Facile fabrication of Au-Ag alloy nanoparticles/Ag nanowires SERS substrates with bimetallic synergistic effect for ultra-sensitive detection of crystal violet and alkali blue 6B.

The bimetallic nanostructure of Au and Ag can integrate two distinct properties into a novel substrate compared to single metal nanostructures. This work presents a rapid and sensitive surface-enhanced Raman scattering (SERS) substrate for detecting illegal food additives and dyes of crystal violet (CV) and alkali blue 6B (AB 6B). Au-Ag alloy nanoparticles/Ag nanowires (Au-Ag ANPs/Ag NWs) were prepared by solid-state ionics method and vacuum thermal evaporation method at 5µA direct current electric field (DCEF), the molar ratio of Au to Ag was 1:18.34. Many 40 nm-140 nm nanoparticles regularly existed on the surface of Ag NWs with the diameters from 80 nm to 150 nm. The fractal dimension of Au-Ag ANPs/Ag NWs is 1.69 due to macroscopic dendritic structures. Compared with single Ag NWs, the prepared Au-Ag ANPs/Ag NWs substrates show superior SERS performance because of higher surface roughness, the SERS active of Ag NWs and bimetallic synergistic effect caused by Au-Ag ANPs, so the limit of detections (LOD) of Au-Ag ANPs/Ag NWs SERS substrates toward detection of CV and AB 6B were as low as 10-16mol/L and 10-9mol/L, respectively. These results indicate that Au-Ag ANPs/Ag NWs substrates can be used for rapid and sensitive detection of CV and AB 6B and have great development potential for detection of illegal food additives and hazardous substances in the fields of environmental monitoring and food safety.

The applicability of the SERS technique in food contamination testing - The detailed spectroscopic, chemometric, genetic, and comparative analysis of food-borne Cronobacter spp. strains.

Microorganisms assigned as Cronobacter are Gram-negative, facultatively anaerobic, bacteria widely distributed in nature, home environments, and hospitals. They can also be detected in foods, milk powder, and powdered infant formula (PIF). Additionally, as an opportunistic pathogen, Cronobacter may cause serious infections, sometimes leading to the death of neonates and infants. Thus, it is essential to test food products for the presence of Cronobacter spp. The currently used standard described in ISO 22964:2017 is a laborious method that could be easily replaced by surface-enhanced Raman scattering (SERS). Here, we demonstrate that SERS allows the identification of food-borne bacteria belonging to Cronobacter spp. based on their SERS spectra. For this purpose, twenty-six Cronobacter strains from different food samples were analyzed. Additionally, it was shown that it is possible to differentiate them from other closely related pathogens such as Salmonella enterica subsp. enterica, Escherichia coli, or Enterobacter spp. The SERS results were supported by principal component analysis (PCA), as well as and sequencing of 16S rRNA, rpoB and fusA genes. Last but not least, it was demonstrated that the cells of Cronobacter sakazakii may be easily separated from PIF using an appropriate filter, microfluidic chip, and dielectrophoresis (DEP) technique.

Au/Ag@ZIF-8 nanocomposite as solid phase extraction adsorbent and SERS substrate for tacrolimus label-free therapeutic drug monitoring in human serum.

Surface Enhanced Raman Scattering (SERS) has been extensively utilized in therapeutic drug monitoring (TDM) due to its rapid detection speed, high sensitivity and straightforward sample pretreatment. In this study, Au/AgNPs were obtained through the reduction of AgNO3 on the surface of AuNPs. Subsequently, Au/AgNPs were embedded into the tetrahedral lattice of ZIF-8 MOFs, resulting in the formation of Au/Ag@ZIF-8 nanocomposites. The Au/Ag@ZIF-8 nanocomposites exhibit a robust electromagnetic enhancement of Au/Ag bimetallic nanoparticles and a considerable adsorption capacity of ZIF-8 MOFs. This enables the pre-enrichment of target molecules in the vicinity of the electromagnetic field of the Au/AgNPs, thereby enhancing the sensitivity of SERS detection. The SERS substrate also exhibits high stability and reproducibility, as well as molecular sieving effects, due to the fact that Au/AgNPs are embedded into the tetrahedral lattice of ZIF-8. A TDM method for tacrolimus (FK506) in human serum was developed by using Au/Ag@ZIF-8 nanocomposites as solid phase extraction (SPE) adsorbent and SERS substrates. The results showed that under the optimized conditions, tacrolimus exhibited satisfactory linearity within the concentration range of 10-5-10-11 mol L-1, with a correlation coefficient (R2) of 0.9944, and the limit of detection (LOD) was as low as 6.4 pg mL-1. The recoveries were observed to range between 92 % and 105 %, with an RSD of below 8 %. The method is highly sensitive, exhibiting a sensitivity that is 3-6 orders of magnitude higher than that of existing analytical techniques. It has the potential to be applied in a clinical setting to biological samples.

