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

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

Grain growth competition during melt pool solidification -- Comparing phase-field and cellular automaton models

A broad range of computational models have been proposed to predict microstructure development during solidification processing but they have seldom been compared to each other on a quantitative and systematic basis. In this paper, we compare phase-field (PF) and cellular automaton (CA) simulations of polycrystalline growth in a two-dimensional melt pool under conditions relevant to additive manufacturing (powder-bed fusion). We compare the resulting grain structures using local (point-by-point) measurements, as well as averaged grain orientation distributions over several simulations. We explore the effect of the CA spatial discretization level and that of the melt pool aspect ratio upon the selected grain texture. Our simulations show that detailed microscopic features related to transient growth conditions and solid-liquid interface stability (e.g. the initial planar growth stage prior to its cellular/dendritic destabilization, or the early elimination of unfavorably oriented grains due to neighbor grain sidebranching) can only be captured by PF simulations. The resulting disagreement between PF and CA predictions can only be addressed partially by a refinement of the CA grid. However, overall grain distributions averaged over the entire melt pools of several simulations seem to lead to a notably better agreement between PF and CA, with some variability with the melt pool shape and CA grid. While further research remains required, in particular to identify the appropriate selection of CA spatial discretization and its link to characteristic microstructural length scales, this research provides a useful step forward in this direction by comparing both methods quantitatively at process-relevant length and time scales

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

Development and characterization of a murine hepatoma model expressing hepatitis Cvirus (HCV) non-structural antigens for evaluating HCV vaccines

Hepatitis C (HCV) is a highly prevalent blood-borne virus with infection of 2-3% of world population and high rate of chronicity (\u3e70%) leading to chronic hepatitis, which often progress to cirrhosis and hepatocellular carcinoma. HCV- specific immune responses consisting of CD4 and CD8 T cells and virus neutralizing antibodies have been shown to eliminate HCV infections in humans and chimpanzees. Therefore, vaccines that can induce potent and durable anti-HCV T and B cell responses may have the potential to clear chronic HCV infections. A number of HCV vaccines have been tested clinically with limited success. One of the major limitations in developing effective HCV therapies is the lack of effective and reliable animal models due to the narrow host range of the HCV virus. The study described herein reports the generation of a murine hepatoma cell line expressing HCV non-structural proteins and its use in a metastatic tumor setting to test anti-tumor efficacy of bacterial and viral vector vaccines expressing the HCV non-structural genes. HCV-recombinant hepatoma cells formed large solid-mass tumors when implanted into syngeneic mice, allowing the testing of HCV vaccines for immunogenicity and anti-tumor efficacy. Using this model, we tested the therapeutic potential of recombinant anti-HCV-specific vaccines based on two fundamentally different attenuated pathogen vaccine systems - attenuated Salmonella and recombinant adenoviral vector based vaccine. Attenuated Salmonella secreting HCV antigens limited growth of the HCV-recombinant tumors when used in a therapeutic vaccination setting. The inhibition of tumor growth by Salmonella vector-based vaccines was significantly reduced in mice co-injected with an anti-CD8 antibody, suggesting a role by CD8+ cells in the vaccine efficacy. The model was also used to compare replication deficient and replication-competent but non-infectious adenoviral vectors expressing non-structural HCV antigens. Results showed overall greater survival and reduced weight loss with the replication-competent vector compared to the non-replicating vector. Our results demonstrate the novel recombinant murine hepatoma model expressing HCV non-structural antigens as a useful model for evaluating therapeutic vaccines against HCV. Vaccines that are capable of inducing potent anti-HCV immune responses that are capable of controlling aggressive and metastatic tumor growth in this model would likely have the potential to control chronic viral infections such as HCV. This novel approach is particularly interesting for the development of therapeutic vaccines

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

Sleep disturbances and the at risk mental state : a systematic review and meta-analysis

Aims: To synthesise and investigate how sleep disturbances relate to psychotic symptoms, functioning and Quality of Life (QoL) in At Risk Mental State (ARMS) youth. Method: A comprehensive search of six databases (MEDLINE, PsycINFO, Embase, CINAHL, Web of Science and CENTRAL) was conducted. Eligible studies provided data on sleep disturbances or disorders in ARMS patients. Results: Sixteen studies met the inclusion criteria (n=1962 ARMS patients) including 7 cross-sectional studies, 2 RCT’s and 7 cohort studies.Narrative synthesis revealed that self-reported sleep (e.g., general disturbances, fragmented night time sleep and nightmares) was poorer among ARMS patients compared to healthy controls. In the limited studies (n=4) including objective measurements of sleep disturbances, ARMS patients experienced higher levels of movement during sleep, more daytime naps and increased sleep latency compared to controls. Furthermore, sleep disturbances were associated with attenuated psychotic symptoms and functional outcomes cross-sectionally and longitudinally. Only one study investigated the relationship between sleep and QoL. The exploratory meta-analysis revealed a significant difference in self-reported sleep disturbances measured by the PSQI (mean difference in score: 3.30 (95% CI 1.87, 4.74), p<0.00001) and SIPS (mean difference in score: 1.58 (95% CI 0.80, 2.35), p<0.00001) of ARMS patients compared to control groups. Conclusions: ARMS individuals report impaired sleep quality and reduced sleep quantity compared to healthy controls. However, further research is needed to explore the longitudinal relationship between sleep disruptions and QoL in early psychosis. Significant variations in how sleep is measured across studies highlights a need to assess disturbances to sleep using robust and consistent approaches in this patient group