substrate. Our SERS results demonstrate the feasibility of the non-invasive detection of vapor phase explosives under ambient conditions.

Interactions of deprotonated phenylalanine with gold Clusters: Theoretical study with prospects for amino acid detection

Nanomaterials are widely used nowadays in industry and medicine. The specific properties of gold nanoclusters (Au NCs) are chemical stability, low cytotoxicity, low photobleaching, high sensitivity to the molecular environment. This set of properties allows to use Au NCs as nanosensors in bioimaging and diagnostics. We have investigated gold cluster complexes with proteinogenic amino acid phenylalanine (Phe). Detection of phenylalanine is essential for diagnostics of phenylketonuria, vitiligo, sclerosis, cancer, tuberculosis, etc. We have studied the complexes of Phe with Aunq clusters with atomic number equal 1-6, 8, 20 and a charge equal 0-2. We have established that the clusters Au40, Au21+ and Au32+ form the most stable complexes with Phe among NCs with charge 0, +1 and + 2, respectively. Intracomplex interactions have been studied using Atoms-In-Molecules (AIM) theory and Natural Bond Orbital (NBO) analysis. It has been shown that metal-ligand intracomplex interactions are partially covalent and partially electrostatic. Also, we have simulated the UV-vis absorption and Raman spectra of the Phe-Au NCs. We have established that the clusters possess prospective features if being used for colorimetric and Raman detection of Phe. Au20 cluster is remarkable for its six-times enhancement of the Raman signal. Moreover, our study provides insights into metal-ligand interactions for clusters synthesized inside a polypeptide globula. Hence, to the best of our knowledge this is a first attempt to perform a detailed analysis of Phe interactions with gold using quantum chemical calculations.

Determination of latent tuberculosis infection from plasma samples via label-free SERS sensors and machine learning

Effective diagnostic tools for screening of latent tuberculosis infection (LTBI) are lacking. We aim to investigate the performance of LTBI diagnostic approaches using label-free surface-enhanced Raman spectroscopy (SERS). We used 1000 plasma samples from Northeast Thailand. Fifty percent of the samples had tested positive in the interferon-gamma release assay (IGRA) and 50 % negative. The SERS investigations were performed on individually prepared protein specimens using the Raman-mapping technique over a 7 × 7 grid area under measurement conditions that took under 10 min to complete. The machine-learning analysis approaches were optimized for the best diagnostic performance. We found that the SERS sensors provide 81 % accuracy according to train-test split analysis and 75 % for LOOCV analysis from all samples, regardless of the batch-to-batch variation of the sample sets and SERS chip. The accuracy increased to 93 % when the logistic regression model was used to analyze the last three batches of samples, following optimization of the sample collection, SERS chips, and database. We demonstrated that SERS analysis with machine learning is a potential diagnostic tool for LTBI screening.

A double defects-dominated flexible TiO2 matrix for in-situ SERS sensing of antibiotic residues in aquatic ecosystem (fish & fishpond water) and their on-site degradation in flowing water

High-performance flexible semiconductor material can be used as an excellent multifunctional matrix for in-situ ultrasensitive surface-enhanced Raman scattering (SERS) detection and synchronous photocatalytic degradation of antibiotic residues in aquatic ecosystem. Here, a calcium-doped TiO2 flexible matrix with double defects (surface oxygen vacancy defect and Ti3+ energy level defect) was developed by its "in-situ one-step" hydrothermal synthesis on cotton fabric for the above purposes. Due to the joint contribution of double defects, a multi-channel charge transfer mode and a high-efficiency carrier separation are achieved, which endows flexible cotton fabric/Ca-doped TiO2 (Cot/Ca-TiO2) substrate with the greatly boosted SERS effect for in-situ detection of antibiotic residues on fish body surface and in fishpond water by a simple wiping or dipping sampling method, even for simultaneous identification of multi-component residues. The detection limits of three antibiotic residues (enrofloxacin, ciprofloxacin and enoxacin) are as low as 10-9 M, which are far lower than the EU standard. More meaningfully, the flexible Cot/Ca-TiO2 can be used as a multifunctional filter-membrane type photocatalyst for efficient on-site degradation of antibiotic residues in flowing fishpond water by a multi-grade photocatalysis means. Moreover, the flexible matrix exhibits good recyclability in both actual detection and photocatalysis.

A stable and sensitive 2D SERS sensor for bioanalytical applications

In this study, we describe a 2D-SERS sensor obtained by deposition of spherical gold nanoparticles (AuNPs) onto a suitably functionalized metal surface. Morphological analysis of the SERS surface by SEM and AFM demonstrated a uniform and stable distribution of the active nanoparticles. Following p-mercaptoaniline (pMA) functionalization, the sensor was characterized by co-localized Raman measurements, demonstrating a significant enhancement in Raman signals with homogeneous SERS activity across the entire sampled area. The as-prepared SERS sensor was demonstrated to be suitable for Therapeutic Drug Monitoring (TDM) of 6-mercaptopurine (6-MP), exhibiting a linear correlation between analyte concentration and SERS intensity in the range 5 - 20 μM. This work highlights the potential of 2D-SERS sensors for hypersensitive and accurate analytical measurements, particularly in the biomedical field.

Design superhydrophobic no-noble metal substrates for highly sensitive and signal stable SERS sensing

Surface-enhanced Raman spectroscopy (SERS) is an analytical technique with a broad range of potential applications in fields such as biomedicine, electrochemistry, and hazardous chemicals. However, it is challenging to develop SERS substrates that are both good sensitive and signal stable. Here we designed a superhydrophobic Nd doped MoS2 uniformly assembled on the activated carbon fiber cloth (CFC) to avoid the coffee ring effect and enrich the analyte, improving the enhancement factor (EF) to 3.9 × 109 and pesticide endosulfan (<10-10) analyte detection. We demonstrate our strategy by density-functional theory (DFT) calculations confirming that both adsorption energy and density of states are enhanced after doping Nd leading to SERS enhancement. Beside DFT calculations, our experiments also provide an effective means to demonstrate that the high SERS sensitivity is based on multiple charge transfer processes combined with the activated carbon cloth. Our results address the limitations of low sensitivity and limit of detection (LOD) of semiconductor SERS substrates for trace analysis and are a step towards practical applications.

Functionalized Single Crystal Perovskite Materials for SERS and Their Potential Detection Applications

Recent advances in detection and diagnostic tools have improved understanding and identification of plant physiological and biochemical processes. Effective and safe Surface Enhanced Raman Spectroscopy (SERS) can find objects quickly and accurately. Raman enhancement amplifies the signal by 1014-1015 to accurately quantify plant metabolites at the molecular level. This paper shows how to use functionalized perovskite substrates for SERS. These perovskite substrates have lots of surface area, intense Raman scattering, and high sensitivity and specificity. These properties eliminate sample matrix component interference. This study identified research gaps on perovskite substrates' effectiveness, precision, and efficiency in biological metabolite detection compared to conventional substrates. This article details the synthesis and use of functionalized perovskites for plant metabolites measurement. It analyzes their pros and cons in this context. The manuscript analyzes perovskite-based SERS substrates, including single-crystalline perovskites with enhanced optoelectronic properties. This manuscript aims to identify this study gap by comprehensively reviewing the literature and using it to investigate plant metabolite detection in future studies.

Plasmonic Annular Nanotrenches with 1 nm Nanogaps for Detection of SARS-CoV-2 Using SERS-Based Immunoassay

This study represents the synthesis of a novel class of nanoparticles denoted as annular Au nanotrenches (AANTs). AANTs are engineered to possess embedded, narrow circular nanogaps with dimensions of approximately 1 nm, facilitating near-field focusing for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via a surface-enhanced Raman scattering (SERS)-based immunoassay. Notably, AANTs exhibited an exceedingly low limit of detection (LOD) of 1 fg/mL for SARS-CoV-2 spike glycoproteins, surpassing the commercially available enzyme-linked immunosorbent assay (ELISA) by 6 orders of magnitude (1 ng/mL from ELISA). To assess the real-world applicability, a study was conducted on 50 clinical samples using an SERS-based immunoassay with AANTs. The results revealed a sensitivity of 96% and a selectivity of 100%, demonstrating the significantly enhanced sensing capabilities of the proposed approach in comparison to ELISA and commercial lateral flow assay kits.

NIR-Active Gold Dogbone Nanorattles Impregnated in Cationic Dextrin Nanoparticles for Cancer Nanotheranostics

Theranostic systems, which integrate therapy and diagnosis into a single platform, have gained significant attention as a promising approach for noninvasive cancer treatment. The field of image-guided therapy has revolutionized real-time tumor detection, and within this domain, plasmonic nanostructures have garnered significant attention. These structures possess unique localized surface plasmon resonance (LSPR), allowing for enhanced absorption in the near-infrared (NIR) range. By leveraging the heat generated from plasmonic nanoparticles upon NIR irradiation, target cancer cells can be effectively eradicated. This study introduces a plasmonic gold dogbone-nanorattle (AuDB NRT) structure that exhibits broad absorption in the NIR region and demonstrates a photothermal conversion efficiency of 35.29%. When exposed to an NIR laser, the AuDB NRTs generate heat, achieving a maximum temperature rise of 38 °C at a concentration of 200 μg/mL and a laser power density of 3 W/cm2. Additionally, the AuDB NRTs possess intrinsic electromagnetic hotspots that amplify the signal of a Raman reporter molecule, making them an excellent probe for surface-enhanced Raman scattering-based bioimaging of cancer cells. To improve the biocompatibility of the nanorattles, the AuDB NRTs were conjugated with mPEG-thiol and successfully encapsulated into cationic dextrin nanoparticles (CD NPs). Biocompatibility tests were performed on HEK 293 A and MCF-7 cell lines, revealing high cell viability when exposed to AuDB NRT-CD NPs. Remarkably, even at a low laser power density of 1 W/cm2, the application of the NIR laser resulted in a remarkable 80% cell death in cells treated with a nanocomposite concentration of 100 μg/mL. Further investigation elucidated that the cell death induced by photothermal heat followed an apoptotic mechanism. Overall, our findings highlight the significant potential of the prepared nanocomposite for cancer theranostics, combining effective photothermal therapy along with the ability to image cancer cells.

A review of clinical use of surface-enhanced Raman scattering-based biosensing for glioma

Glioma is the most common malignant tumor of the nervous system in recent centuries, and the incidence rate of glioma is increasing year by year. Its invasive growth and malignant biological behaviors make it one of the most challenging malignant tumors. Maximizing the resection range (EOR) while minimizing the impact on normal brain tissue is crucial for patient prognosis. Changes in metabolites produced by tumor cells and their microenvironments might be important indicators. As a powerful spectroscopic technique, surface-enhanced Raman scattering (SERS) has many advantages, including ultra-high sensitivity, high specificity, and non-invasive features, which allow SERS technology to be widely applied in biomedicine, especially in the differential diagnosis of malignant tumor tissues. This review first introduced the clinical use of responsive SERS probes. Next, the sensing mechanisms of microenvironment-responsive SERS probes were summarized. Finally, the biomedical applications of these responsive SERS probes were listed in four sections, detecting tumor boundaries due to the changes of pH-responsive SERS probes, SERS probes to guide tumor resection, SERS for liquid biopsy to achieve early diagnosis of tumors, and the application of free-label SERS technology to detect fresh glioma specimens. Finally, the challenges and prospects of responsive SERS detections were summarized for clinical use.

High-performance, large-area flexible SERS substrates prepared by reactive ion etching for molecular detection

In the realm of molecular detection, the surface-enhanced Raman scattering (SERS) technique has garnered increasing attention due to its rapid detection, high sensitivity, and non-destructive characteristics. However, conventional rigid SERS substrates are either costly to fabricate and challenging to prepare over a large area, or they exhibit poor uniformity and repeatability, making them unsuitable for inspecting curved object surfaces. In this work, we present a flexible SERS substrate with high sensitivity as well as good uniformity and repeatability. First, the flexible polydimethylsiloxane (PDMS) substrate is manually formulated and cured. SiO2/Ag layer on the substrate can be obtained in a single process by using ion beam sputtering. Then, reactive ion etching is used to etch the upper SiO2layer of the film, which directly leads to the desired densely packed nanostructure. Finally, a layer of precious metal is deposited on the densely packed nanostructure by thermal evaporation. In our proposed system, the densely packed nanostructure obtained by etching the SiO2layer directly determines the SERS ability of the substrate. The bottom layer of silver mirror can reflect the penetrative incident light, the spacer layer of SiO2and the top layer of silver thin film can further localize the light in the system, which can realize the excellent absorption of Raman laser light, thus enhancing SERS ability. In the tests, the prepared substrates show excellent SERS performance in detecting crystalline violet with a detection limit of 10-11M. The development of this SERS substrate is anticipated to offer a highly effective and convenient method for molecular substance detection.