Dual LSPR and CT synergy: 3D urchin-like Au@W18O49 enables highly sensitive in-situ SERS detection of dissolved furfural in insulating oils.

Assessing the levels of furfural in insulating oils is a crucial technical method for evaluating the degree of aging and mechanical deterioration of oil-paper insulation. The surface-enhanced Raman spectroscopy (SERS) technique provides an effective method for enhancing the sensitivity of in-situ detection of furfural. In this study, a homogeneous three-dimensional (3D) urchin-like Au@W18O49 heterostructure was synthesized as a SERS substrate using a straightforward hydrothermal method. The origin of the superior Raman enhancement properties of the 3D urchin-like heterostructures formed by the noble metal Au and the plasmonic semiconductor W18O49, which is rich in oxygen vacancies, is analyzed experimentally in conjunction with density-functional theory (DFT) calculations. The Raman enhancement is further amplified by the remarkable dual localized surface plasmon resonance (LSPR) effect, which generates a strong local electric field and creates numerous "hot spots," in addition to the interfacial charge transport (CT). The synergistic effect of these factors results in the 3D urchin-like Au@W18O49 heterostructure exhibiting exceptionally high SERS activity. Testing the rhodamine 6G (R6G) probe resulted in a Raman enhancement factor of 3.41 × 10-8, and the substrate demonstrated excellent homogeneity and stability. Furthermore, the substrate was effectively utilized to achieve highly sensitive in-situ surface-enhanced Raman scattering (SERS) detection of dissolved furfural in complex plant insulating oils. The development of the 3D urchin-like Au@W18O49 heterostructure and the exploration of its enhancement mechanism provide theoretical insights for the advancement of high-performance SERS substrates.

Tuning surface morphology of AuNPs film via thiourea as a stable SERS platform for methylene blue.

Gold nanoparticles (AuNPs) have been extensively utilized in various fields such as sensors, life sciences, and catalysis. In this study, AuNPs were synthesized using a reduction method and subsequently treated with thiourea in an ethanol-water environment to prepare AuNPs film using a centrifugal deposition method for first time, resulting in the aggregation of the initial small-sized AuNPs into larger microsphere-like structures. The addition of thiourea facilitated the interconnection between AuNPs, ultimately leading to the formation of large stable gold microspheres. The sheet resistance of the AuNP films transitioned from being non-conductive to exhibiting a sheet resistance of 42.6 Ω/sq following thiourea treatment. The transformation from a flat surface to tightly connected particles resembling microspheres was observed from SEM images. The thiourea treatment not only altered the morphological characteristic of the AuNPs films but also significantly increased the number of scattering sites on their surface, leading to a substantial enhancement in the Raman scattering effect for methylene blue. This structural configuration also improved the electronic conduction and stability of the treated AuNPs films. Consequently, these findings suggest that AuNPs have promising application prospects in surface-enhanced Raman scatting (SERS), as well as in flexible electronics, catalysis, adsorption, and energy fields.

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 semiconductor SERS sensor of corrosion-resistant PPy/GO composite film by electrochemical growth for detecting crystal violet residues in fresh fish tissue.

