Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning

Radiation-induced lung injury (RILI) is a dose-limiting toxicity for cancer patients receiving thoracic radiotherapy. As such, it is important to characterize metabolic associations with the early and late stages of RILI, namely pneumonitis and pulmonary fibrosis. Recently, Raman spectroscopy has shown utility for the differentiation of pneumonitic and fibrotic tissue states in a mouse model; however, the specific metabolite-disease associations remain relatively unexplored from a Raman perspective. This work harnesses Raman spectroscopy and supervised machine learning to investigate metabolic associations with radiation pneumonitis and pulmonary fibrosis in a mouse model. To this end, Raman spectra were collected from lung tissues of irradiated/non-irradiated C3H/HeJ and C57BL/6J mice and labelled as normal, pneumonitis, or fibrosis, based on histological assessment. Spectra were decomposed into metabolic scores via group and basis restricted non-negative matrix factorization, classified with random forest (GBR-NMF-RF), and metabolites predictive of RILI were identified. To provide comparative context, spectra were decomposed and classified via principal component analysis with random forest (PCA-RF), and full spectra were classified with a convolutional neural network (CNN), as well as logistic regression (LR). Through leave-one-mouse-out cross-validation, we observed that GBR-NMF-RF was comparable to other methods by measure of accuracy and log-loss (p > 0.10 by Mann-Whitney U test), and no methodology was dominant across all classification tasks by measure of area under the receiver operating characteristic curve. Moreover, GBR-NMF-RF results were directly interpretable and identified collagen and specific collagen precursors as top fibrosis predictors, while metabolites with immune and inflammatory functions, such as serine and histidine, were top pneumonitis predictors. Further support for GBR-NMF-RF and the identified metabolite associations with RILI was found as CNN interpretation heatmaps revealed spectral regions consistent with these metabolites.

Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network

Reprogramming of cellular metabolism is a driving factor of tumour progression and radiation therapy resistance. Identifying biochemical signatures associated with tumour radioresistance may assist with the development of targeted treatment strategies to improve clinical outcomes. Raman spectroscopy (RS) can monitor post-irradiation biomolecular changes and signatures of radiation response in tumour cells in a label-free manner. Convolutional Neural Networks (CNN) perform feature extraction directly from data in an end-to-end learning manner, with high classification performance. Furthermore, recently developed CNN explainability techniques help visualize the critical discriminative features captured by the model. In this work, a CNN is developed to characterize tumour response to radiotherapy based on its degree of radioresistance. The model was trained to classify Raman spectra of three human tumour cell lines as radiosensitive (LNCaP) or radioresistant (MCF7, H460) over a range of treatment doses and data collection time points. Additionally, a method based on Gradient-Weighted Class Activation Mapping (Grad-CAM) was used to determine response-specific salient Raman peaks influencing the CNN predictions. The CNN effectively classified the cell spectra, with accuracy, sensitivity, specificity, and F1 score exceeding 99.8%. Grad-CAM heatmaps of H460 and MCF7 cell spectra (radioresistant) exhibited high contributions from Raman bands tentatively assigned to glycogen, amino acids, and nucleic acids. Conversely, heatmaps of LNCaP cells (radiosensitive) revealed activations at lipid and phospholipid bands. Finally, Grad-CAM variable importance scores were derived for glycogen, asparagine, and phosphatidylcholine, and we show that their trends over cell line, dose, and acquisition time agreed with previously established models. Thus, the CNN can accurately detect biomolecular differences in the Raman spectra of tumour cells of varying radiosensitivity without requiring manual feature extraction. Finally, Grad-CAM may help identify metabolic signatures associated with the observed categories, offering the potential for automated clinical tumour radiation response characterization.

Synthesis of Graphene and Graphene Films with Minimal Structural Defects

Graphene is a carbon material with extraordinary properties that has been drawing a significant amount of attention in the recent decade. High-quality graphene can be produced by different methods, such as epitaxial growth, chemical vapor deposition, and micromechanical exfoliation. The reduced graphene oxide route is, however, the only current approach that leads to the large-scale production of graphene materials at a reasonable cost. Unfortunately, graphene oxide reduction normally yields graphene materials with a high defect density. Here, we introduce a new route for the large-scale synthesis of graphene that minimizes the creation of structural defects. The method involves high-quality hydrogen functionalization of graphite followed by thermal dehydrogenation. We also demonstrated that the hydrogenated graphene synthesis route can be used for the preparation of high-quality graphene films on glass substrates. A reliable method for the preparation of these types of films is essential for the widespread implementation of graphene devices. The structural evolution from the hydrogenated form to graphene, as well as the quality of the materials and films, was carefully evaluated by Raman spectroscopy.

Detection of SARS-CoV-2 in saliva by a low-cost LSPR-based sensor

The SARS-CoV-2 pandemic started more than 3 years ago, but the containment of the spread is still a challenge. Screening is imperative for informed decision making by government authorities to contain the spread of the virus locally. The access to screening tests is disproportional, due to the lack of access to reagents, equipment, finances or because of supply chain disruptions. Low and middle-income countries have especially suffered with the lack of these resources. Here, we propose a low cost and easily constructed biosensor device based on localized surface plasmon resonance, or LSPR, for the screening of SARS-CoV-2. The biosensor device, dubbed "sensor" for simplicity, was constructed in two modalities: (1) viral detection in saliva and (2) antibody against COVID in saliva. Saliva collected from 18 patients were tested in triplicates. Both sensors successfully classified all COVID positive patients (among hospitalized and non-hospitalized). From the COVID negative patients 7/8 patients were correctly classified. For both sensors, sensitivity was determined as 100% (95% CI 79.5-100) and specificity as 87.5% (95% CI 80.5-100). The reagents and equipment used for the construction and deployment of this sensor are ubiquitous and low-cost. This sensor technology can then add to the potential solution for challenges related to screening tests in underserved communities.

