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[Image: see text] For more effective early-stage cancer diagnostics, there is a need to develop sensitive and specific, non- or minimally invasive, and cost-effective methods for identifying circulating nanoscale extracellular vesicles (EVs). Here, we report the utilization of a simple plasmonic scaffold composed of a microscale biosilicate substrate embedded with silver nanoparticles for surface-enhanced Raman scattering (SERS) analysis of ovarian and endometrial cancer EVs. These substrates are rapidly and inexpensively produced without any complex equipment or lithography. We extensively characterize the substrates with electron microscopy and outline a reproducible methodology for their use in analyzing EVs from in vitro and in vivo biofluids. We report effective chemical treatments for (i) decoration of metal surfaces with cysteamine to nonspecifically pull down EVs to SERS hotspots and (ii) enzymatic cleavage of extraluminal moieties at the surface of EVs that prevent localization of complementary chemical features (lipids/proteins) to the vicinity of the metal-enhanced fields. We observe a major loss of sensitivity for ovarian and endometrial cancer following enzymatic cleavage of EVs’ extraluminal domain, suggesting its critical significance for diagnostic platforms. We demonstrate that the SERS technique represents an ideal tool to assess and measure the high heterogeneity of EVs isolated from clinical samples in an inexpensive, rapid, and label-free assay.

Using a regular CMOS sensor as a template, we are able to fabricate a simple but highly effective superhydrophobic SERS substrate. Specifically, we decorated the microlens layer of the sensor with 7 μm polystyrene beads to obtain a PDMS patterned replica. The process resulted in a uniform pattern of voids in the PDMS (denoted nanobowls) that are intercalated with a few larger voids (denoted here microbowls). The voids act as superhydrophobic substrates with analyte concentration capabilities in bigger bowl-like structures. Silver nanoparticles were directly grown on the patterned PDMS substrate inside both the nano- and microbowls, and serve as strong electromagnetic field enhancers for the SERS substrate. After systematic characterization of the fabricated SERS substrate by atomic force microscopy and scanning electron microscopy, we demonstrated its SERS performance using 4-aminothiophenol as a reporter molecule. Finally, we employed this innovative substrate to concentrate and analyze extracellular vesicles (EVs) isolated from an MC65 neural cell line in an ultralow sample volume. This substrate can be further exploited for the investigation of various EV biomarkers for early diagnosis of different diseases using liquid biopsy.

Surface-enhanced Raman scattering (SERS) is a powerful technique for sensitive label-free analysis of chemical and biological samples. While much recent work has established sophisticated automation routines using machine learning and related artificial intelligence methods, these efforts have largely focused on downstream processing (e.g., classification tasks) of previously collected data. While fully automated analysis pipelines are desirable, current progress is limited by cumbersome and manually intensive sample preparation and data collection steps. Specifically, a typical lab-scale SERS experiment requires the user to evaluate the quality and reliability of the measurement (i.e., the spectra) as the data are being collected. This need for expert user-intuition is a major bottleneck that limits applicability of SERS-based diagnostics for point-of-care clinical applications, where trained spectroscopists are likely unavailable. While application-agnostic numerical approaches (e.g., signal-to-noise thresholding) are useful, there is an urgent need to develop algorithms that leverage expert user intuition and domain knowledge to simplify and accelerate data collection steps. To address this challenge, in this work, we introduce a machine learning-assisted method at the acquisition stage. We tested six common algorithms to measure best performance in the context of spectral quality judgment. For adoption into future automation platforms, we developed an open-source python package tailored for rapid expert user annotation to train machine learning algorithms. We expect that this new approach to use machine learning to assist in data acquisition can serve as a useful building block for point-of-care SERS diagnostic platforms.

Two nonlinear imaging modalities, coherent anti-Stokes Raman scattering (CARS) and sum-frequency generation (SFG), were successfully combined for sensitive multimodal imaging of multiple solid-state forms and their changes on drug tablet surfaces. Two imaging approaches were used and compared: (i) hyperspectral CARS combined with principal component analysis (PCA) and SFG imaging and (ii) simultaneous narrowband CARS and SFG imaging. Three different solid-state forms of indomethacin-the crystalline gamma and alpha forms, as well as the amorphous form-were clearly distinguished using both approaches. Simultaneous narrowband CARS and SFG imaging was faster, but hyperspectral CARS and SFG imaging has the potential to be applied to a wider variety of more complex samples. These methodologies were further used to follow crystallization of indomethacin on tablet surfaces under two storage conditions: 30 °C/23% RH and 30 °C/75% RH. Imaging with (sub)micron resolution showed that the approach allowed detection of very early stage surface crystallization. The surfaces progressively crystallized to predominantly (but not exclusively) the gamma form at lower humidity and the alpha form at higher humidity. Overall, this study suggests that multimodal nonlinear imaging is a highly sensitive, solid-state (and chemically) specific, rapid, and versatile imaging technique for understanding and hence controlling (surface) solid-state forms and their complex changes in pharmaceuticals.

