Surface-enhanced Raman Imaging Research Articles

Confocal Surface-Enhanced Raman Imaging of the Intestinal Barrier Crossing Behavior of Model Nanoplastics in Daphnia Magna.

Nanoplastics (nP) pose hazards to aquatic animals once they are ingested. Significant knowledge gaps exist regarding the nP translocation across the animal intestine, which is the first barrier between the ingested nP and the animal body. We examined the intestinal barrier crossing behavior of nP in an aquatic animal model (Daphnia magna) and determined the translocation mechanism with the help of model "core-shell" polystyrene nanoplastics (nPS) and confocal surface-enhanced Raman spectroscopy (SERS). The Raman reporter (4-mercaptobenzoic acid)-tagged gold "core" of the model nPS enables sensitive and reliable particle imaging by confocal SERS. This method detected SERS signals of model nPS concentration as low as 4.1 × 109 particles/L (equivalent to 0.27 μg/L PS "shell" concentration). The translocation was observed with the help of multilayer stacked Raman maps of SERS signals of the model nPS. With a higher concentration or longer exposure time of the model nPS, uptake and translocation of the plastic particles increased. In addition, we demonstrated that clathrin-dependent endocytosis and macropinocytosis were two major mechanisms underlying the translocation. This study contributes to a mechanistic understanding of nP translocation by using the pioneering model nPS and an analytical toolkit, which undergird further investigations into nP behavior and health effects in aquatic species.

Imaging and identification of single nanoplastic particles and agglomerates

Pollution by nanoplastic is a growing environmental and health concern. Currently the extent of nanoplastic in the environment can only be cumbersomely and indirectly estimated but not measured. To be able to quantify the extent of the problem, detection methods that can identify nanoplastic particles that are smaller than 1 mum are critically needed. Here, we employ surface-enhanced Raman scattering (SERS) to image and identify single nanoplastic particles down to 100 nm in size. We can differentiate between single particles and agglomerates and our method allows an improvement in detection speed of 10^{7} compared to state-of-the art surface-enhanced Raman imaging. Being able to resolve single particles allows to measure the SERS enhancement factor on individual nanoplastic particles instead of averaging over a concentration without spatial information. Our results thus contribute to the better understanding and employment of SERS for nanoplastic detection and present an important step for the development of future sensors.

Fluorescence-free bis(dithiolene)nickel dyes for surface-enhanced resonance Raman imaging in the second near-infrared window

Second near-infrared window (NIR-II, 1000–1700 nm) imaging is one of the foremost optical imaging techniques. However, surface-enhanced Raman scattering (SERS)-based research in this optical region remains in its infancy, mainly because of a lack of suitable NIR-II Raman reporters. Herein, we report the first example of a nickel dithiolene complex as a NIR-II resonance Raman reporter with intense long wavelength absorption (ε = 9.58 × 104 m−1 cm−1 at 1007 nm), fluorescence-free features and ultrahigh affinity to noble metal surfaces with its eight sulfur atoms. Surface-enhanced resonance Raman scattering nanoprobes constructed with such reporters enable high contrast and highly photostable lymph node imaging far superior to that possible with existing NIR-I and NIR-II SERS nanoprobes. The developed NIR-II nanoprobes allow deep optical penetration (8 mm) as well as in vivo SERS detection of deep-seated microtumors in mice.

Surface-enhanced Raman imaging through sprayed probes for the application in chemical visualization of methamphetamine within fingerprints.

For fingerprint-involved forensic investigations, cyanoacrylates and inorganic nanophosphors are mostly used for fingerprint visualization. However, methods to simultaneously report fingerprint images and the corresponding specific chemical information have yet to be realized. In this work, chemical visualization of the analytes in fingerprints is achieved through surface-enhanced Raman spectroscopy (SERS) measurements with the aid of spray-dispersed gold nanorods (AuNRs). The optimal coverage of AuNRs was studied by theoretical simulations and experimental operations. A rapid sampling of fingerprints with the chemical of interest was developed by tuning the spray parameters. In particular, the SERS imaging of methamphetamine in fingerprint latent was attempted by addressing the SERS spectral features of methamphetamine. This chemical visualization method reflects both the graphical and chemical characteristics of fingerprints in a single batch measurement, in which methamphetamine can be detected and mapped at the concentration of 10-5M. The data processing approach was also modified by employing relevant logical judgments. The improved SERS images with sharpened patterns of fingerprints were obtained by involving the scored multi-peak judgments.