A Direct Immunoassay Based on Surface-Enhanced Spectroscopy Using AuNP/PS-b-P2VP Nanocomposites

A biosensor was developed for directly detecting human immunoglobulin G (IgG) and adenosine triphosphate (ATP) based on stable and reproducible gold nanoparticles/polystyrene-b-poly(2-vinylpyridine) (AuNP/PS-b-P2VP) nanocomposites. The substrates were functionalized with carboxylic acid groups for the covalent binding of anti-IgG and anti-ATP and the detection of IgG and ATP (1 to 150 μg/mL). SEM images of the nanocomposite show 17 ± 2 nm AuNP clusters adsorbed over a continuous porous PS-b-P2VP thin film. UV–VIS and SERS were used to characterize each step of the substrate functionalization and the specific interaction between anti-IgG and the targeted IgG analyte. The UV–VIS results show a redshift of the LSPR band as the AuNP surface was functionalized and SERS measurements showed consistent changes in the spectral features. Principal component analysis (PCA) was used to discriminate between samples before and after the affinity tests. Moreover, the designed biosensor proved to be sensitive to different concentrations of IgG with a limit-of-detection (LOD) down to 1 μg/mL. Moreover, the selectivity to IgG was confirmed using standard solutions of IgM as a control. Finally, ATP direct immunoassay (LOD = 1 μg/mL) has demonstrated that this nanocomposite platform can be used to detect different types of biomolecules after proper functionalization.

Reconstruction of Raman Spectra of Biochemical Mixtures Using Group and Basis Restricted Non-Negative Matrix Factorization

Raman spectroscopy is a useful tool for obtaining biochemical information from biological samples. However, interpretation of Raman spectroscopy data in order to draw meaningful conclusions related to the biochemical make up of cells and tissues is often difficult and could be misleading if care is not taken in the deconstruction of the spectral data. Our group has previously demonstrated the implementation of a group- and basis-restricted non-negative matrix factorization (GBR-NMF) framework as an alternative to more widely used dimensionality reduction techniques such as principal component analysis (PCA) for the deconstruction of Raman spectroscopy data as related to radiation response monitoring in both cellular and tissue data. While this method provides better biological interpretability of the Raman spectroscopy data, there are some important factors which must be considered in order to provide the most robust GBR-NMF model. We here evaluate and compare the accuracy of a GBR-NMF model in the reconstruction of three mixture solutions of known concentrations. The factors assessed include the effect of solid versus solutions bases spectra, the number of unconstrained components used in the model, the tolerance of different signal to noise thresholds, and how different groups of biochemicals compare to each other. The robustness of the model was assessed by how well the relative concentration of each individual biochemical in the solution mixture is reflected in the GBR-NMF scores obtained. We also evaluated how well the model can reconstruct original data, both with and without the inclusion of an unconstrained component. Overall, we found that solid bases spectra were generally comparable to solution bases spectra in the GBR-NMF model for all groups of biochemicals. The model was found to be relatively tolerant of high levels of noise in the mixture solutions using solid bases spectra. Additionally, the inclusion of an unconstrained component did not have a significant effect on the deconstruction, on the condition that all biochemicals in the mixture were included as bases chemicals in the model. We also report that some groups of biochemicals achieve a more accurate deconstruction using GBR-NMF than others, likely due to similarity in the individual bases spectra.

High-Speed Spectral Characterization of Single-Molecule SERS Fluctuations

The concept of plasmonic "hotspots" is central to the broad field of nanophotonics. In surface-enhanced Raman scattering (SERS), hotspots can increase Raman scattering efficiency by orders of magnitude. Hotspot dimensions may range from a few nanometers down to the atomic scale and are able to generate SERS signals from single molecules. However, these single-molecule SERS signals often show significant fluctuations, and the concept of intense, localized, yet static hotspots has come into question. Recent experiments have shown these SERS intensity fluctuations (SIFs) to occur over an extremely wide range of timescales, from seconds to microseconds, due to the various physical mechanisms causing SERS and the dynamic nature of light-matter interaction at the nanoscale. The underlying source of single-molecule SERS fluctuations is therefore likely to be a complex interplay of several different effects at different timescales. A high-speed acquisition system that captures a full SERS spectrum with microsecond time resolution can therefore provide information about these dynamic processes. Here, we show an acquisition system that collects at a rate of 100,000 SERS spectra per second, allowing high-speed characterization. We find that while each individual SIF event will enhance a different portion of the SERS spectrum, including a single peak, over 10s to 100s of microseconds, the SIF events overall do not favor one region of the spectrum over another. These high-speed SIF events can therefore occur with relatively equal probability over a broad spectral range, covering both the anti-Stokes and the Stokes sides of the spectrum, sometimes leading to anomalously large anti-Stokes peaks. This indicates that both temporally and spectrally transient hotspots drive the SERS fluctuations at high speeds.

Exploring Intensity Distributions and Sampling in SERS-Based Immunoassays

Surface-enhanced Raman scattering (SERS) is a sensitive, widely used spectroscopic technique. However, SERS is perceived as poorly reproducible and insufficiently robust for standard applications in analytical chemistry. Here, we demonstrated that reliable SERS immunoassay quantification at low concentrations (pM range) can be achieved by careful experimental design and appropriate data analysis statistics. A SERS-based immunoassay for IgG in human serum (3.1-50.0 ng mL^-1 or 20.6-333 pM) was developed as a proof of concept. Calibration curves were created using the population median of the band area, centered at 592 cm^-1, of a SERS reporter (Nile Blue A). Histograms of 7200 SERS spectra show lognormal distributions. SEM images of the sensor platform confirm a correlation between the number of SERS probes (ERLs) at the surface and the SERS intensity response. The IgG immunosensor reported here presented a limit of detection of 1.11 ng mL^-1 or 7.39 pM and a limit of quantification of 9.04 ng mL^-1 or 60.30 pM, within a 95% confidence level. The % error of the predicted versus the actual response of a quality control (QC) sample was 0.13%. The percent error of the QC sample decreases exponentially with the number of measurements. Randomly selected spatially separated measurements provided lower QC % error than a larger number of measurements that were closely spaced. We propose that it is necessary to describe the measured populations using an appropriate sample size for good statistics and consider the interrogation of sufficiently large and well-separated areas of the sensor surface to achieve a reliable sampling.