Crystal violet (CV) residues in Marine food have produced a severe health threat in human life. In this study, we proposed a semiconductor surface-enhanced Raman scattering (SERS) sensor of corrosion-resistant Polyaniline/Graphene oxide (PPy/GO) film by electrochemical growth method to detect CV residues in fresh fish tissue. A PPy/GO dispersion solution was one-step deposited on a stainless steel sheet surface by electrochemical polymerization process to form a PPy/GO composite film acting as a semiconductor SERS substrate. Since the substrate of PPy/GO film was mainly composed of GO sheet without other metals, it had a good corrosion resistance. The SERS enhancement factor and charge transfer intensity PCT of PPy/Go SERS substrate for CV molecules were up to 1.18 × 106 and 0.903, respectively. Furthermore, the limit of detection (LOD) of PPy/GO SERS substrate could reach 1.58 nM. In addition, SERS sensor of PPy/GO film could identify CV residues in fresh fish tissues, and its recovery rate was 91.8 %-107 %. This preparing method and detecting method we proposed PPy/GO SERS substrate provide a new pathway for detecting CV residues in Marine food.

A critical review on metal organic frameworks (MOFs)-based sensors for foodborne pathogenic bacteria detection.

The pervasive threat of foodborne pathogenic bacteria necessitates advancements in rapid and reliable detection methods. Traditional approaches suffer from significant limitations including prolonged processing times, limited sensitivity and specificity. This review comprehensively examines the integration of metal organic frameworks (MOFs) with sensor technologies for the enhanced detection of foodborne pathogens. MOFs, with their unique properties such as high porosity, tunable pore sizes, and ease of functionalization, offer new avenues for sensor enhancement. This paper provides a comprehensive analysis of recent developments in MOFs-based sensors, particularly focusing on electrochemical, fluorescence, colorimetric, and surface-enhanced Raman spectroscopy sensors. We have provided a detailed introduction for the operational principles of these sensors, highlighting the role of MOFs play in enhancing their performance. Comparative analyses demonstrate MOFs' superior capabilities in enhancing signal response, reducing response time, and expanding detection limits. This review culminates in presenting MOFs as transformative materials in the detection of foodborne pathogens, paving the way for their broader application in ensuring food safety.

Rapid determination of phenolic composition in chamomile (Matricaria recutita L.) using surface-enhanced Raman spectroscopy.

Flavonoids and hydroxycinnamic acids are the main responsible of the antioxidant activity of chamomile (Matricaria recutita L.). Traditional methods for the analysis of the phenolic content in vegetables often suffer from limitations such as being expensive, time-consuming, and complex. In this study, we propose, for the first time, the use of surface-enhanced Raman spectroscopy (SERS) for the rapid determination of the main components of the polyphenolic fraction in chamomile. Results demonstrate that SERS can serve as an alternative or complementary technique to main analytical strategies for qualitative and quantitative determination of polyphenol compounds in plant extracts. The method can be proposed for quasi real-time analysis of herbal teas and infusions, facilitating rapid screening of their main antioxidant components.

Sensitive phenotyping of serum extracellular vesicles on a SERS-microfluidic platform for early-stage clinical diagnosis of ovarian carcinoma.

Ovarian carcinoma (OvCa) poses a severe threat to women's health due to its high mortality rate and lack of efficient early diagnosis approach. There is evidence to suggest that nanosized small extracellular vesicles (sEVs) which carrying cell-specific components from OvCa can serve as potential diagnostic biomarkers. Herein, we reported a Surface-enhanced Raman Scattering (SERS)-multichannel microchip for sEVs (S-MMEV) assay to investigate the phenotype changes of sEVs. The microchip composed of seven microchannels, which enabled the parallel detection of multiple biomarkers to improve the detection accuracy. Using SERS probes conjugated with antibodies recognizing different biomarkers including ubiquitous EV biomarkers (i.e., tetraspanins; CD9, CD81) and putative OvCa tumor biomarkers (i.e. EpCAM, CD24, CA125, EGFR), we successfully analyzed the phenotypic changes of sEVs and accurately differentiated OvCa patients from healthy controls, even at early stage (I-II), with high sensitivity, high specificity and an area under the curve value of 0.9467. Additionally, the proposed approach exhibited higher sensitivity than conventional methods, demonstrating the efficiency of precise detection from cell culture and clinical samples. Collectively, the developed EV phenotyping approach S-MMEV could serve as a potential tool to achieve the early clinical diagnosis of OvCa for further precise diagnosis and personal treatment monitoring.

Quantification of Pectobacterium carotovorum subsp. carotovorum in kimchi cabbage using a surface-enhanced Raman scattering platform with silver nanostructures.