Synovial fluid research based on SERS and SERRS for enhanced detection of biomarkers in staged osteoarthritis

Surface-enhanced (resonance) Raman scattering (SER(R)S) can extremely enhance Raman intensity of samples, which is helpful for detecting synovial fluid (SF) that does not show Raman activity under normal conditions. In this study, SER(R)S spectra of SF from three different osteoarthritis (OA) stages were collected and analyzed for OA progress, finding that the content of collagen increased throughout the disease, while non-collagen proteins and polysaccharides decreased sharply at advanced OA stage accompanied by the increase of phospholipid. The spectral features and differences were enhanced by salting-out and centrifugation. Much more information on biomolecules at different OA stages was disclosed by using SERRS for the first time, these main trace components (β-carotene, collagen, hyaluronic acid, nucleotide, and phospholipid) can be used as potential biomarkers. It indicates that SERRS has a more comprehensive ability to assist SERS in seeking micro(trace) biomolecules as biomarkers and facilitating accurate and efficient diagnosis and mechanism research of OA.

CRISPR/Cas9-mediated SERS/colorimetric dual-mode lateral flow platform combined with smartphone for rapid and sensitive detection of Staphylococcus aureus

Pathogenic bacteria infections pose a significant threat to global public health, making the development of rapid and reliable detection methods urgent. Here, we developed a surface-enhanced Raman scattering (SERS) and colorimetric dual-mode platform, termed smartphone-integrated CRISPR/Cas9-mediated lateral flow strip (SCC-LFS), and applied it to the ultrasensitive detection of Staphylococcus aureus (S. aureus). Strategically, functionalized silver-coated gold nanostar (AuNS@Ag) was prepared and used as the labeling material for LFS assay. In the presence of S. aureus, target gene-induced amplicons can be accurately recognized and unwound by the user-defined CRISPR/Cas9 system, forming intermediate bridges that bind many AuNS@Ag to the test line (T-line) of the strip. As a result, the T-line was colored and a recognizable SERS signal was obtained using a smartphone-integrated portable Raman spectrometer. This design not only maintains the simplicity of visual readout, but also integrates the quantitative capability of SERS, enabling the user to flexibly select the assay mode as needed. With this method, S. aureus down to 1 CFU/mL can be detected by both colorimetric and SERS modes, which is better than most existing methods. By incorporating a rapid extraction procedure, the entire assay can be completed in 45 min. The robustness and practicality of the method were further demonstrated by various real samples, indicating its considerable potential toward reliable screening of S. aureus.

A review of SERS coupled microfluidic platforms: From configurations to applications

Microfluidic systems have attracted considerable attention due to their low reagent consumption, short analysis time, and ease of integration in comparison to conventional methods, but still suffer from shortcomings in sensitivity and selectivity. Surface enhanced Raman scattering (SERS) offers several advantages in the detection of compounds, including label-free detection at the single-molecule level, and the narrow Raman peak width for multiplexing. Combining microfluidics with SERS is a viable way to improve their detection sensitivity. Researchers have recently developed several SERS coupled microfluidic platforms with substantial potential for biomolecular detection, cellular and bacterial analysis, and hazardous substance detection. We review the current development of SERS coupled microfluidic platforms, illustrate their detection principles and construction, and summarize the latest applications in biology, environmental protection and food safety. In addition, we innovatively summarize the current status of SERS coupled multi-mode microfluidic platforms with other detection technologies. Finally, we discuss the challenges and countermeasures during the development of SERS coupled microfluidic platforms, as well as predict the future development trend of SERS coupled microfluidic platforms.