Extracellular vesicles (EVs) have the ability to function as molecular vehicles and could therefore be harnessed to deliver drugs to target cells in diseases such as cancer. The composition of EVs determines their function as well as their interactions with cells, which consequently affects the cell uptake efficacy of EVs. In this study, we present two novel label-free approaches for studying EVs; characterization of EV composition by time-gated surface-enhanced Raman spectroscopy (TG-SERS) and monitoring the kinetics and amount of cellular uptake of EVs by surface plasmon resonance (SPR) in real-time. Using these methods, we characterized the most abundant EVs of human blood, red blood cell (RBC)- and platelet (PLT)-derived EVs and studied their interactions with prostate cancer cells. Complementary studies were performed with nanoparticle tracking analysis for concentration and size determinations of EVs, zeta potential measurements for surface charge analysis, and fluorophore-based confocal imaging and flow cytometry to confirm EV uptake. Our results revealed distinct biochemical features between the studied EVs and demonstrated that PLT-derived EVs were more efficiently internalized by PC-3 cells than RBC-derived EVs. The two novel label-free techniques introduced in this study were found to efficiently complement conventional techniques and paves the way for further use of TG-SERS and SPR in EV studies.

Human epidermal growth factor receptor 2 (HER2) is overexpressed in over 20% of breast cancers. The dimerization of HER2 receptors leads to the activation of down-stream signals enabling proliferation and survival of malignant phenotypes. Owing to the high expression levels of HER2, combination therapies are currently required for the treatment of HER2-positive breast cancer. Here, we designed non-toxic transformable peptides that self-assemble into micelles in aqueous conditions, but, upon binding to HER2 on cancer cells, transform into nanofibers, which disrupt HER2 dimerization and subsequent downstream signalling events, leading to apoptosis of cancer cells. The phase transformation of the peptides enables specific HER2-targeting and inhibition of HER2 dimerization blocks the expression of proliferation and survival genes in the nucleus. We demonstrate that these transformable peptides can be used as a monotherapy for the treatment of HER2+ breast cancer in mouse xenograft models.

© 2019 Rojalin, Phong, Koster and Carney. All cells release a multitude of nanoscale extracellular vesicles (nEVs) into circulation, offering immense potential for new diagnostic strategies. Yet, clinical translation for nEVs remains a challenge due to their vast heterogeneity, our insufficient ability to isolate subpopulations, and the low frequency of disease-associated nEVs in biofluids. The growing field of nanoplasmonics is poised to address many of these challenges. Innovative materials engineering approaches based on exploiting nanoplasmonic phenomena, i.e. the unique interaction of light with nanoscale metallic materials, can achieve unrivaled sensitivity, offering real-time analysis and new modes of medical and biological imaging. We begin with an introduction into the basic structure and function of nEVs before critically reviewing recent studies utilizing nanoplasmonic platforms to detect and characterize nEVs. For the major techniques considered, surface plasmon resonance (SPR), localized SPR, and surface enhanced Raman spectroscopy (SERS), we introduce and summarize the background theory before reviewing the studies applied to nEVs. Along the way, we consider notable aspects, limitations, and considerations needed to apply plasmonic technologies to nEV detection and analysis.

We recently found that subsequent treatments of hardwood kraft pulps with a tertiary amine (DABCO; 1,4-diazabicyclo[2.2.2]octane) catalyzed hypochlorous acid (Hcat), ozone (Z) and hydrogen peroxide (P) may provide full brightness with low chemical dosages in a short overall reaction time. Here we report chemical characteristics and stability of Hcat–Z–P bleached eucalyptus kraft pulps. In comparison with a normal ECF (elementary chlorine free) bleached pulp the Hcat–Z–P bleached pulps had low carbonyl group content while the degree of polymerization of cellulose remained at high level. However, the brightness of the Hcat–Z–P bleached pulps was reversed more easily under humid ageing conditions in comparison with the ECF bleached pulp. The discoloration was accompanied by an increase in Raman emission at 1560 cm−1 which is indicative of formation of highly conjugated chromophores. The brightness reversion did not correlate with the carbonyl content that is often considered to be the main origin of the brightness loss under humid conditions. In contrast, the brightness instability of the catalytically bleached pulps possibly resulted from the relatively high organochlorine content.