An Economical and Scalable Method to Synthesize Graphitic-Like Films

An economical and facile method to synthesize a precursor for carbon films and materials has been developed. This precursor can be easily coated onto substrates without binder reagents and then converted into a graphitic-like structure after mild thermal treatment. This approach potentially allows the coating of glass surfaces of different shapes and forms, such as the inside of a glass tube, for instance. The precursor consists of tetrahedral halocarbyne units which randomly combine through single electron transfer with organometallic compounds to create a poly(carbyne)-like polymeric material. Advanced characterization tools reveal that the synthesized product (poly(halocarbyne) or PXC, where X indicate the presence of halogens, is composed mostly of carbon, hydrogen, and a variable percentage of residual halocarbon groups. Therefore, it possesses good solubility in organic solvents and can be coated on any complex substrate. The coated PXC material produced here was annealed under mild conditions, leading to the production of a graphitic-like film on a glass substrate. The chemical homogeneity of the carbon material of the film was confirmed by Raman spectroscopy.

Raman spectroscopy and supervised learning as a potential tool to identify high-dose-rate-brachytherapy induced biochemical profiles of prostate cancer

High-dose-rate-brachytherapy (HDR-BT) is an increasingly attractive alternative to external beam radiation-therapy for patients with intermediate risk prostate cancer. Despite this, no bio-marker based method currently exists to monitor treatment response, and the changes which take place at the biochemical level in hypo-fractionated HDR-BT remain poorly understood. The aim of this pilot study is to assess the capability of Raman spectroscopy (RS) combined with principal component analysis (PCA) and random-forest classification (RF) to identify radiation response profiles after a single dose of 13.5 Gy in a cohort of nine patients. We here demonstrate, as a proof-of-concept, how RS-PCA-RF could be utilised as an effective tool in radiation response monitoring, specifically assessing the importance of low variance PCs in complex sample sets. As RS provides information on the biochemical composition of tissue samples, this technique could provide insight into the changes which take place on the biochemical level, as result of HDR-BT treatment.

Prediction of disease progression indicators in prostate cancer patients receiving HDR-brachytherapy using Raman spectroscopy and semi-supervised learning: a pilot study

This work combines Raman spectroscopy (RS) with supervised learning methods-group and basis restricted non-negative matrix factorisation (GBR-NMF) and linear discriminant analysis (LDA)-to aid in the prediction of clinical indicators of disease progression in a cohort of 9 patients receiving high dose rate brachytherapy (HDR-BT) as the primary treatment for intermediate risk (D'Amico) prostate adenocarcinoma. The combination of Raman spectroscopy and GBR-NMF-sparseLDA modelling allowed for the prediction of the following clinical information; Gleason score, cancer of the prostate risk assessment (CAPRA) score of pre-treatment biopsies and a Ki67 score of < 3.5% or > 3.5% in post treatment biopsies. The three clinical indicators of disease progression investigated in this study were predicted using a single set of Raman spectral data acquired from each individual biopsy, obtained pre HDR-BT treatment. This work highlights the potential of RS, combined with supervised learning, as a tool for the prediction of multiple types of clinically relevant information to be acquired simultaneously using pre-treatment biopsies, therefore opening up the potential for avoiding the need for multiple immunohistochemistry (IHC) staining procedures (H&E, Ki67) and blood sample analysis (PSA) to aid in CAPRA scoring.

Selective suppression of {112} anatase facets by fluorination for enhanced TiO2 particle size and phase stability at elevated temperatures

Generally, anatase is the most desirable TiO₂ polymorphic phase for photovoltaic and photocatalytic applications due to its higher photoconductivity and lower recombination rates compared to the rutile phase. However, in applications where temperatures above 500 °C are required, growing pure anatase phase nanoparticles is still a challenge, as above this temperature TiO₂ crystallite sizes are larger than 35 nm which thermodynamically favors the growth of rutile crystallites. In this work, we show strong evidence, for the first time, that achieving a specific fraction (50%) of the {112} facets on the TiO₂ surface is the key limiting step for anatase-to-rutile phase transition, rather than the crystallite size. By using a fluorinated ionic liquid (IL) we have obtained pure anatase phase crystallites at temperatures up to 800 °C, even after the crystallites have grown beyond their thermodynamic size limit of ca. 35 nm. While fluorination by the IL did not affect {001} growth, it stabilized the pure anatase TiO₂ by suppressing the formation of {112} facets on anatase particles. By suppressing the {112} facets, using specific concentrations of fluorinated ionic liquid in the TiO₂ synthesis, we controlled the anatase-to-rutile phase transition over a wide range of temperatures. This information shall help synthetic researchers to determine the appropriate material conditions for specific applications.

Digital plasmonic holography with iterative phase retrieval for sensing

Propagating surface plasmon waves have been used for many applications including imaging and sensing. However, direct in-plane imaging of micro-objects with surface plasmon waves suffers from the lack of simple, two-dimensional lenses, mirrors, and other optical elements. In this paper, we apply lensless digital holographic techniques and leakage radiation microscopy to achieve in-plane surface imaging with propagating surface plasmon waves. As plasmons propagate in two-dimensions and scatter from various objects, a hologram is formed over the surface. Iterative phase retrieval techniques applied to this hologram remove twin image interference for high-resolution in-plane imaging and enable further applications in real-time plasmonic phase sensing.

Peering into the Formation of Template-Free Hierarchical Flowerlike Nanostructures of SrTiO3

The development of efficient advanced functional materials is highly dependent on properties such as morphology, crystallinity, and surface functionality. In this work, hierarchical flowerlike nanostructures of SrTiO3 have been synthesized by a simple template-free solvothermal method involving poly(vinylpyrrolidone) (PVP). Molecular dynamics simulations supported by structural characterization have shown that PVP preferentially adsorbs on {110} facets, thereby promoting the {100} facet growth. This interaction results in the formation of hierarchical flowerlike nanostructures with assembled nanosheets. The petal morphology is strongly dependent on the presence of PVP, and the piling up of nanosheets, leading to nanocubes, is observed when PVP is removed at high temperatures. This work contributes to a better understanding of how to control the morphological properties of SrTiO3, which is fundamental to the synthesis of perovskite-type materials with tailored properties.

High-Speed Fluctuations in Surface-Enhanced Raman Scattering Intensities from Various Nanostructures

The observation of single molecule events using surface-enhanced Raman scattering (SERS) is a well-established phenomenon. These events are characterized by strong fluctuations in SERS intensities. High-speed SERS intensity fluctuations (in the microsecond time scale) have been reported for experiments involving single metallic particles. In this work, the high-speed SERS behavior of six different types of nanostructured metal systems (Ag nanoshells, Ag nanostars, Ag aggregated spheres, Au aggregated spheres, particle-on-mirror, and Ag deposited on microspheres) was investigated. All systems demonstrated high-speed SERS intensity fluctuations. Statistical analysis of the duration of the SERS fluctuations yielded tailed distributions with average event durations around 100 μs. Although the characteristics of the fluctuations seem to be random, the results suggest interesting differences between the system that might be associated with the strength distribution and density of the localized SERS hotspots. For instance, systems with more localized fields, such as nanostars, present faster fluctuation bursts compared to metallic aggregates that support spread-out fields. The results presented here appear to confirm that high-speed SERS intensity fluctuations are a fundamental characteristic of the SERS effect.

Exploring Diffusion and Cellular Uptake: Charged Gold Nanoparticles in an in Vitro Breast Cancer Model

Gold nanoparticles have emerged as a prominent tool in nanomedicine, particularly for applications in cancer diagnostic and treatment. One of the challenges for the successful implementation of gold nanoparticles in cancer therapy is their delivery to the specific cancer area within the tumor microenvironment. The presence of cancer enables a poorly organized vascularization system, increasing the pressure with the microenvironment, limiting the uptake of particles. The physicochemical properties of the gold nanoparticles (size, shape, and surface charge) also have a significant effect on diffusion to the tumor site and cellular uptake. In this work, we analyzed the transport of 10 nm gold nanoparticles with different surface charges (neutral, negative, and positive) through a hydrogel composite. Three-dimensional in vitro models composed of breast cancer cells loaded in the hydrogel composite were used for the qualitative and quantitative evaluation of cellular uptake of the gold nanoparticles. Surprisingly, an inverse correlation between the diffusion coefficients of the nanoparticles and cellular uptake was demonstrated. Positively charged gold nanoparticles displayed high cellular uptake, although their diffusion coefficient indicated slow transport through the hydrogel matrix. Neutral particles, on the other hand, displayed fast diffusion but the lowest cellular uptake. The results obtained indicate that nanoparticle diffusion and cellular uptake should be studied together in realistic in vitro models for a true evaluation of transport in tumor microenvironments.

Detection of Buried Explosives Using a Surface-Enhanced Raman Scattering (SERS) Substrate Tailored for Miniaturized Spectrometers

The advent of miniaturized, fiber-based, Raman spectrometers provides a clear path for the wide implementation of surface-enhanced Raman scattering (SERS) in analytical chemistry. For instance, miniaturized systems are especially useful in field applications due to their simplicity and low cost. However, traditional SERS substrates are generally developed and optimized using expensive Raman microscope systems equipped with high numerical aperture (NA) objective lenses. Here, we introduced a new type of SERS substrate with intrinsic Raman photon directing capability that compensates the relatively low signal collection power of fiber-based Raman spectrometers. The substrate was tested for the detection of buried 2,4-dinitrotoluene in simulated field conditions. A linear calibration curve (R² = 0.98) for 2,4-dinitrotoluene spanning 3 orders of magnitude (from μg kg^-1 to mg kg^-1) was obtained with a limit of detection of 10 μg kg^-1 within a total volume of 10 μL. This detection level is 2 orders of magnitude lower than that possible with the current state-of-the-art technologies, such as ion mobility spectrometry-mass spectrometry. The approach reported here demonstrated a high-performance detection of 2,4-dinitrotoluene in field conditions by a SERS platform optimized for miniaturized Raman systems that can be deployed for a routine inspection of landmine-contaminated sites and homeland security applications.

Present and Future of Surface-Enhanced Raman Scattering

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.

A review on recent advances in the applications of surface-enhanced Raman scattering in analytical chemistry

This review is focused on recent developments of surface-enhanced Raman scattering (SERS) applications in Analytical Chemistry. The work covers advances in the fabrication methods of SERS substrates, including nanoparticles immobilization techniques and advanced nanopatterning with metallic features. Recent insights in quantitative and sampling methods for SERS implementation and the development of new SERS-based approaches for both qualitative and quantitative analysis are discussed. The advent of methods for pre-concentration and new approaches for single-molecule SERS quantification, such as the digital SERS procedure, has provided additional improvements in the analytical figures-of-merit for analysis and assays based on SERS. The use of metal nanostructures as SERS detection elements integrated in devices, such as microfluidic systems and optical fibers, provided new tools for SERS applications that expand beyond the laboratory environment, bringing new opportunities for real-time field tests and process monitoring based on SERS. Finally, selected examples of SERS applications in analytical and bioanalytical chemistry are discussed. The breadth of this work reflects the vast diversity of subjects and approaches that are inherent to the SERS field. The state of the field indicates the potential for a variety of new SERS-based methods and technologies that can be routinely applied in analytical laboratories.

High-speed imaging of surface-enhanced Raman scattering fluctuations from individual nanoparticles

The concept of plasmonic hotspots is central to the interpretation of the surface-enhanced Raman scattering (SERS) effect. Although plasmonic hotspots are generally portrayed as static features, single-molecule SERS (SM-SERS) is marked by characteristic time-dependent fluctuations in signal intensity. The origin of those fluctuations can be assigned to a variety of dynamic and complex processes, including molecular adsorption or desorption, surface diffusion, molecular reorientation and metal surface reconstruction. Since each of these mechanisms simultaneously contributes to a fluctuating SERS signal, probing their relative impact in SM-SERS remains an experimental challenge. Here, we introduce a super-resolution imaging technique with an acquisition rate of 800,000 frames per second to probe the spatial and temporal features of the SM-SERS fluctuations from single silver nanoshells. The technique has a spatial resolution of ~7 nm. The images reveal short ~10 µs scattering events localized in various regions on a single nanoparticle. Remarkably, even a fully functionalized nanoparticle was 'dark' more than 98% of the time. The sporadic SERS emission suggests a transient hotspot formation mechanism driven by a random reconstruction of the metallic surface, an effect that dominates over any plasmonic resonance of the particle itself. Our results provide the SERS community with a high-speed experimental approach to study the fast dynamic properties of SM-SERS hotspots in typical room-temperature experimental conditions, with possible implications in catalysis and sensing.

Collagen Type I-Gelatin Methacryloyl Composites: Mimicking the Tumor Microenvironment

Therapeutic drugs can penetrate tissues by diffusion and advection. In a healthy tissue, the interstitial fluid is composed of an influx of nutrients and oxygen from blood vessels. In the case of cancerous tissue, the interstitial fluid is poorly drained because of the lack of lymphatic vasculature, resulting in an increase in interstitial pressure. Furthermore, cancer cells invade healthy tissue by pressing and pushing the surrounding environment, creating an increase in pressure inside the tumor area. This results in a large differential pressure between the tumor and the healthy tissue, leading to an increase in extracellular matrix (ECM) stiffness. Because of high interstitial pressure in addition to matrix stiffening, penetration and distribution of systemic therapies are limited to diffusion, decreasing the efficacy of cancer treatment. This work reports on the development of a microfluidic system that mimics in vitro healthy and cancerous microenvironments using collagen I and gelatin methacryloyl (GelMA) composite hydrogels. The microfluidic device developed here contains a simplistic design with a central chamber and two lateral channels. In the central chamber, hydrogel composites were used to mimic the ECM, whereas lateral channels simulated capillary vessels. The transport of fluorescein sodium salt and fluorescently labeled gold nanoparticles from capillary-mimicking channels through the ECM-mimicking hydrogel was explored by tracking fluorescence. By tuning the hydrogel composition and concentration, the impact of the tumor microenvironment properties on the transport of those species was evaluated. In addition, breast cancer MCF-7 cells were embedded in the hydrogel composites, displaying the formation of 3D clusters with high viability and, consequently, the development of an in vitro tumor model.

Raman spectroscopy detects metabolic signatures of radiation response and hypoxic fluctuations in non-small cell lung cancer

BACKGROUND

Radiation therapy is a standard form of treating non-small cell lung cancer, however, local recurrence is a major issue with this type of treatment. A better understanding of the metabolic response to radiation therapy may provide insight into improved approaches for local tumour control. Cyclic hypoxia is a well-established determinant that influences radiation response, though its impact on other metabolic pathways that control radiosensitivity remains unclear.

METHODS

We used an established Raman spectroscopic (RS) technique in combination with immunofluorescence staining to measure radiation-induced metabolic responses in human non-small cell lung cancer (NSCLC) tumour xenografts. Tumours were established in NOD.CB17-Prkdcscid/J mice, and were exposed to radiation doses of 15 Gy or left untreated. Tumours were harvested at 2 h, 1, 3 and 10 days post irradiation.

RESULTS

We report that xenografted NSCLC tumours demonstrate rapid and stable metabolic changes, following exposure to 15 Gy radiation doses, which can be measured by RS and are dictated by the extent of local tissue oxygenation. In particular, fluctuations in tissue glycogen content were observed as early as 2 h and as late as 10 days post irradiation. Metabolically, this signature was correlated to the extent of tumour regression. Immunofluorescence staining for γ-H2AX, pimonidazole and carbonic anhydrase IX (CAIX) correlated with RS-identified metabolic changes in hypoxia and reoxygenation following radiation exposure.

CONCLUSION

Our results indicate that RS can identify sequential changes in hypoxia and tumour reoxygenation in NSCLC, that play crucial roles in radiosensitivity.

Intensity Fluctuations in Single-Molecule Surface-Enhanced Raman Scattering

Around 20 years ago, the first reports of single-molecule surface-enhanced Raman scattering (SM-SERS) caused a revolution in nanotechnology. Several researchers were quick to recognize the importance of a technique that can provide molecular vibrational fingerprinting at the SM level. Since then, a large amount of work has been devoted to the development of nanostructures capable of SM-SERS detection. A great effort has also been geared toward elucidating the different mechanisms that contribute to the effect. The understanding of the concept of plasmonic SERS hotspots, the role of chemical effects, and the dynamics of atomic and cluster rearrangements in nanometric domains has significantly advanced, driven by new computational and experimental methods used to study SM-SERS. In particular, SERS intensity fluctuations (SIFs) are now recognized as a hallmark of SM-SERS. Interpretation of SM-SERS data must take into consideration temporal and spatial variations as a natural consequence of the extreme localization inherent to surface plasmon resonances. Further analysis of variations in spectral signature, due to either molecular reorientation or photo (or thermal) processes, pointed to a new area that combines the power of SERS fingerprinting at the SM level to modern concepts of catalysis, such as hot-electrons-driven chemistry. This large body of work on the fundamental characteristics of the SM-SERS effect paved the way to the interpretation of other related phenomena, such as tip-enhanced Raman scattering (TERS). Despite all the fundamental progress, there are still very few examples of real applications of SM-SERS. In recent years, our research group has been studying SIFs, focused on different ways to use SM-SERS. The obvious application of SM-SERS is in analytical chemistry, particularly for quantification at ultralow concentrations (below 1 nM). However, quantification using SM-SERS faces a fundamental sampling problem: the analytes (adsorbed in very small amounts, i.e., low surface coverage) must find rare SERS hotspots (areas with intense electric field localization that yields SERS). This limitation leads to strong temporal and spatial variations in SERS intensities, which translates into very large error bars in an experimental calibration curve. We tackled this problem by introducing the concept of "digital SERS". This approach provided a roadmap for SERS quantification at ultralow concentrations and a potential pathway for a better understanding of the "reproducibility problem" associated with SERS. In this Account, we discuss not only the analytical applications but also other implementations of SM-SERS demonstrated by our group. These include the use of SM-SERS as a tool to probe colloidal aggregation, to evaluate the efficiency of SERS substrates, and to characterize the energy of localized resonances. SERS involves a series of random processes: hotspots are rare; surfaces/clusters constantly reconstruct; and molecules diffuse, adsorb, and desorb. All these pathways contribute to strong fluctuations in SERS intensities. Our work indicates that a statistical view of the effect can lead to interesting insights and the potential to fulfill the promise of this SM technique for real-world applications.