Pectobacterium carotovorum subsp. carotovorum (PCC) is a notorious plant pathogen responsible for severe soft rot in kimchi cabbage, which results in significant economic losses. To detect PCC rapidly and accurately in kimchi cabbage, we developed a surface-enhanced Raman scattering (SERS) substrate on which silver nanospheres (AgNSs), nanowires (AgNWs), and nanoseeds are combined on a polydimethylsiloxane (PDMS) platform. The incorporation of Ag nanoseeds creates a higher density of hotspots, which ensures a low detection limit of 1.001 CFU/mL. Electron microscopy and spectroscopic analyses confirmed the successful fabrication of the substrate and its enhanced sensitivity. The SERS substrate exhibits excellent selectivity by effectively distinguishing PCC from other bacteria commonly found in kimchi cabbage. The substrate gives rise to strong Raman signals across PCC concentrations ranging from 101 to 106 CFU/mL. Additionally, a predictive model was developed for accurately detecting PCC in real kimchi cabbage samples, and the results were validated by polymerase chain reaction measurements. A sensitive, selective, and rapid approach for PCC detection in kimchi cabbage that offers a promising improvement over existing methodologies is presented.

Cerebrospinal fluid-induced stable and reproducible SERS sensing for various meningitis discrimination assisted with machine learning.

Cerebrospinal fluid (CSF)-based pathogen or biochemical testing is the standard approach for clinical diagnosis of various meningitis. However, misdiagnosis and missed diagnosis always occur due to the shortages of unusual clinical manifestations and time-consuming shortcomings, low sensitivity, and poor specificity. Here, for the first time, we propose a simple and reliable CSF-induced SERS platform assisted with machine learning (ML) for the diagnosis and identification of various meningitis. Stable and reproducible SERS spectra are obtained within 30 s by simply mixing the colloidal silver nanoparticles (Ag NPs) with CSF sample, and the relative standard deviation of signal intensity is achieved as low as 2.1%. In contrast to conventional salt agglomeration agent-induced irreversible aggregation for achieving Raman enhancement, a homogeneous and dispersed colloidal solution is observed within 1 h for the mixture of Ag NPs/CSF (containing 110-140 mM chloride), contributing to excellent SERS stability and reproducibility. In addition, the interaction processes and potential enhancement mechanisms of different Ag colloids-based SERS detection induced by CSF sample or conventional NaCl agglomeration agents are studied in detail through in-situ UV-vis absorption spectra, SERS analysis, SEM and optical imaging. Finally, an ML-assisted meningitis classification model is established based on the spectral feature fusion of characteristic peaks and baseline. By using an optimized KNN algorithm, the classification accuracy of autoimmune encephalitis, novel cryptococcal meningitis, viral meningitis, or tuberculous meningitis could be reached 99%, while an accuracy value of 68.74% is achieved for baseline-corrected spectral data. The CSF-induced SERS detection has the potential to provide a new type of liquid biopsy approach in the fields of diagnosis and early detection of various cerebral ailments.

Branched hybridization chain reaction and tetrahedral DNA-based trivalent aptamer powered SERS sensor for ultra-highly sensitive detection of cancer-derived exosomes.

Exosomes have emerged as a promising noninvasive biomarker for early cancer diagnosis due to their ability to carry specific bioinformation related to cancer cells. However, accurate detection of trace amount of cancer-derived exosomes in complex blood remains a significant challenge. Herein, an ultra-highly sensitive SERS sensor, powered by the branched hybridization chain reaction (bHCR) and tetrahedral DNA-based trivalent aptamer (triApt-TDN), has been proposed for precise detection of cancer-derived exosomes. Taking gastric cancer SGC-7901 cells-derived exosomes as a test model, the triApt-TDNs were constructed by conjugating aptamers specific to mucin 1 (MUC1) protein with tetrahedral DNAs and subsequently immobilized on the surface of silver nanorods (AgNRs) arrays to create SERS-active sensing chips capable of specifically capturing exosomes overexpressing MUC1 proteins. The bHCR was further initiated by the trigger aptamers (tgApts) bound to exosomes, and as a result the SERS tags were assembled into AuNP network structures with abundant SERS hotspots. By optimizing the sensing conditions, the SERS sensor showed good performance in ultra-highly sensitive detection of target exosomes within 60 min detection time, with a broad response ranging of 1.44 to 1.44 × 104 particles·µL-1 and an ultralow limit of detection capable of detecting a single exosome in 2 µL sample. Furthermore, the SERS sensor exhibited good uniformity, repeatability and specificity, and capability to distinguish between gastric cancer (GC) patients and healthy controls (HC) through the detection of exosomes in clinical human serums, indicating its promising clinical potential for early diagnosis of gastric cancer.

