A Label-Free Platform for Identification of Exosomes from Different Sources.

Exosomes contain cell- and cell-state-specific cargos of proteins, lipids, and nucleic acids and play significant roles in cell signaling and cell-cell communication. Current research into exosome-based biomarkers has relied largely on analyzing candidate biomarkers, i.e., specific proteins or nucleic acids. However, this approach may miss important biomarkers that are yet to be identified. Alternative approaches are to analyze the entire exosome system, either by "omics" methods or by techniques that provide "fingerprints" of the system without identifying each individual biomolecule component. Here, we describe a platform of the latter type, which is based on surface-enhanced Raman spectroscopy (SERS) in combination with multivariate analysis, and demonstrate the utility of this platform for analyzing exosomes derived from different biological sources. First, we examined whether this analysis could use exosomes isolated from fetal bovine serum using a simple, commercially available isolation kit or necessitates the higher purity achieved by the "gold standard" ultracentrifugation/filtration procedure. Our data demonstrate that the latter method is required for this type of analysis. Having established this requirement, we rigorously analyzed the Raman spectral signature of individual exosomes using a unique, hybrid SERS substrate made of a graphene-covered Au surface containing a quasi-periodic array of pyramids. To examine the source of the Raman signal, we used Raman mapping of low and high spatial resolution combined with morphological identification of exosomes by scanning electron microscopy. Both approaches suggested that the spectra were collected from single exosomes. Finally, we demonstrate for the first time that our platform can distinguish among exosomes from different biological sources based on their Raman signature, a promising approach for developing exosome-based fingerprinting. Our study serves as a solid technological foundation for future exploration of the roles of exosomes in various biological processes and their use as biomarkers for disease diagnosis and treatment monitoring

Covariance-domain Dictionary Learning for Overcomplete EEG Source Identification

We propose an algorithm targeting the identification of more sources than channels for electroencephalography (EEG). Our overcomplete source identification algorithm, Cov-DL, leverages dictionary learning methods applied in the covariance-domain. Assuming that EEG sources are uncorrelated within moving time-windows and the scalp mixing is linear, the forward problem can be transferred to the covariance domain which has higher dimensionality than the original EEG channel domain. This allows for learning the overcomplete mixing matrix that generates the scalp EEG even when there may be more sources than sensors active at any time segment, i.e. when there are non-sparse sources. This is contrary to straight-forward dictionary learning methods that are based on the assumption of sparsity, which is not a satisfied condition in the case of low-density EEG systems. We present two different learning strategies for Cov-DL, determined by the size of the target mixing matrix. We demonstrate that Cov-DL outperforms existing overcomplete ICA algorithms under various scenarios of EEG simulations and real EEG experiments

Radio Spectra and NVSS Maps of Decametric Sources

We constructed radio spectra for ~1400 UTR-2 sources and find that 46% of them have concave curvature. Inspection of NVSS maps of 700 UTR sources suggests that half of all UTR sources are either blends of two or more sources or have an ultra-steep spectrum (USS). The fraction of compact USS sources in UTR may be near 10%. Using NVSS and the Digitized Sky Survey(s) we expect to double the UTR optical identification rate from currently ~19%.Comment: 2 pages, no figures; to appear in Proc. "Observational Cosmology with the New Radio Surveys", eds. M. Bremer, N. Jackson & I. Perez-Fournon, Kluwer Acad. Pres

A Search for Sub-millisecond Pulsations in Unidentified FIRST and NVSS Radio Sources

We have searched 92 unidentified sources from the FIRST and NVSS 1400 MHz radio survey catalogs for radio pulsations at 610 MHz. The selected radio sources are bright, have no identification with extragalactic objects, are point-like and are more than 5% linearly polarized. Our search was sensitive to sub-millisecond pulsations from pulsars with dispersion measures (DMs) less than 500 pc cm-3 in the absence of scattering. We have detected no pulsations from these sources and consider possible effects which might prevent detection. We conclude that as a population, these sources are unlikely to be pulsars.Comment: 8 pages, including 2 tables and 1 figure. Accepted for publication in A

Optical identification of XMM sources in the CFHTLS

We present optical spectroscopic identifications of X-ray sources in ~3 square degrees of the XMM-Large Scale Structure survey (XMM-LSS), also covered by the Canada France Hawaii Telescope Legacy Survey (CFHTLS), obtained with the AAOmega instrument at the Anglo Australian Telescope. In a flux limited sample of 829 point like sources in the optical band with g' <~22 mag and the 0.5-2 keV flux > 1x10^{-15}erg/cm^2/s, we observed 695 objects and obtained reliable spectroscopic identification for 489 sources, ~59% of the overall sample. We therefore increase the number of identifications in this field by a factor close to five. Galactic stellar sources represent about 15% of the total (74/489). About 55% (267/489) are broad-line Active Galactic Nuclei (AGNs) spanning redshifts between 0.15 and 3.87 with a median value of 1.68. The optical-to-X-ray spectral index of the broad-line AGNs is 1.47, typical of optically-selected Type I quasars and is found to correlate with the rest frame X-ray and optical monochromatic luminosities at 2 keV and 2500 angstroms respectively. Consistent with previous studies, we find alpha_ox not to be correlated with z. In addition, 32 and 116 X-ray sources are, respectively absorption and emission-line galaxies at z<0.76. From a line ratio diagnostic diagram it is found that in about 50% of these emission line galaxies, the emission lines are powered significantly by the AGN. Thirty of the XMM sources are detected at one or more radio frequencies. In addition, 24 sources have ambiguous identification: in 8 cases, two XMM sources have a single optical source within 6 arcsecs of each of them, whereas, 2 and 14 XMM sources have, respectively, 3 and 2 possible optical sources within 6 arcsecs of each of them.Comment: 15 pages, 14 figures, 5 tables, accepted for publication in MNRA