A Universal and Accurate Method for Easily Identifying Components in Raman Spectroscopy Based on Deep Learning.

Raman spectroscopy has been widely used to provide the structural fingerprint for molecular identification. Due to interference from coexisting components, noise, baseline, and systematic differences between spectrometers, component identification with Raman spectra is challenging, especially for mixtures. In this study, a method entitled DeepRaman has been proposed to solve those problems by combining the comparison ability of a pseudo-Siamese neural network (pSNN) and the input-shape flexibility of spatial pyramid pooling (SPP). DeepRaman was trained, validated, and tested with 41,564 augmented Raman spectra from two databases (pharmaceutical material and S.T. Japan). It can achieve 96.29% accuracy, 98.40% true positive rate (TPR), and 94.36% true negative rate (TNR) on the test set. Another six data sets measured on different instruments were used to evaluate the performance of the proposed method from different aspects. DeepRaman can provide accurate identification results and significantly outperform the hit quality index (HQI) method and other deep learning models. In addition, it performs well in cases of different spectral complexity and low-content components. Once the model is established, it can be used directly on different data sets without retraining or transfer learning. Furthermore, it also obtains promising results for the analysis of surface-enhanced Raman spectroscopy (SERS) data sets and Raman imaging data sets. In summary, it is an accurate, universal, and ready-to-use method for component identification in various application scenarios.

Progress of advanced nanomaterials in diagnosis of neurodegenerative diseases

Neurodegenerative diseases (NDDs) encompass a wide range of clinically and pathologically diverse diseases characterized by progressive long-term cognitive decline, memory and function loss in daily life. Due to the lack of effective drugs and therapeutic strategies for preventing or delaying neurodegenerative progression, it is urgent to diagnose NDDs as early and accurately as possible. Nanomaterials, emerged as one of the most promising materials in the 21st century, have been widely applied and play a significant role in diagnosis and treatment of NDDs because of their remarkable properties including stability, prominent biocompatibility, unique structure, novel physical and chemical characteristics. In this review, we outlined general strategies for the application of different types of advanced materials in early and staged diagnosis of NDDs in vivo and in vitro. According to applied technology, in vivo research mainly involves magnetic resonance, fluorescence, and surface enhanced Raman imaging on structures of brain tissues, cerebral vessels and related distributions of biomarkers. In vitro research is focused on the detection of fluid biomarkers in cerebrospinal fluid and peripheral blood based on fluorescence, electrochemical, Raman and surface plasmon resonance techniques. Finally, we discussed the current challenges and future perspectives of biomarker-based NDDs diagnosis as well as potential applications regarding advanced nanomaterials.

Progress in surface-enhanced Raman scattering (SERS) imaging of cellular functional molecules and related applications

<p indent="0mm">Surface-enhanced Raman spectroscopy (SERS) has the characteristics of high sensitivity and high throughput. As a non-destructive biological imaging technology, SERS imaging has been widely used in biological analysis and imaging, such as quantification, structural analysis and functional tracking of glycan on cell surface, microRNA and protein in cells, analysis of cellular pH, describing the edges of tumor tissues to guide surgical resection, and quick detection of bacteria and bacteria communications. SERS imaging can avoid the strong molecular self-fluorescence in living systems and the photobleaching phenomenon in fluorescence imaging, and achieve highly sensitive and highly throughput bioimaging with fingerprint spectra of different Raman beacons. Combined with other imaging technologies (such as magnetic resonance imaging and photoacoustic imaging), SERS imaging is expected to be applied in the research of more complex living systems. This article reviews the recent research progress in surface enhanced Raman imaging of cellular functional molecules and its applications.

Analyte-Induced Desert Rose-like Ag Nanostructures for Surface-Enhanced Raman Scattering-Based Biomolecule Detection and Imaging.

