Tumour-derived extracellular vesicles (EVs) are of increasing interest as a resource of diagnostic biomarkers. However, most EV assays require large samples, are time-consuming, low-throughput and costly, and thus impractical for clinical use. Here, we describe a rapid, ultrasensitive and inexpensive nanoplasmon-enhanced scattering (nPES) assay that directly quantifies tumor-derived EVs from as little as 1 μL of plasma. The assay uses the binding of antibody-conjugated gold nanospheres and nanorods to EVs captured by EV-specific antibodies on a sensor chip to produce a local plasmon effect that enhances tumour-derived EV detection sensitivity and specificity. We identified a pancreatic cancer EV biomarker, ephrin type-A receptor 2 (EphA2), and demonstrate that an nPES assay for EphA2-EVs distinguishes pancreatic cancer patients from pancreatitis patients and healthy subjects. EphA2-EVs were also informative in staging tumour progression and in detecting early responses to neoadjuvant therapy, with better performance than a conventional enzyme-linked immunosorbent assay. The nPES assay can be easily refined for clinical use, and readily adapted for diagnosis and monitoring of other conditions with disease-specific EV biomarkers.

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As the major redox couple and nonprotein thiol source in human tissues, the level of glutathione (GSH) has been a concern for its relation with many diseases. However, the similar physical and chemical properties of interference molecules such as cysteine (Cys) and homocysteine (Hcy) make discriminative detection of GSH in complex biological fluids challenging. Here we report a novel surface-enhanced Raman scattering (SERS) platform, based on silver-nanoparticleembedded porous silicon disks (PSDs/Ag) substrates for highly sensitive and selective detection of GSH in biofluids. Silver nanoparticles (AgNPs) were reductively synthesized and aggregated directly into pores of PSDs, achieving a SERS enhancement factor (EF) up to 2.59 × 10 7 . Ellman's reagent 5,5′-ditho-bis (2-nitrobenzoic acid) (DTNB) was selected as the Raman reactive reporting agent, and the GSH quantification was determined using enzymatic recycling method, and allowed the detection limit of GSH to be down to 74.9 nM using a portable Raman spectrometer. Moreover, the significantly overwhelmed enhancement ratio of GSH over other substances enables the discrimination of GSH detection in complex biofluids.

Tumor-derived extracellular vesicles (EVs) are under intensive study for their potential as noninvasive diagnosis biomarkers. Most EV-based cancer diagnostic assays trace supernumerary of a single cancer-associated marker or marker signatures. These types of biomarker assays are either subtype-specific or vulnerable to be masked by high background signals. In this study, we introduce using the β-sheet richness (BR) of the tumor-derived EVs as an effective way to discriminate EVs originating from malignant and nonmalignant cells, where EV contents are evaluated as a collective attribute rather than single factors. Circular dichroism, Fourier transform infrared spectroscopy, fluorescence staining assays, and a de novo workflow combining proteomics, bioinformatics, and protein folding simulations were employed to validate the collective attribute at both cellular and EV levels. Based on the BR of the tumorous EVs, we integrated immunoprecipitation and fluorescence labeling targeting the circulating tumor-derived EVs in serum and developed the process into a clinical assay, named EvIPThT. The assay can distinguish patients with and without malignant disease in a pilot cohort, with weak correlations to prognosis biomarkers, suggesting the potential for a cancer screening panel with existing prognostic biomarkers to improve overall performance.

Nanoporous CuO layer on Cu foil with a thick Cu2O interlayer is synthesized via post annealing of previously fabricated Cu(OH)2 nanowires at 500 °C under an oxygen flow. The formation of the thick sandwiched Cu2O layer is realized through the outward diffusion of Cu ions and subsequent oxidation. An O2 pressure above the dissociation pressure of CuO is used to form a CuO layer at the outer surface of the structure, thus realizing a low cost structure having a porous and high isoelectric point layer. The Cu/Cu2O/CuO structure is used as an efficient electrode for glucose sensing. Sensitivities of [Formula: see text] at 0.8 V versus Ag/AgCl and 1066 μA mM(-1) cm(-2) at 0.6 V versus Ag/AgCl are achieved in an enzymatic and non-enzymatic glucose sensing schemes, respectively. The improved electrochemical sensing ability might be attributed to the efficient electrocatalytic reaction on the high crystal quality CuO layer and the porous structure.

Nanoparticles have become a powerful tool for cell imaging, biomolecule and cell and protein interaction studies, but are difficult to rapidly and accurately measure in most assays. Dark-field microscope (DFM) image analysis approaches used to quantify nanoparticles require high-magnification near-field (HN) images that are labor intensive due to a requirement for manual image selection and focal adjustments needed when identifying and capturing new regions of interest. Low-magnification far-field (LF) DFM imagery is technically simpler to perform but cannot be used as an alternate to HN-DFM quantification, since it is highly sensitive to surface artifacts and debris that can easily mask nanoparticle signal. We now describe a new noise reduction approach that markedly reduces LF-DFM image artifacts to allow sensitive and accurate nanoparticle signal quantification from LF-DFM images. We have used this approach to develop a “Dark Scatter Master” (DSM) algorithm for the popular NIH image analysis program ImageJ, which can be readily adapted for use with automated high-throughput assay analyses. This method demonstrated robust performance quantifying nanoparticles in different assay formats, including a novel method that quantified extracellular vesicles in patient blood sample to detect pancreatic cancer cases. Based on these results, we believe our LF-DFM quantification method can markedly decrease the analysis time of most nanoparticle-based assays to impact both basic research and clinical analyses.

Dark-field microscope (DFM) analysis of nanoparticle binding signal is highly useful for a variety of research and biomedical applications, but current applications for nanoparticle quantification rely on expensive DFM systems. The cost, size, limited robustness of these DFMs limits their utility for non-laboratory settings. Most nanoparticle analyses use high-magnification DFM images, which are labor intensive to acquire and subject to operator bias. Low-magnification DFM image capture is faster, but is subject to background from surface artifacts and debris, although image processing can partially compensate for background signal. We thus mated an LED light source, a dark-field condenser and a 20× objective lens with a mobile phone camera to create an inexpensive, portable and robust DFM system suitable for use in non-laboratory conditions. This proof-of-concept mobile DFM device weighs less than 400g and costs less than $2000, but analysis of images captured with this device reveal similar nanoparticle quantitation results to those acquired with a much larger and more expensive desktop DFMM system. Our results suggest that similar devices may be useful for quantification of stable, nanoparticle-based activity and quantitation assays in resource-limited areas where conventional assay approaches are not practical.

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