Fiber Orientation Estimation Guided by a Deep Network

Diffusion magnetic resonance imaging (dMRI) is currently the only tool for noninvasively imaging the brain's white matter tracts. The fiber orientation (FO) is a key feature computed from dMRI for fiber tract reconstruction. Because the number of FOs in a voxel is usually small, dictionary-based sparse reconstruction has been used to estimate FOs with a relatively small number of diffusion gradients. However, accurate FO estimation in regions with complex FO configurations in the presence of noise can still be challenging. In this work we explore the use of a deep network for FO estimation in a dictionary-based framework and propose an algorithm named Fiber Orientation Reconstruction guided by a Deep Network (FORDN). FORDN consists of two steps. First, we use a smaller dictionary encoding coarse basis FOs to represent the diffusion signals. To estimate the mixture fractions of the dictionary atoms (and thus coarse FOs), a deep network is designed specifically for solving the sparse reconstruction problem. Here, the smaller dictionary is used to reduce the computational cost of training. Second, the coarse FOs inform the final FO estimation, where a larger dictionary encoding dense basis FOs is used and a weighted l1-norm regularized least squares problem is solved to encourage FOs that are consistent with the network output. FORDN was evaluated and compared with state-of-the-art algorithms that estimate FOs using sparse reconstruction on simulated and real dMRI data, and the results demonstrate the benefit of using a deep network for FO estimation.Comment: A shorter version is accepted by MICCAI 201

Characterization and Comparison of 2 Distinct Epidemic Community-Associated Methicillin-Resistant Staphylococcus aureus Clones of ST59 Lineage.

Sequence type (ST) 59 is an epidemic lineage of community-associated (CA) methicillin-resistant Staphylococcus aureus (MRSA) isolates. Taiwanese CA-MRSA isolates belong to ST59 and can be grouped into 2 distinct clones, a virulent Taiwan clone and a commensal Asian-Pacific clone. The Taiwan clone carries the Panton-Valentine leukocidin (PVL) genes and the staphylococcal chromosomal cassette mec (SCCmec) VT, and is frequently isolated from patients with severe disease. The Asian-Pacific clone is PVL-negative, carries SCCmec IV, and a frequent colonizer of healthy children. Isolates of both clones were characterized by their ability to adhere to respiratory A549 cells, cytotoxicity to human neutrophils, and nasal colonization of a murine and murine sepsis models. Genome variation was determined by polymerase chain reaction of selected virulence factors and by multi-strain whole genome microarray. Additionally, the expression of selected factors was compared between the 2 clones. The Taiwan clone showed a much higher cytotoxicity to the human neutrophils and caused more severe septic infections with a high mortality rate in the murine model. The clones were indistinguishable in their adhesion to A549 cells and persistence of murine nasal colonization. The microarray data revealed that the Taiwan clone had lost the ø3-prophage that integrates into the β-hemolysin gene and includes staphylokinase- and enterotoxin P-encoding genes, but had retained the genes for human immune evasion, scn and chps. Production of the virulence factors did not differ significantly in the 2 clonal groups, although more α-toxin was expressed in Taiwan clone isolates from pneumonia patients. In conclusion, the Taiwan CA-MRSA clone was distinguished by enhanced virulence in both humans and an animal infection model. The evolutionary acquisition of PVL, the higher expression of α-toxin, and possibly the loss of a large portion of the β-hemolysin-converting prophage likely contribute to its higher pathogenic potential than the Asian-Pacific clone

Gravity waves and the LHC: Towards high-scale inflation with low-energy SUSY

It has been argued that rather generic features of string-inspired inflationary theories with low-energy supersymmetry (SUSY) make it difficult to achieve inflation with a Hubble scale H > m_{3/2}, where m_{3/2} is the gravitino mass in the SUSY-breaking vacuum state. We present a class of string-inspired supergravity realizations of chaotic inflation where a simple, dynamical mechanism yields hierarchically small scales of post-inflationary supersymmetry breaking. Within these toy models we can easily achieve small ratios between m_{3/2} and the Hubble scale of inflation. This is possible because the expectation value of the superpotential relaxes from large to small values during the course of inflation. However, our toy models do not provide a reasonable fit to cosmological data if one sets the SUSY-breaking scale to m_{3/2} < TeV. Our work is a small step towards relieving the apparent tension between high-scale inflation and low-scale supersymmetry breaking in string compactifications.Comment: 21+1 pages, 5 figures, LaTeX, v2: added references, v3: very minor changes, version to appear in JHE

Resolution of the stochastic strategy spatial prisoner's dilemma by means of particle swarm optimization

We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.Comment: 12 pages, 4 figures; accepted for publication in PLoS ON

Wisdom of groups promotes cooperation in evolutionary social dilemmas

Whether or not to change strategy depends not only on the personal success of each individual, but also on the success of others. Using this as motivation, we study the evolution of cooperation in games that describe social dilemmas, where the propensity to adopt a different strategy depends both on individual fitness as well as on the strategies of neighbors. Regardless of whether the evolutionary process is governed by pairwise or group interactions, we show that plugging into the "wisdom of groups" strongly promotes cooperative behavior. The more the wider knowledge is taken into account the more the evolution of defectors is impaired. We explain this by revealing a dynamically decelerated invasion process, by means of which interfaces separating different domains remain smooth and defectors therefore become unable to efficiently invade cooperators. This in turn invigorates spatial reciprocity and establishes decentralized decision making as very beneficial for resolving social dilemmas.Comment: 8 two-column pages, 7 figures; accepted for publication in Scientific Report

Towards single particle imaging of human chromosomes at SACLA

Single particle imaging (SPI) is one of the front-page opportunities which were used to motivate the construction of the first x-ray free electron lasers (XFELs). SPI&apos;s big advantage is that it avoids radiation damage to biological samples because the diffraction takes place in femtosecond single shots before any atomic motion can take place in the sample, hence before the onset of radiation damage. This is the &apos;diffract before destruction&apos; theme, destruction being assured from the high x-ray doses used. This article reports our collaboration&apos;s first attempt at SPI using the SACLA XFEL facility in June 2015. The report is limited to experience with the instrumentation and examples of data because we have not yet had time to invert them to images.112Ysciescopu

The Bound State S-matrix of the Deformed Hubbard Chain

In this work we use the q-oscillator formalism to construct the atypical (short) supersymmetric representations of the centrally extended Uq (su(2|2)) algebra. We then determine the S-matrix describing the scattering of arbitrary bound states. The crucial ingredient in this derivation is the affine extension of the aforementioned algebra.Comment: 44 pages, 3 figures. v2: minor correction

Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.

BackgroundTo determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed.MethodsTen CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system.ResultsAn average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q &lt; 0.05, fold change &gt;2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). Skipped exon was the most frequent splicing alteration in CLL specimens with 128 significant events (P-value &lt;0.05, minimum inclusion level difference &gt;0.1).ConclusionThe RNA-seq analysis of CLL specimens identifies novel DEG and alternatively spliced genes that are potential prognostic markers and therapeutic targets. High level of validation by qRT-PCR for a number of DEG genes supports the accuracy of this analysis. Global comparison of transcriptomes of B cells, IGVH non-mutated CLL (U-CLL) and mutated CLL specimens (M-CLL) with multidimensional scaling analysis was able to segregate CLL and B cell transcriptomes but the M-CLL and U-CLL transcriptomes were indistinguishable. The analysis of HTS RNA-seq data to identify alternative splicing events and other genetic abnormalities specific to CLL is an added advantage of RNA-seq that is not feasible with other genome wide analysis

Identification of a cytokine network sustaining neutrophil and Th17 activation in untreated early rheumatoid arthritis

© 2010 Cascão et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease characterized by sustained synovitis. Recently, several studies have proposed neutrophils and Th17 cells as key players in the onset and perpetuation of this disease. The main goal of this work was to determine whether cytokines driving neutrophil and Th17 activation are dysregulated in very early rheumatoid arthritis patients with less than 6 weeks of disease duration and before treatment (VERA). Methods: Cytokines related to neutrophil and Th17 activation were quantified in the serum of VERA and established RA patients and compared with other very early arthritis (VEA) and healthy controls. Synovial fluid (SF) from RA and osteoarthritis (OA) patients was also analyzed. Results: VERA patients had increased serum levels of cytokines promoting Th17 polarization (IL-1b and IL-6), as well as IL-8 and Th17-derived cytokines (IL-17A and IL-22) known to induce neutrophil-mediated inflammation. In established RA this pattern is more evident within the SF. Early treatment with methotrexate or corticosteroids led to clinical improvement but without an impact on the cytokine pattern. Conclusions: VERA patients already display increased levels of cytokines related with Th17 polarization and neutrophil recruitment and activation, a dysregulation also found in SF of established RA. 0 Thus, our data suggest that a cytokine-milieu favoring Th17 and neutrophil activity is an early event in RA pathogenesis.This work was supported by a grant from Sociedade Portuguesa de Reumatologia/Schering-Plough 2005. RAM and RC were funded by Fundação para a Ciência e a Tecnologia (FCT) SFRH/BD/30247/2006 and SFRH/BD/40513/2007, respectively. MMS-C was funded by Marie Curie Intra-European Fellowship PERG-2008-239422 and a EULAR Young Investigator Award