Biomolecule detection based on surface-enhanced Raman scattering (SERS) for application to biosensors and bio-imaging requires the fabrication of SERS nanoprobes that can generate strong Raman signals as well as surface modifications for analyte-specific recognition and binding. Such requirements lead to disadvantages in terms of reproducibility and practicality, and thus, it has been difficult to apply biomolecule detection utilizing the advantages of the SERS phenomenon to actual clinically relevant analysis. To achieve reproducible and practical SERS signal generation in a biomolecule-specific manner without requiring the synthesis of nanostructures and their related surface modification to introduce molecules for specific recognition, we developed a new type of SERS probe formed by enzyme reactions in the presence of Raman reporters. By forming unique plasmonic structures, our method achieves the detection of biomolecules on chips with uniform and stable signals over long periods. To test the proposed approach, we applied it to a SERS-based immunohistochemistry assay and found successful multiplexed protein detection in brain tissue from transgenic mice.

Simultaneous Deep Tracking of Stem Cells by Surface Enhanced Raman Imaging Combined with Single‐Cell Tracking by NIR‐II Imaging in Myocardial Infarction

AbstractStem cell therapy has been used as a potential approach for the treatment of myocardial infarction (MI) over the last two decades. Imaging cellular behaviors of the transplanted stem cells with deep tissue penetration and high precision imaging modalities is crucial for the clinical translation of stem cell therapy approaches for MI. Herein, a gold nanostar (Au‐Star) based second near‐infrared window (NIR‐II) fluorescence/surface enhanced Raman scattering dual‐modal imaging probe (gold nanostar‐3.3′‐diethylthiatricarbocyanine iodide‐silver sulfide nanoparticles, Au‐Star‐DTTC‐Ag2S NPs, GDS NPs) is designed for labeling and precise tracking of the stem cells. The Ag2S compartment generates strong NIR‐II emission, which compensates for the deficiencies of bioluminescent imaging and enables the dynamic observation of in vivo cellular behavior. Subsequently, the specific Raman signal of Au‐Star‐DTTC compartment enables high‐resolution imaging, which could effectively delineate stem cells from the surrounding normal tissues, even at a single‐cell resolution. Using this imaging and tracking approach, it is able to track stem cells in hypodermic and MI models, with high resolution and depth‐independent imaging capabilities, which have not been reported in any other cell tracking platform. This two‐armed imaging toolkit offers new opportunities for a wide range of mechanistic stem cell therapy investigations in different organs.

Review—Biosensing and Biomedical Applications of Graphene: A Review of Current Progress and Future Prospect

Graphene has generated widely interest in biosensor study because it had a large surface area, excellent electrical and thermal conductivity, high mechanical strength and other unique physical and chemical properties. In this paper, graphene was reviewed from three aspects. Firstly, several common fabrication methods and characteristics of graphene were introduced. Secondly, applications of the nanosized graphene (NG) and nanosized graphene oxide (NGO) in biosensor and medical imaging were discussed. The NG and NGO had the characteristics of photoluminescence. Based on the fluorescence quenching nature of the graphene surface, the targeting molecules could be confirmed by detecting the fluorescent substance. In addition, the graphene oxide (GO) had a promising prospect in the field of surface-enhanced Raman imaging. In the field of electrochemistry, graphene and its derivatives could be modified on the surface to couple with ligands and antigens and were able to detect specific biomolecules, such as glucose, DNA, proteins and etc. Thirdly, this paper introduced graphene applications in medical treatment. Due to the inherent high near-infrared (NIR) absorbance, graphene materials were widely used in the treatment of in vivo cancer photothermal therapy. The combination of the graphene, anticancer drugs, and specific antigens was highly efficient for drug delivery. This paper summarized the achievements of graphene materials in the medical diagnostics, the presents challenges, and the future prospect.

Plasmonic nanoparticle-based expansion microscopy with surface-enhanced Raman and dark-field spectroscopic imaging.

Fluorescence-based expansion microscopy (ExM) is a new technique which can yield nanoscale resolution of biological specimen on a conventional fluorescence microscope through physical sample expansion up to 20 times its original dimensions while preserving structural information. It however inherits known issues of fluorescence microscopy such as photostability and multiplexing capabilities, as well as an ExM-specific issue in signal intensity reduction due to a dilution effect after expansion. To address these issues, we propose using antigen-targeting plasmonic nanoparticle labels which can be imaged using surface-enhanced Raman scattering spectroscopy (SERS) and dark-field spectroscopy. We demonstrate that the nanoparticles enable multimodal imaging: bright-field, dark-field and SERS, with excellent photostability, contrast enhancement and brightness.

Raman Imaging in Cell Membranes, Lipid-Rich Organelles, and Lipid Bilayers.

Raman-based optical imaging is a promising analytical tool for noninvasive, label-free chemical imaging of lipid bilayers and cellular membranes. Imaging using spontaneous Raman scattering suffers from a low intensity that hinders its use in some cellular applications. However, developments in coherent Raman imaging, surface-enhanced Raman imaging, and tip-enhanced Raman imaging have enabled video-rate imaging, excellent detection limits, and nanometer spatial resolution, respectively. After a brief introduction to these commonly used Raman imaging techniques for cell membrane studies, this review discusses selected applications of these modalities for chemical imaging of membrane proteins and lipids. Finally, recent developments in chemical tags for Raman imaging and their applications in the analysis of selected cell membrane components are summarized. Ongoing developments toward improving the temporal and spatial resolution of Raman imaging and small-molecule tags with strong Raman scattering cross sections continue to expand the utility of Raman imaging for diverse cell membrane studies.

Plasmonic patterned wide-field gap mode mechanism for surface enhanced Raman imaging

The gap mode enhancement of metal nanoparticles is introduced into wide-field Raman microscopic imaging, where it produces a more efficient Raman scattering map compared with the scanning mechanism based on a single nanoparticle. Patterned surface plasmon illumination technique is employed to extend spatial resolution of the wide-field Raman imaging to 133 nm achieved by a modified total internal reflection microscope. The images by different Raman shifts are extracted by using narrow band pass dielectric filters. The technique can serve as a robust tool for wide-field surface enhanced Raman imaging.

Determination of trace thiophanate-methyl and its metabolite carbendazim with teratogenic risk in red bell pepper (Capsicumannuum L.) by surface-enhanced Raman imaging technique

Surface-enhanced Raman scattering (SERS) imaging coupling with multivariate analysis in spectral region of 200 to 1800cm−1 was developed to quantify and visualize thiophanate-methyl (TM) and its metabolite carbendazim residues in red bell pepper (Capsicum annuum L.). Least squares support vector machines (LS-SVM) and support vector machines (SVM) models based on seven optimized characteristic peaks that showed SERS effects of TM and its metabolite carbendazim residues were employed to establish prediction models. SERS spectra with first derivative (1st) and second derivative (2nd) method were subsequently compared and the optimized model of 1st-LS-SVM acquired showed the best performance (RPD=6.08, R2P=0.986 and RMSEP=0.473). The results demonstrated that SERS imaging with multivariate analysis had the potential for rapid determination and visualization of the trace TM and its metabolite carbendazim residues in complex food matrices.

Detection of malathion in food peels by surface-enhanced Raman imaging spectroscopy and multivariate curve resolution

An analytical methodology was developed for detection of malathion in the peels of tomatoes and Damson plums by surface-enhanced Raman imaging spectroscopy and multivariate curve resolution. To recover the pure spectra and the distribution mapping of the analyzed surfaces, non-negative matrix factorization (NMF), multivariate curve calibration methods with alternating least squares (MCR-ALS) and MCR with weighted alternating least square (MCR-WALS) were utilized. Error covariance matrices were estimated to evaluate the structure of the error over all the data. For the tomato data, NMF-ALS and MCR-ALS presented excellent spectral recovery even in the absence of initial knowledge of the pesticide spectrum. For the Damson plum data, owing to heteroscedastic noise, MCR-WALS produced better results. This methodology enabled detection below to the maximum residue limit permitted for this pesticide. This approach can be implemented for in situ monitoring because it is fast and does not require extensive manipulation of samples, making its use feasible for other fruits and pesticides as well.

Surface-enhanced Raman imaging of cell membrane by a highly homogeneous and isotropic silver nanostructure.

Label-free chemical imaging of live cell membranes can shed light on the molecular basis of cell membrane functionalities and their alterations under membrane-related diseases. In principle, this can be done by surface-enhanced Raman scattering (SERS) in confocal microscopy, but requires engineering plasmonic architectures with a spatially invariant SERS enhancement factor G(x, y) = G. To this end, we exploit a self-assembled isotropic nanostructure with characteristics of homogeneity typical of the so-called near-hyperuniform disorder. The resulting highly dense, homogeneous and isotropic random pattern consists of clusters of silver nanoparticles with limited size dispersion. This nanostructure brings together several advantages: very large hot spot density (∼10(4) μm(-2)), superior spatial reproducibility (SD < 1% over 2500 μm(2)) and single-molecule sensitivity (Gav ∼ 10(9)), all on a centimeter scale transparent active area. We are able to reconstruct the label-free SERS-based chemical map of live cell membranes with confocal resolution. In particular, SERS imaging is here demonstrated on red blood cells in vitro in order to use the Raman-resonant heme of the cell as a contrast medium to prove spectroscopic detection of membrane molecules. Numerical simulations also clarify the SERS characteristics of the substrate in terms of electromagnetic enhancement and distance sensitivity range consistently with the experiments. The large SERS-active area is intended for multi-cellular imaging on the same substrate, which is important for spectroscopic comparative analysis of complex organisms like cells. This opens new routes for in situ quantitative surface analysis and dynamic probing of living cells exposed to membrane-targeting drugs.

Synthetically Encoding 10 nm Morphology in Silicon Nanowires

Si nanowires (NWs) have been widely explored as a platform for photonic and electronic technologies. Here, we report a bottom-up method to break the conventional "wire" symmetry and synthetically encode a high-resolution array of arbitrary shapes, including nanorods, sinusoids, bowties, tapers, nanogaps, and gratings, along the NW growth axis. Rapid modulation of phosphorus doping combined with selective wet-chemical etching enabled morphological features as small as 10 nm to be patterned over wires more than 50 μm in length. This capability fundamentally expands the set of technologies that can be realized with Si NWs, and as proof-of-concept, we demonstrate two distinct applications. First, nanogap-encoded NWs were used as templates for Noble metals, yielding plasmonic structures with tunable resonances for surface-enhanced Raman imaging. Second, core/shell Si/SiO2 nanorods were integrated into electronic devices that exhibit resistive switching, enabling nonvolatile memory storage. Moving beyond these initial examples, we envision this method will become a generic route to encode new functionality in semiconductor NWs.

Raman and SERS microscopy for molecular imaging of live cells

Raman microscopy is a promising technology for visualizing the distribution of molecules in cells. A challenge for live-cell imaging using Raman microscopy has been long imaging times owing to the weak Raman signal. Here we present a protocol for constructing and using a Raman microscope equipped with both a slit-scanning excitation and detection system and a laser steering and nanoparticle-tracking system. Slit scanning allows Raman imaging with high temporal and spatial resolution, whereas the laser beam steering system enables dynamic surface-enhanced Raman imaging using gold nanoparticles. Both features enable mapping of the distributions of molecules in live cells and visualization of cellular transport pathways. Furthermore, its utility can be expanded to small-molecule imaging by using tiny Raman-active tags such as alkyne. For example, DNA synthesis in a cell can be visualized by detecting 5-ethynyl-2'-deoxyuridine (EdU), a deoxyuridine derivative with an alkyne moiety. We describe the optics, hardware and software to construct the Raman microscope, and discuss the conditions and parameters involved in live-cell imaging. The whole system can be built in ∼8 h.

Nanoclustered Gold Honeycombs for Surface-Enhanced Raman Scattering

A honeycomb-shaped gold substrate was developed for surface-enhanced Raman imaging (SERI). The honeycombs are composed of clusters of 50-70 nm gold nanoparticles and exhibit high Raman enhancement efficiency. An average surface enhancement factor (ASEF) of 1.7 × 10(6) was estimated for a monolayer of L-cysteine molecules adsorbed to gold via a thiol linkage. The presence of a linear relationship in the low concentration region was observed in SERI detection of malachite green isothiocyanate (MGITC). These results together with the high reproducibility and simple and cost-effective fabrication of this substrate suggest that it has utility for applications of surface-enhanced Raman scattering (SERS) in quantitative diagnoses and analyte detection.

Remote Surface Enhanced Raman Imaging via a Nanostructured Optical Fiber Array

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