Facile synthesis of gold nanostars for the duplex detection of pesticide residues in grapes using SERS

In recent years, concerns have been raised regarding the contamination of grapes with pesticide residues. As consumer demand for safer food products grows, regular monitoring of pesticide residues in food has become essential. This study sought to develop a rapid and sensitive technique for detecting two specific pesticides (phosmet and paraquat) present on the grape surface using the surface-enhanced Raman spectroscopy (SERS) method. Gold nanostars (AuNS) particles were synthesized, featuring spiky tips that act as hot spots for localized surface plasmon resonance, thereby enhancing Raman signals. Additionally, the roughened surface of AuNS increases the surface area, resulting in improved interactions between the substrate and analyte molecules. Prominent Raman peaks of mixed contaminants were acquired and used to characterize and quantify the pesticides. It was observed that the SERS intensity of the Raman peaks changed in proportion to the concentration ratio of phosmet and paraquat. Moreover, AuNS exhibited superior SERS enhancement compared to gold nanoparticles. The results demonstrate that the lowest detectable concentration for both pesticides on grape surfaces is 0.5 mg/kg. These findings suggest that SERS coupled with AuNS constitutes a practical and promising approach for detecting and quantifying trace contaminants in food. PRACTICAL APPLICATION: This research established a novel surface-enhanced Raman spectroscopy (SERS) method coupled with a simplified extraction protocol and gold nanostar substrates to detect trace levels of pesticides in fresh produce. The detection limits meet the maximum residue limits set by the EPA. This substrate has great potential for rapid measurements of chemical contaminants in foods.

A colorimetric and SERS dual-mode aptasensor for the detection of Shiga toxin type II based on Mn/Fe-MIL(53)@AuNSs

Shiga toxin type II (Stx2), the major virulence component of enterohemorrhagic Escherichia coli, is strongly associated with the life-threatening hemolytic uremic syndrome thus posing a substantial risk to food safety and human health. In this work, a dual-mode aptasensor with colorimetric and surface-enhanced Raman scattering was developed for Stx2 specific detection based on noble metal nanoparticles and Raman reporter loaded metal-organic framework (Mn/Fe-MIL(53)@AuNSs-MBA). The Mn/Fe-MIL(53)@AuNSs could catalyze the H2O2-mediated oxidation of 3,3',5,5'-tetramethylbenzidine (TMB), thereby enabling visual detection. Meanwhile, the SERS signal from MBA can be enhanced by the decorated AuNSs. Under optimal conditions, a linear range of 0.05-500 ng/mL with limit of detection (LOD) of 26 pg/mL was achieved in colorimetric mode and a linear range of 5-1000 ng/mL with LOD of 0.82 ng/mL in SERS mode, in which the dual-mode results complement each other, widening the linear range, increasing the accuracy and reliability of the detection. The method was further applied to the detection of Stx2 in milk with average recovery of 101.1 %, demonstrating its superior potential for bacterial toxin monitoring.

Machine learning-based exosome profiling of multi-receptor SERS sensors for differentiating adenocarcinoma in situ from early-stage invasive adenocarcinoma

Exosomes, extracellular vesicles released by cells, hold potential as diagnostic markers for the early detection of lung cancer. Despite their clinical promise, current technologies lack rapid and effective means to discriminate between exosomes derived from adenocarcinoma in situ (AIS) and early-stage invasive adenocarcinoma (IAC). This challenge arises from the intrinsic structural heterogeneity of exosomes, necessitating the development of advanced methodologies for precise differentiation. Here, we demonstrate a novel approach for plasma exosome detection utilizing multi-receptor surface-enhanced Raman spectroscopy (SERS) technology to differentiate between AIS and early-stage IAC. To accomplish this, we synthesized a stable and uniform two-dimensional SERS substrate (BC/Au NPs film) by fabricating gold nanoparticles onto bacterial cellulose. We then enhanced its capabilities by introducing multi-receptor SERS functionality via modifying the substrate with both low-specificity and physicochemical-selective molecules. Furthermore, by strategically combining all capturer-exosome SERS spectra, comprehensive "combined-SERS spectra" are reconstructed to enhance spectral variations of the exosome. Combining these features with partial least squares regression-discriminant analysis (PLS-DA) modeling significantly improved discriminatory accuracy, achieving 90% sensitivity and 95% specificity in distinguishing AIS from early-stage IAC. Our developed SERS sensor provides an effective method for early detection of lung cancer, thereby paving a new way for innovative advancements in diagnosing lung cancer.

