Preclinical translation of exosomes derived from mesenchymal stem/stromal cells.

Exosomes are nanovesicles secreted by virtually all cells. Exosomes mediate the horizontal transfer of various macromolecules previously believed to be cell-autonomous in nature, including nonsecretory proteins, various classes of RNA, metabolites, and lipid membrane-associated factors. Exosomes derived from mesenchymal stem/stromal cells (MSCs) appear to be particularly beneficial for enhancing recovery in various models of disease. To date, there have been more than 200 preclinical studies of exosome-based therapies in a number of different animal models. Despite a growing number of studies reporting the therapeutic properties of MSC-derived exosomes, their underlying mechanism of action, pharmacokinetics, and scalable manufacturing remain largely outstanding questions. Here, we review the global trends associated with preclinical development of MSC-derived exosome-based therapies, including immunogenicity, source of exosomes, isolation methods, biodistribution, and disease categories tested to date. Although the in vivo data assessing the therapeutic properties of MSC-exosomes published to date are promising, several outstanding questions remain to be answered that warrant further preclinical investigation

An Optimal-Dimensionality Sampling for Spin-ss Functions on the Sphere

For the representation of spin-$s$ band-limited functions on the sphere, we propose a sampling scheme with optimal number of samples equal to the number of degrees of freedom of the function in harmonic space. In comparison to the existing sampling designs, which require ${\sim}2L^2$ samples for the representation of spin-$s$ functions band-limited at $L$, the proposed scheme requires $N_o=L^2-s^2$ samples for the accurate computation of the spin-$s$ spherical harmonic transform~($s$-SHT). For the proposed sampling scheme, we also develop a method to compute the $s$-SHT. We place the samples in our design scheme such that the matrices involved in the computation of $s$-SHT are well-conditioned. We also present a multi-pass $s$-SHT to improve the accuracy of the transform. We also show the proposed sampling design exhibits superior geometrical properties compared to existing equiangular and Gauss-Legendre sampling schemes, and enables accurate computation of the $s$-SHT corroborated through numerical experiments.Comment: 5 pages, 2 figure

Iterative Residual Fitting for Spherical Harmonic Transform of Band-Limited Signals on the Sphere: Generalization and Analysis

We present the generalized iterative residual fitting (IRF) for the computation of the spherical harmonic transform (SHT) of band-limited signals on the sphere. The proposed method is based on the partitioning of the subspace of band-limited signals into orthogonal subspaces. There exist sampling schemes on the sphere which support accurate computation of SHT. However, there are applications where samples~(or measurements) are not taken over the predefined grid due to nature of the signal and/or acquisition set-up. To support such applications, the proposed IRF method enables accurate computation of SHTs of signals with randomly distributed sufficient number of samples. In order to improve the accuracy of the computation of the SHT, we also present the so-called multi-pass IRF which adds multiple iterative passes to the IRF. We analyse the multi-pass IRF for different sampling schemes and for different size partitions. Furthermore, we conduct numerical experiments to illustrate that the multi-pass IRF allows sufficiently accurate computation of SHTs.Comment: 5 Pages, 7 Figure

Recovering the state sequence of hidden Markov models using mean-field approximations

Inferring the sequence of states from observations is one of the most fundamental problems in Hidden Markov Models. In statistical physics language, this problem is equivalent to computing the marginals of a one-dimensional model with a random external field. While this task can be accomplished through transfer matrix methods, it becomes quickly intractable when the underlying state space is large. This paper develops several low-complexity approximate algorithms to address this inference problem when the state space becomes large. The new algorithms are based on various mean-field approximations of the transfer matrix. Their performances are studied in detail on a simple realistic model for DNA pyrosequencing.Comment: 43 pages, 41 figure