Machine learning assisted dual-modal SERS detection for circulating tumor cells.

Detecting circulating tumor cells (CTCs) from blood has become a promising approach for cancer diagnosis. Surface-enhanced Raman Spectroscopy (SERS) has rapidly developed as a significant detection technology for CTCs, offering high sensitivity and selectivity. Encoded SERS bioprobes have gained attention due to their excellent specificity and ability to identify tumor cells using Raman signals. Machine learning has also made significant contributions to biomedical applications, especially in medical diagnosis. In this study, we developed a detection strategy combining encoded SERS bioprobes and machine learning models to identify CTCs. Dual-modal SERS bioprobes were designed and co-incubated with tumor cells by the "cocktail" method. An identification model for CTCs was constructed using principal component analysis (PCA) and the Random Forest classification algorithm. This innovative strategy endows SERS bioprobes with both effective magnetic separation and highly sensitive identification of CTCs, even at low concentrations of 2 cells/mL. It achieved a high detection rate of 98% for CTCs and effectively eliminated interference from peripheral WBCs. This simple and efficient strategy provides a new approach for CTCs detection and holds important significance for cancer diagnosis.

Direct laser writing of curved SERS for light-guided enhancement.

Flexible SERS substrates, typically used on irregular surfaces, have unexplored optomechanical effects that could enhance performance. We developed a micromechanically bending structure, i.e. microbender, to study how bending affects SERS substrates' performance. Optical simulations of nanopillar arrays on micro-curved surfaces showed a 25-134 % improvement in mean-field localization at the pillar tips for arrays with pillar diameters of 0.4-1 µm, pitches of 0.5-0.8 µm, and heights of 0.5-4.5 µm. Raman measurements showed that SERS intensity increases when in a curved state due to enhanced light scattering, guiding, and field localization. A curved array of 6 µm tall pillars (0.5 µm diameter, 1 µm spacing) produced Raman intensities similar to dense single-voxel arrays with shorter 0.8 µm pillars (0.2 µm diameter, 0.2 µm gaps) in the planar state. This finding suggests that low resolution fabrication technologies can produce curved SERS substrates with similar performance to high resolution planar SERS, offering an alternative to the current "smaller is better" trend through post-fabrication manipulation.

Combining array-assisted SERS microfluidic chips and machine learning algorithms for clinical leukemia phenotyping.

The disease progression and treatment options of leukemia between different subtypes vary considerably, emphasizing the importance of phenotyping. However, early typing of leukemia remains challenging due to the lack of highly sensitive and specific analytical tools. Herein, we propose a SERS-based platform for the classification of acute lymphoblastic T-cell leukemia (T-ALL) and chronic myeloid leukemia (CML) through the combination of machine learning and microfluidic chips. The ordered arrays in microfluidic channels reshape the microscopic flow field and contacting interfaces, facilitating the uniform and efficient capture of tumor cells. To enable phenotypic analysis, spectrally orthogonal SERS aptamer nanoprobes were applied, providing composite spectral signatures of individual cells in accordance with surface protein expression. Further, machine learning algorithms were employed to analyze the SERS signatures automatically, resulting in an accuracy of 98.6 % for 73 clinical blood samples. The results demonstrate that this platform holds promising potential for clinical leukemia diagnosis and precision medicine.

Microcavity Array-Based Digital SERS Chip for Rapid and Accurate Label-free Quantitative Detection of Live Bacteria.