Colourimetric and SERS dual-mode aptasensor using Au@Ag and magnetic nanoparticles for the detection of Campylobacter jejuni

A dual-mode aptasensor has been developed for the effective detection of Campylobacter jejuni (C. jejuni), a major cause of gastrointestinal disease worldwide. The aptasensor utilizes nanoparticles, specifically a core-shell structure consisting of gold and silver (Au@Ag NPs), along with magnetic nanoparticles (MNPs). When Campylobacter jejuni is introduced, "Au@Ag NPs-Aptamer-Campylobacter jejuni-Aptamer-MNPs" sandwich complexes are formed due to the high affinity of the aptamer for the bacterial surface membrane proteins. The dual-mode aptasensor can magnetically enrich the sample in just 15 min, and the presence of Campylobacter jejuni is determined by observing a color change. Additionally, the concentration of Campylobacter jejuni can be quantified using surface-enhanced Raman spectroscopy (SERS) and standard curves. This results in a wider linear range (1.8 × 101-108 CFU/mL) under optimal conditions, a lower limit of detection (6 CFU/mL), and a higher selectivity for the detection of bacteria compared to previously reported sensors. Compared with traditional microbial culture counting methods, the dual-mode aptasensor does not require Raman reporters. The physical action of magnetic enrichment, along with the application of Au@Ag NPs, improves the accuracy of the dual-mode aptasensor, offering the advantages of convenience and high sensitivity. Moreover, by utilizing different types of aptamers, this aptasensor can be modified to detect a wider range of harmful pathogens in various environments.

Quantifying the effect of non-ionic surfactant alkylphenol ethoxylates on the persistence of thiabendazole on fresh produce surface

BACKGROUND

Understanding the role of adjuvants in pesticide persistence is crucial to develop effective pesticide formulations and manage pesticide residues in fresh produce. This study investigated the impact of a commercial non-ionic surfactant product containing alkylphenol ethoxylates (APEOs) on the persistence of thiabendazole on apple and spinach surfaces against the 30 kg m-3 baking soda (sodium bicarbonate, NaHCO3 ) soaking, which was used to remove the active ingredient (AI) in the cuticular wax layer of fresh produce through alkaline hydrolysis. Surface-enhanced Raman scattering (SERS) mapping method was used to quantify the residue levels on fresh produce surfaces at different experimental scenarios. Four standard curves were established to quantify surface thiabendazole in the absence and presence of APEOs, on apple and spinach leaf surfaces, respectively.

RESULTS

Overall, the result showed that APEOs enhanced the persistence of thiabendazole over time. After 3 days of exposure, APEOs increased thiabendazole surface residue against NaHCO3 hydrolysis on apple and spinach surfaces by 5.39% and 10.47%, respectively.

CONCLUSION

The study suggests that APEOs led to more pesticide residues on fresh produce and greater difficulty in washing them off from the surfaces using baking soda, posing food safety concerns. © 2023 Society of Chemical Industry.

Crystallinity as a factor of SERS stability of silver nanoparticles formed by Ar+ irradiation

The plasmonic sensors based on silver nanoparticles are limited in application due to their relatively fast degradation in the ambient atmosphere. The technology of ion-beam modification for the creation of monocrystalline silver nanoparticles (NPs) with stable plasmonic properties will expand the application of silver nanostructures. In the present study, highly-stable monocrystalline NPs were formed on the basis of a thin silver film by low-energy ion irradiation. Combined with lithography, this technique allows the creation of nanoparticle ensembles in variant forms. The characterization of the nanoparticles formed by ion-beam modification showed long-term outstanding for Ag nanoparticles stability of their plasmonic properties due to their monocrystalline structure. According to optical spectroscopy data, the reliable plasmonic properties in the ambient atmosphere are preserved for up to 39 days. The mapping of crystal violet dye via surface-enhanced Raman spectroscopy (SERS) revealed a strong amplification factor sustaining at least thrice as long as the one of similarly sized polycrystalline silver NPs formed by annealing. The plasmonic properties sustain more than a month of storage in the ambient atmosphere. Thus, ion-beam modification of silver film makes it possible to fabricate NPs with stable plasmonic properties and form clusters of NPs for sensor technology and SERS applications.