In this work, we utilize a short-wavelength, 532-nm picosecond pulsed laser coupled with a time-gated complementary metal-oxide semiconductor (CMOS) single-photon avalanche diode (SPAD) detector to acquire Raman spectra of several drugs of interest. With this approach, we are able to reveal previously unseen Raman features and suppress the fluorescence background of these drugs. Compared to traditional Raman setups, the present time-resolved technique has two major improvements. First, it is possible to overcome the strong fluorescence background that usually interferes with the much weaker Raman spectra. Second, using the high photon energy excitation light source, we are able to generate a stronger Raman signal compared to traditional instruments. In addition, observations in the time domain can be performed, thus enabling new capabilities in the field of Raman and fluorescence spectroscopy. With this system, we demonstrate for the first time the possibility of recording fluorescence-suppressed Raman spectra of solid, amorphous and crystalline, and non-photoluminescent and photoluminescent drugs such as caffeine, ranitidine hydrochloride, and indomethacin (amorphous and crystalline forms). The raw data acquired by utilizing only the picosecond pulsed laser and a CMOS SPAD detector could be used for identifying the compounds directly without any data processing. Moreover, to validate the accuracy of this time-resolved technique, we present density functional theory (DFT) calculations for a widely used gastric acid inhibitor, ranitidine hydrochloride. The obtained time-resolved Raman peaks were identified based on the calculations and existing literature. Raman spectra using non-time-resolved setups with continuous-wave 785- and 532-nm excitation lasers were used as reference data. Overall, this demonstration of time-resolved Raman and fluorescence measurements with a CMOS SPAD detector shows promise in diverse areas, including fundamental chemical research, the pharmaceutical setting, process analytical technology (PAT), and the life sciences. Graphical abstract Time-resolved Raman measurement of a pharmaceutical sample using the complementary metal-oxide semiconductor (CMOS) single photon avalanche diode (SPAD) detector technology Electronic supplementary material The online version of this article (doi:10.1007/s00216-015-9156-6) contains supplementary material, which is available to authorized users.

When nanocarriers are administered into the blood circulation, a complex biomolecular layer known as the “protein corona” associates with their surface. Although the drivers of corona formation are not known, it is widely accepted that this layer mediates biological interactions of the nanocarrier with its surroundings. Label-free optical methods can be used to study protein corona formation without interfering with its dynamics. We demonstrate the proof-of-concept for a multi-parametric surface plasmon resonance (MP-SPR) technique in monitoring the formation of a protein corona on surface-immobilized liposomes subjected to flowing 100 % human serum. We observed the formation of formulation-dependent “hard” and “soft” coronas with distinct refractive indices, layer thicknesses, and surface mass densities. MP-SPR was also employed to determine the affinity (KD) of a complement system molecule (C3b) with cationic liposomes with and without polyethylene glycol. Tendency to create a thick corona correlated with a higher affinity of opsonin C3b for the surface. The label-free platform provides a fast and robust preclinical tool for tuning nanocarrier surface architecture and composition to control protein corona formation. When nanocarriers are administered into the blood circulation, a complex biomolecular layer known as the "protein corona" associates with their surface. Although the drivers of corona formation are not known, it is widely accepted that this layer mediates biological interactions of the nanocarrier with its surroundings. Label-free optical methods can be used to study protein corona formation without interfering with its dynamics. We demonstrate the proof-ofconcept for a multi-parametric surface plasmon resonance (MP-SPR) technique in monitoring the formation of a protein corona on surface-immobilized liposomes subjected to flowing 100 % human serum. We observed the formation of formulation-dependent "hard" and "soft" coronas with distinct refractive indices, layer thicknesses, and surface mass densities. MP-SPR was also employed to determine the affinity (K-D) of a complement system molecule (C3b) with cationic liposomes with and without polyethylene glycol. Tendency to create a thick corona correlated with a higher affinity of opsonin C3b for the surface. The label-free platform provides a fast and robust preclinical tool for tuning nanocarrier surface architecture and composition to control protein corona formation.

Exosomes are small (~100nm) membrane bound vesicles excreted by cells as part of their normal biological processes. These extracellular vesicles are currently an area of intense research, since they were recently found to carry functional mRNA that allows transfer of proteins and other cellular instructions between cells. Exosomes have been implicated in a wide range of diseases, including cancer. Cancer cells are known to have increased exosome production, and may use those exosomes to prepare remote environments for metastasis. Therefore, there is a strong need to develop characterization methods to help understand the structure and function of these vesicles. However, current techniques, such as proteomics and genomics technologies, rely on aggregating a large amount of exosome material and reporting on chemical content that is averaged over many millions of exosomes. Here we report on the use of laser-tweezers Raman spectroscopy (LTRS) to probe individual vesicles, discovering distinct heterogeneity among exosomes both within a cell line, as well as between different cell lines. Through principal components analysis followed by hierarchical clustering, we have identified four “subpopulations” of exosomes shared across seven cell lines. The key chemical differences between these subpopulations, as determined by spectral analysis of the principal component loadings, are primarily related to membrane composition. Specifically, the differences can be ascribed to cholesterol content, cholesterol to phospholipid ratio, and surface protein expression. Thus, we have shown LTRS to be a powerful method to probe the chemical content of single extracellular vesicles.