Digital plasmonic holography

We demonstrate digital plasmonic holography for direct in-plane imaging with propagating surface-plasmon waves. Imaging with surface plasmons suffers from the lack of simple in-plane lenses and mirrors. Lens-less digital holography techniques, however, rely on digitally decoding an interference pattern between a reference wave and an object wave. With far-field diffractive optics, this decoding scheme provides a full recording, i.e., a hologram, of the amplitude and phase of the object wave, giving three-dimensional information from a two-dimensional recording. For plasmonics, only a one-dimensional recording is needed, and both the phase and amplitude of the propagating plasmons can be extracted for high-resolution in-plane imaging. Here, we demonstrate lens-less, point-source digital plasmonic holography using two methods to record the plasmonic holograms: a dual-probe near-field scanning optical microscope and lithographically defined circular fluorescent screens. The point-source geometry gives in-plane magnification, allowing for high-resolution imaging with relatively lower-resolution microscope objectives. These results pave the way for a new form of in-plane plasmonic imaging, gathering the full complex wave, without the need for plasmonic mirrors or lenses.

Zika Immunoassay Based on Surface-Enhanced Raman Scattering Nanoprobes

Zika virus (ZIKV) was considered a public health emergency of international concern after the 2015 outbreak. Serological tests based on immunoassay platforms is one of the methods applied on the diagnosis of ZIKV and Dengue virus (DENV). However, the high limits of detection (LOD) and the cross-reactivity between ZIKV and DENV are still limitations in immunological tests. In order to tackle these issues, we have designed an immune-specific assay based on surface-enhanced Raman scattering (SERS) nanoprobes. Gold shell-isolated nanoparticles (Au-SHINs) were synthesized with 100 nm Au nanoparticles and 4 nm silica shell thickness coated with Nile Blue (Raman reporter). Then, the SERS nanoprobes were wrapped in a final silica shell and functionalized with monoclonal anti-ZIKV NS1 antibodies. Concentrations of ZIKV NS1 down to 10 ng/mL were probed free of cross-reactivity with DENV NS1 antigens.

Ex Vivo Detection of Circulating Tumor Cells from Whole Blood by Direct Nanoparticle Visualization

The detection of circulating tumor cells (CTCs) from blood samples can predict prognosis, response to systemic chemotherapy, and metastatic spread of carcinoma. Therefore, approaches for CTC identification is an important aspect of current cancer research. Here, a method for the direct visualization of nanoparticle-coated CTCs under dark field illumination is presented. A metastatic breast cancer cell line (4T1) was transduced with a non-native target protein (Thy1.1). Positive 4T1-Thy1.1 cells incubated with antibody-coated metallic nanoshells appeared overly bright at low magnification, allowing a quick screening of samples and easy visual detection of even single isolated CTCs. The use of a nontransduced cell line as control creates the ideal scenario to evaluate nonspecific binding. A murine metastatic tumor model with the 4T1-Thy1.1 cell line was also implemented. Blood was drawn from mice over the course of one month, and CTCs were successfully detected in all positive subjects. This work validates the use of metallic nanoshells as labels for direct visualization of CTCs while providing guidelines to a systematic development of nanotechnology-based detection systems for CTCs.

Breast cancer subtype specific biochemical responses to radiation

External beam radiotherapy is a common form of treatment for breast cancer.

Digital Protocol for Chemical Analysis at Ultralow Concentrations by Surface-Enhanced Raman Scattering

Single molecule surface-enhanced Raman spectroscopy (SM-SERS) has the potential to revolutionize quantitative analysis at ultralow concentrations (less than 1 nM). However, there are no established protocols to generalize the application of this technique in analytical chemistry. Here, a protocol for quantification at ultralow concentrations using SM-SERS is proposed. The approach aims to take advantage of the stochastic nature of the single-molecule regime to achieved lower limits of quantification (LOQ). Two emerging contaminants commonly found in aquatic environments, enrofloxacin (ENRO) and ciprofloxacin (CIPRO), were chosen as nonresonant molecular probes. The methodology involves a multivariate resolution curve fitting known as non-negative matrix factorization with alternating least-squares algorithm (NMF-ALS) to solve spectral overlaps. The key element of the quantification is to realize that, under SM-SERS conditions, the Raman intensity generated by a molecule adsorbed on a "hotspot" can be digitalized. Therefore, the number of SERS event counts (rather than SERS intensities) was shown to be proportional to the solution concentration. This allowed the determination of both ENRO and CIPRO with high accuracy and precision even at ultralow concentrations regime. The LOQ for both ENRO and CIPRO were achieved at 2.8 pM. The digital SERS protocol, suggested here, is a roadmap for the implementation of SM-SERS as a routine tool for quantification at ultralow concentrations.

Plasmonic labeling of subcellular compartments in cancer cells: multiplexing with fine-tuned gold and silver nanoshells

Fine-tuned gold and silver nanoshells were produced via an entirely reformulated synthesis. The new method yielded ultramonodisperse samples, with polydispersity indexes (PI) as low as 0.02 and narrow extinction bands suited for multiplex analysis. A library of nanoshell samples with localized surface plasmon resonances (LSPR) spanning across the visible range was synthesized. Hyperspectral analysis revealed that the average scattering spectrum of 100 nanoshells matched closely to the spectrum of a single nanoshell, indicating an unprecedented low level of nanoparticle-to-nanoparticle variation for this type of system. A cell labeling experiment, targeting different subcellular compartments in MCF-7 human breast cancer cells, demonstrated that these monodisperse nanoparticles can be used as a multiplex platform for single cell analysis at the intracellular and extracellular level. Antibody-coated gold nanoshells targeted the plasma membrane, while silver nanoshells coated with a nuclear localization signal (NLS) targeted the nuclear membrane. A fluorescence counterstaining experiment, as well as single cell hyperspectral microscopy showed the excellent selectivity and specificity of each type of nanoparticle for its designed subcellular compartment. A time-lapse photodegradation experiment confirmed the enhanced stability of the nanoshells over fluorescent labeling and their capabilities for long-term live cell imaging.

SPR platform based on image acquisition for HER2 antigen detection

HER2 antigen is a marker used for breast cancer diagnosis and prevention. Its determination has great importance since breast cancer is one of the most insidious types of cancer in women. HER2 antigen assessment in human serum is traditionally achieved by enzyme-linked immunosorbent assay (ELISA method), but it has some disadvantages, such as suppressing the thermodynamic-kinetic studies regarding the antibody-antigen interaction, and the use of labeled molecules that can promote false positive responses. Biosensors based on surface plasmon resonance (SPR) are sensitive optical techniques widely applied on bioassays. The plasmonic devices do not operate with labeled molecules, overcoming conventional immunoassay limitations, and enabling a direct detection of target analytes. In this way, a new SPR biosensor to assess HER2 antigen has been proposed, using nanohole arrays on a gold thin film by signal transduction of transmitted light measurements from array image acquisitions. These metallic nanostructures may couple the light directly on surface plasmons using a simple collinear arrangement. The proposed device reached an average sensitivity for refractive index (RI) variation on a metal surface of 4146 intensity units/RIU (RIU = RI units). The device feasibility on biomolecular assessment was evaluated. For this, 3 ng ml^-1 known HER2 antigen concentration was efficiently flowed (using a microfluidic system) and detected from aqueous solutions. This outcome shows that the device may be a powerful apparatus for bioassays, particularly toward breast cancer diagnosis and prognosis.

Raman spectroscopy identifies radiation response in human non-small cell lung cancer xenografts

External beam radiation therapy is a standard form of treatment for numerous cancers. Despite this, there are no approved methods to account for patient specific radiation sensitivity. In this report, Raman spectroscopy (RS) was used to identify radiation-induced biochemical changes in human non-small cell lung cancer xenografts. Chemometric analysis revealed unique radiation-related Raman signatures that were specific to nucleic acid, lipid, protein and carbohydrate spectral features. Among these changes was a dramatic shift in the accumulation of glycogen spectral bands for doses of 5 or 15 Gy when compared to unirradiated tumours. When spatial mapping was applied in this analysis there was considerable variability as we found substantial intra- and inter-tumour heterogeneity in the distribution of glycogen and other RS spectral features. Collectively, these data provide unique insight into the biochemical response of tumours, irradiated in vivo, and demonstrate the utility of RS for detecting distinct radiobiological responses in human tumour xenografts.

Polarization-dependent extraordinary optical transmission from upconversion nanoparticles

Enhanced upconversion (UC) emission was experimentally demonstrated using gold double antenna nanoparticles coupled to nanoslits in gold films. The transmitted red emission from UC ytterbium and erbium co-doped sodium yttrium fluoride (NaYF4:Yb(3+)/Er(3+)) nanoparticles (UC NPs) at ∼665 nm (excited with a 980 nm diode laser) was enhanced relative to the green emission at ∼550 nm. The relatively enhanced UC NP emission could be tuned by the different polarization-dependent extraordinary optical transmission modes coupled to the gold nanostructures. Finite-difference time-domain calculations suggest that the preferential enhanced UC emission is related to a combination of different surface plasmon mode excitation coupling to cavity Fabry-Perot interactions. A maximum UC enhancement of 6-fold was measured for nanoslit arrays in the absence of the double antennas. In the presence of the double nanoantennas inside the nanoslits, the UC enhancement was between 2- and 4-fold, depending on the experimental conditions.

Improving the performance of gold nanohole array biosensors by controlling the optical collimation conditions

An experimental investigation on how the bulk and surface sensitivities of gold nanohole arrays fabricated by interference lithography affect the degree of white light beam collimation is presented. The optical transmission response of nanohole arrays has been recorded by focused and collimated beam transmission spectra. The results show that both the bulk and surface sensitivities for the collimated case are much larger than for the focused case. In particular, the shape of the spectra was dependent on the degree of beam collimation. The results showed that improved sensing performance (around 3.5 times) and higher figure of merit (around 4.4 times) can be obtained by simply adjusting the incident/collection experimental conditions in transmission measurements.

A Raman spectroscopic study of cell response to clinical doses of ionizing radiation

The drive toward personalized radiation therapy (RT) has created significant interest in determining patient-specific tumor and normal tissue responses to radiation. Raman spectroscopy (RS) is a non-invasive and label-free technique that can detect radiation response through assessment of radiation-induced biochemical changes in tumor cells. In the current study, single-cell RS identified specific radiation-induced responses in four human epithelial tumor cell lines: lung (H460), breast (MCF-7, MDA-MB-231), and prostate (LNCaP), following exposure to clinical doses of radiation (2-10 Gy). At low radiation doses (2 Gy), H460 and MCF-7 cell lines showed an increase in glycogen-related spectral features, and the LNCaP cell line showed a membrane phospholipid-related radiation response. In these cell lines, only spectral information from populations receiving 10 Gy or less was required to identify radiation-related features using principal component analysis (PCA). In contrast, the MDA-MB-231 cell line showed a significant increase in protein relative to nucleic acid and lipid spectral features at doses of 6 Gy or higher, and high-dose information (30, 50 Gy) was required for PCA to identify this biological response. The biochemical nature of the radiation-related changes occurring in cells exposed to clinical doses was found to segregate by status of p53 and radiation sensitivity. Furthermore, the utility of RS to identify a biological response in human tumor cells exposed to therapeutic doses of radiation was found to be governed by the extent of the biochemical changes induced by a radiation response and is therefore cell line specific. The results of this study demonstrate the utility and effectiveness of single-cell RS to identify and measure biological responses in tumor cells exposed to standard radiotherapy doses.

SERS optrode as a “fishing rod” to direct pre-concentrate analytes from superhydrophobic surfaces

SERS optrodes were used to “fish” aqueous drops from superhydrophobic surfaces, which led to an improvement of 2–3 orders of magnitude in sensitivity. 20 pg of the pesticide triazophos was detected by this method.

Surface plasmon enhanced up-conversion from NaYF4:Yb/Er/Gd nano-rods

The enhancement of upconversion emission from Yb³⁺–Er³⁺–Gd³⁺ co-doped sodium yttrium fluoride (NaYF₄:Yb/Er/Gd) nano-rods (UC NRs) was controlled by gold nanoparticle arrays (AuNPAs) of various periodicities.

Comparison of Ag and SiO2 Nanoparticles for Light Trapping Applications in Silicon Thin Film Solar Cells

Plasmonic and photonic light trapping structures can significantly improve the efficiency of solar cells. This work presents an experimental and computational comparison of identically shaped metallic (Ag) and nonmetallic (SiO2) nanoparticles integrated to the back contact of amorphous silicon solar cells. Our results show comparable performance for both samples, suggesting that minor influence arises from the nanoparticle material. Particularly, no additional beneficial effect of the plasmonic features due to metallic nanoparticles could be observed.

Raman Spectral Studies of Aqueous Acidic Pyrazine Solutions

Raman spectra of aqueous pyrazine have been investigated in acidic media: HCl from pH = 4 up to 11 M; HCLO4 from 0.1 M to 12 M; H2SO4 form 0.1 M to 18 M. From observation of the shifts of the bands from neutral solutions, it has been possible to identify bands uniquely characteristic of unprotonated pyrazine and its two protonated forms. The diprotonated form was only observed for high concentrations of HCLO4 and H2SO4. From bandfitting of the spectral contours it has been possible to construct the species distribution diagram and estimate the pK values. Raman bands of the three species have been identified and assigned. The results are used to explain an unassigned band at 1235 cm-1, reported by several authors, in SERS from pyrazine on silver and gold electrodes.

A silver nanoparticle embedded hydrogel as a substrate for surface contamination analysis by surface-enhanced Raman scattering

A surface enhanced Raman scattering (SERS) hydrogel substrate, capable of extracting small amounts of organic species from surfaces of different types of materials with variable roughness, has been fabricated.

Quantification of ovarian cancer markers with integrated microfluidic concentration gradient and imaging nanohole surface plasmon resonance

Nanohole array-based biosensors integrated with a microfluidic concentration gradient generator were used for imaging detection and quantification of ovarian cancer markers. Calibration curves based on controlled concentrations of the analyte were created using a microfluidic stepped diffusive mixing scheme. Quantification of samples with unknown concentration of analyte was achieved by image-intensity comparison with the calibration curves. The biosensors were first used to detect the immobilization of ovarian cancer marker antibodies, and subsequently applied for the quantification of the ovarian cancer marker r-PAX8 (with a limit of detection of about 5 nM and a dynamic range from 0.25 to 9.0 μg.mL(-1)). The proposed biosensor demonstrated the ability of self-generating calibration curves on-chip in an integrated microfluidic platform, representing a further step towards the development of comprehensive lab-on-chip biomedical diagnostics based on nanohole array technology.

Periodic metallic nanostructures as plasmonic chemical sensors

Periodic plasmonic nanostructures are being widely studied, optimized, and developed to produce a new generation of low-cost and efficient chemical sensors and biosensors. The extensive variety of nanostructures, interrogation approaches, and setups makes a direct comparison of the reported performance from different sensing platforms a challenging exercise. In this feature Article, the most common parameters used for the evaluation of plasmonic nanostructures will be reviewed, with particular focus on the advances in periodic plasmonic nanostructures. Recent progress in the fabrication methods that allow for the high-volume production of periodic plasmonic sensors at low cost will be described, together with an assessment of the state of the art in terms of periodic structures employed for chemical sensing.

Improved synthesis of gold and silver nanoshells

Metallic nanoshells have been in evidence as multifunctional particles for optical and biomedical applications. Their surface plasmon resonance can be tuned over the electromagnetic spectrum by simply adjusting the shell thickness. Obtaining these particles, however, is a complex and time-consuming process, which involves the preparation and functionalization of silica nanoparticles, synthesis of very small metallic nanoparticles seeds, attachment of these seeds to the silica core, and, finally, growing of the shells in a solution commonly referred as K-gold. Here we present synthetic modifications that allow metallic nanoshells to be obtained in a faster and highly reproducible manner. The main improved steps include a procedure for quick preparation of 2.3 ± 0.5 nm gold particles and a faster approach to synthesize the silica cores. An investigation on the effect of the stirring speed on the shell growth showed that the optimal stirring speeds for gold and silver shells were 190 and 1500 rpm, respectively. In order to demonstrate the performance of the nanoshells fabricated by our method in a typical plasmonic application, a method to immobilize these particles on a glass slide was implemented. The immobilized nanoshells were used as substrates for the surface-enhanced Raman scattering from Nile Blue A.