Studying the Effects and Competitive Mechanisms of YOYO-1 on the Binding Characteristics of DOX and DNA Molecules Based on Surface-Enhanced Raman Spectroscopy and Molecular Docking Techniques

Revealing the interaction mechanisms between anticancer drugs and target DNA molecules at the single-molecule level is a hot research topic in the interdisciplinary fields of biophysical chemistry and pharmaceutical engineering. When fluorescence imaging technology is employed to carry out this kind of research, a knotty problem due to fluorescent dye molecules and drug molecules acting on a DNA molecule simultaneously is encountered. In this paper, based on self-made novel solid active substrates NpAA/(ZnO-ZnCl2)/AuNPs, we use a surface-enhanced Raman spectroscopy method, inverted fluorescence microscope technology, and a molecular docking method to investigate the action of the fluorescent dye YOYO-1 and the drug DOX on calf thymus DNA (ctDNA) molecules and the influencing effects and competitive relationships of YOYO-1 on the binding properties of the ctDNA-DOX complex. The interaction sites and modes of action between the YOYO-1 and the ctDNA-DOX complex are systematically examined, and the DOX with the ctDNA-YOYO-1 are compared, and the impact of YOYO-1 on the stability of the ctDNA-DOX complex and the competitive mechanism between DOX and YOYO-1 acting with DNA molecules are elucidated. This study has helpful experimental guidance and a theoretical foundation to expound the mechanism of interaction between drugs and biomolecules at the single-molecule level.

Gold and Silver Nanoparticles as Biosensors: Characterization of Surface and Changes in the Adsorption of Leucine Dipeptide under the Influence of Substituent Changes

Early detection of diseases can increase the chances of successful treatment and survival. Therefore, it is necessary to develop a method for detecting or sensing biomolecules that cause trouble in living organisms. Disease sensors should possess specific properties, such as selectivity, reproducibility, stability, sensitivity, and morphology, for their routine application in medical diagnosis and treatment. This work focuses on biosensors in the form of surface-functionalized gold (AuNPs) and silver nanoparticles (AgNPs) prepared using a less-time-consuming, inexpensive, and efficient synthesis route. This allows for the production of highly pure and stable (non-aggregating without stabilizers) nanoparticles with a well-defined spherical shape, a desired diameter, and a monodisperse distribution in an aqueous environment, as confirmed by transmission electron microscopy with energy-dispersive X-ray spectroscopy (TEM-EDS), X-ray diffraction (XRD), photoelectron spectroscopy (XPS), ultraviolet-visible (UV-VIS) spectroscopy, and dynamic light scattering (DLS). Thus, these nanoparticles can be used routinely as biomarker sensors and drug-delivery platforms for precision medicine treatment. The NPs' surface was coated with phosphonate dipeptides of L-leucine (Leu; l-Leu-C(R1)(R2)PO3H2), and their adsorption was monitored using SERS. Reproducible spectra were analyzed to determine the orientation of the dipeptides (coating layers) on the nanoparticles' surface. The appropriate R2 side chain of the dipeptide can be selected to control the arrangement of these dipeptides. This allows for the proper formation of a layer covering the nanoparticles while also simultaneously interacting with the surrounding biological environment, such as cells, tissues, and biological fluids.

Fabrication and Application of Ag@SiO2/Au Core-Shell SERS Composite in Detecting Cu2+ in Water Environment

A sensitive and simple method for detecting Cu2+ in the water source was proposed by using surface-enhanced Raman scattering spectroscopy (SERS) based on the Ag@SiO2/Au core-shell composite. The Ag@SiO2 SERS tag was synthesized by a simple approach, in which Ag nanoparticles were first embedded with Raman reporter PATP and next coated with a SiO2 shell. The Ag@SiO2 nanoparticles had strong stability even in a high-concentration salty solution, and there were no changes to their properties and appearance within one month. The Ag@SiO2/Au composite was fabricated through a controllable self-assemble process. L-cysteine was decorated on the surface of a functionalized Ag@SiO2/Au composite, as the amino and carboxyl groups of it can form coordinate covalent bond with Cu2+, which shows that the Ag@SiO2/Au composite labelled with L-cysteine has excellent performance for the detection of Cu2+ in aqueous media. In this study, the SERS detection of Cu2+ was carried out using Ag@SiO2 nanoparticles, and the limit of detection (LOD) as low as 0.1 mg/L was achieved.

Adaptive Gap-Tunable Surface-Enhanced Raman Spectroscopy

Gap plasmon (GP) resonance in static surface-enhanced Raman spectroscopy (SERS) structures is generally too narrow and not tunable. Here, we present an adaptive gap-tunable SERS device to selectively enhance and modulate different vibrational modes via active flexible Au nanogaps, with adaptive optical control. The tunability of GP resonance is up to ∼1200 cm-1 by engineering gap width, facilitated by mechanical bending of a polyethylene terephthalate substrate. We confirm that the tuned GP resonance selectively enhances different Raman spectral regions of the molecules. Additionally, we dynamically control the SERS intensity through the wavefront shaping of excitation beams. Furthermore, we demonstrate simulation results, exhibiting the mechanical and optical properties of a one-dimensional flexible nanogap and their advantage in high-speed biomedical sensing. Our work provides a unique approach for observing and controlling the enhanced chemical responses with dynamic tunability.

A stable and flexible Au@Ag NPs/PVA SERS platform for thiram residue detection on rough surface

Flexible and transparent surface-enhanced Raman scattering (SERS) substrates have gained great attention in analysis field as they offer a fast, non-destructive, and highly sensitive platform for in-situ detection. In this work, we present a facile one-pot strategy for synthesizing gold-cored silver shell nanoparticles (Au@Ag NPs) in the polyvinyl alcohol (PVA) colloid. With no other reducing agents, PVA can serve as both reducing and stabilizing agents for forming Au@Ag NPs. Besides, PVA acts as a scaffold to maintain SERS "hot-spots" by preventing nanoparticle aggregation. By using this flexible Au@Ag NPs/PVA colloid, the analytes can be extracted from rough surfaces for SERS measurements with excellent sensitivity, repeatability and stability. The SERS activity of the Au@Ag NPs/PVA remained at 89.8% even after 120 days of storage at room temperature in sealed air atmosphere. The selective detection of thiram residues on the surface of fruits and vegetables was successfully achieved. The limits of detection for thiram residues on apple and tomato surfaces were measured to be 0.58 and 0.56 ng cm-2, respectively, with recovery rate ranging from 91% to 107%. This work demonstrates the immense application potential of SERS colloid platform in the fields of food safety and environmental analysis.

Pesticide Identification Using Surface-Enhanced Raman Spectroscopy and Density Functional Theory Calculations: From Structural Insights to On-Site Detection

Pesticides play an important role in conventional agriculture. Yet, their harmful effects on the environment are becoming increasingly apparent. The occurrence of pesticides is hence being monitored worldwide. For fast, easy, yet sensitive identification, surface-enhanced Raman spectroscopy (SERS) is a powerful tool. In this study, a method is introduced that may be amended to in-field detection of pesticides. Gold and silver nanoparticles were synthesized, size-tailored, and characterized. The herbicide paraquat and the fungicide thiram served as model compounds. The preparation yielded reproducible SERS spectra. Using quantum chemical computation, Raman and SERS spectra were calculated and analyzed. The interpretation of vibrational modes in combination with SERS enhancement and attenuation allowed us to identify compound-specific bands. The assignment was interpreted in terms of the orientation of paraquat and thiram on the gold and silver nanoparticle surfaces. Paraquat preferred a co-planar arrangement parallel to the gold nanoparticle surface and a head-on orientation on the silver nanoparticle. For thiram, breaking of the disulfide bond was recognized, such that interaction with the surface occurred via the sulfur atoms. Successful detection of the pesticides after recollection from vegetable leaves demonstrated the method's applicability for pesticide identification.