In this study, we developed a novel digital surface-enhanced Raman spectroscopy (SERS) chip that integrates an inverted pyramid microcavity array, a microchannel cover plate, and a multilayer gold nanoparticle (AuNP) SERS substrate. This innovative design exploits the synergistic effects of the microcavity array and the microchannel to enable rapid and large-scale digital discretization of bacterial suspensions. The concentration effect of the picoliter cavities, combined with the superior Raman enhancement effect of the multilayer AuNP SERS substrate, allows for the precise identification of live bacteria within the microcavities through in situ and label-free SERS testing after a short incubation period. By counting the resulting positive or negative signals, the concentration of the target analyte can be directly determined via Poisson statistics. Experimental results demonstrate that this method enables the accurate quantification of Escherichia coli (E. coli) BL21 within a 4-h incubation period. Compared with traditional analog SERS detection methods, our proposed digital SERS detection strategy reduces the impact of signal intensity fluctuations, thereby significantly improving detection efficiency and accuracy. We believe that this digital SERS chip has great application prospects in the fields of bacterial detection, antibiotic resistance analysis, and cellular dynamics monitoring.

A comparative study of aptasensor vs. immunosensor for ultrasensitive detection of aflatoxin B1 using Ag-pSi SERS substrate.

Numerous SERS based platforms have been designed to address the emerging need for detecting fungal metabolite contamination in foodstuffs, and specifically the Group 1 carcinogen aflatoxin B1. Herein, 4-aminothiophenol modified silver-coated porous silicon was used as the SERS substrate. Two ratiometric responses were individually assessed upon direct target capture using specific aptamers or antibodies. Under optimized physical features, elevated enhancement factor, wide dynamic range, low detection limits and pronounced recycling capabilities were achieved (7.39 × 107, 0.2-200 ppb, 0.0085 and 0.0110 ppb, 7 and 1 regeneration cycles without impairing the performances for aptasensor and immunosensor, respectively). The accuracy and anti-interference responses in several intricate matrices (maize, peanut, wheat, oats and rice) were compared to a routine HPLC method with equivalent recoveries. Overall, the comparative assessment revealed preferable features of reusability, durability and accuracy of the aptasensor over the immunosensor. Furthermore, the results demonstrate the substantial potential of the proposed SERS substrate for diverse on-site analytical applications using simple and portable monitoring instrumentation.

Versatile self-assembled near-infrared SERS nanoprobes for multidrug-resistant bacterial infection-specific surveillance and therapy.

The rise of multidrug-resistant bacteria (MDRB) has made bacterial infection one of the biggest health threats, causing numerous antibiotics to fail. Real-time monitoring of bacterial disease treatment efficacy at the infection site is required. Herein, we report a versatile Raman tag 3,3'-diethylthiatricarbocyanine iodide (DTTC)-conjugated star-shaped Au-MoS2@hyaluronic acid (AMD@HA) nanocomposite as a surface-enhanced Raman scattering (SERS) nanoprobe for quick bacterial identification and in-situ eradication. Localized surface plasmon resonance (LSPR) from the hybrid metallic nanostructure makes AMD@HA highly responsive to the near-infrared laser, enabling it to demonstrate a photothermal (PTT) effect, increased SERS activity, and peroxidase-like catalytic reaction to release reactive oxygen species. The tail vein injection of AMD@HA nanoprobes is invasive, however SERS imaging for bacterial identification is non-invasive and sensitive, making it an efficient residual bacteria monitoring method. The detection limit for methicillin-resistant Staphylococcus aureus (MRSA) is as low as 102 CFU·mL-1, and the substrates allow for taking 120 s to acquire a Raman image of 1600 (40 × 40) pixels. In mouse models of MRSA-induced wound infection and skin abscess, the combination of AMD@HA-mediated PTT and catalytic therapy demonstrates a synergistic effect in promoting wound healing through rapid sterilization. This SERS-guided therapeutic approach exhibits little toxicity and does not cause considerable collateral damage, offering a highly promising intervention for treating diseases caused by MDRB. STATEMENT OF SIGNIFICANCE: This research introduces a SERS nanoprobe, AMD@HA, for the rapid identification and eradication of multidrug-resistant bacteria (MDRB), a critical health threat. The nanoprobe leverages localized surface plasmon resonance for photothermal therapy and enhanced Raman signals, offering a sensitive, non-invasive diagnostic tool. With a low detection limit for MRSA and a synergistic therapeutic effect in mouse models, our approach holds significant promise for treating MDRB-driven infections with minimal toxicity, advancing the field of antimicrobial strategies.

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

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