On the Energy Spectra of GeV/TeV Cosmic Ray Leptons

Recent observations of cosmic ray electrons from several instruments have revealed various degrees of deviation in the measured electron energy distribution from a simple power-law, in a form of an excess around TeV energies. An even more prominent deviation has been observed in the fraction of cosmic ray positrons around 100 GeV energies. In this paper we show that the observed excesses in the electron spectrum may be easily re-produced without invoking any unusual sources other than the general diffuse Galactic components of cosmic rays. The primary physical effect involved is the Klein-Nishina suppression of the electron cooling rate around TeV energies. With a very reasonable choice of the model parameters characterizing the local interstellar medium, we can reproduce the most recent observations by Fermi and HESS experiments. We also find that high positron fraction increasing with energy, as claimed by the PAMELA experiment, cannot be explained in our model with the conservative set of the model parameters. We are able, however, to reproduce the PAMELA results assuming high values of the starlight and interstellar gas densities, which would be more appropriate for vicinities of supernova remnants. A possible solution to this problem may be that cosmic rays undergo most of their interactions near their sources due to the efficient trapping in the far upstream of supernova shocks by self-generated, cosmic ray-driven turbulence.Comment: 31 pages, accepted for publication in ApJ (abstract abridged for arXiv

The detection of sub-solar mass dark matter halos

Dark matter halos of sub-solar mass are the first bound objects to form in cold dark matter theories. In this article, I discuss the present understanding of "microhalos'', their role in structure formation, and the implications of their potential presence, in the interpretation of dark matter experiments.Comment: 18 pages, 7 figures. Invited contribution to NJP Focus Issue on "Dark Matter and Particle Physics

Alleviating the new user problem in collaborative filtering by exploiting personality information

The final publication is available at Springer via http://dx.doi.org/10.1007/s11257-016-9172-zThe new user problem in recommender systems is still challenging, and there is not yet a unique solution that can be applied in any domain or situation. In this paper we analyze viable solutions to the new user problem in collaborative filtering (CF) that are based on the exploitation of user personality information: (a) personality-based CF, which directly improves the recommendation prediction model by incorporating user personality information, (b) personality-based active learning, which utilizes personality information for identifying additional useful preference data in the target recommendation domain to be elicited from the user, and (c) personality-based cross-domain recommendation, which exploits personality information to better use user preference data from auxiliary domains which can be used to compensate the lack of user preference data in the target domain. We benchmark the effectiveness of these methods on large datasets that span several domains, namely movies, music and books. Our results show that personality-aware methods achieve performance improvements that range from 6 to 94 % for users completely new to the system, while increasing the novelty of the recommended items by 3-40 % with respect to the non-personalized popularity baseline. We also discuss the limitations of our approach and the situations in which the proposed methods can be better applied, hence providing guidelines for researchers and practitioners in the field.This work was supported by the Spanish Ministry of Economy and Competitiveness (TIN2013-47090-C3). We thank Michal Kosinski and David Stillwell for their attention regarding the dataset

How to combine visual features with tags to improve movie recommendation accuracy?

Previous works have shown the effectiveness of using stylistic visual features, indicative of the movie style, in content-based movie recommendation. However, they have mainly focused on a particular recommendation scenario, i.e., when a new movie is added to the catalogue and no information is available for that movie (New Item scenario). However, the stylistic visual features can be also used when other sources of information is available (Existing Item scenario). In this work, we address the second scenario and propose a hybrid technique that exploits not only the typical content available for the movies (e.g., tags), but also the stylistic visual content extracted form the movie files and fuse them by applying a fusion method called Canonical Correlation Analysis (CCA). Our experiments on a large catalogue of 13K movies have shown very promising results which indicates a considerable improvement of the recommendation quality by using a proper fusion of the stylistic visual features with other type of features

Future and advances in endoscopy

The future of endoscopy will be dictated by rapid technological advances in the development of light sources, optical fibers, and miniature scanners that will allow for images to be collected in multiple spectral regimes, with greater tissue penetration, and in three dimensions. These engineering breakthroughs will be integrated with novel molecular probes that are highly specific for unique proteins to target diseased tissues. Applications include early cancer detection by imaging molecular changes that occur before gross morphological abnormalities, personalized medicine by visualizing molecular targets specific to individual patients, and image guided therapy by localizing tumor margins and monitoring for recurrence. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87084/1/471_ftp.pd

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL