Scalable Group Level Probabilistic Sparse Factor Analysis

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex noise models than the presently considered.Comment: 10 pages plus 5 pages appendix, Submitted to ICASSP 1

The type Ib supernova 2010O: an explosion in a Wolf-Rayet X-ray binary?

The type Ib supernova 2010O was recently discovered in the interacting starburst galaxy Arp 299. We present an analysis of two archival Chandra X-ray observations of Arp 299, taken before the explosion and show that there is a transient X-ray source at a position consistent with the supernova. Due to the diffuse emission, the background is difficult to estimate. We estimate the flux of the transient from the difference of the two X-ray images and conclude that the transient can be described by a 0.225 keV black body with a luminosity of 2.5+/-0.7 10^{39} erg/s for a distance of 41 Mpc. These properties put the transient in between the Galactic black hole binary XTE J1550-564 and the ultra-luminous X-ray binaries NGC 1313 X-1 and X-2. The high level of X-ray variability associated with the active starburst makes it impossible to rule out a chance alignment. If the source is associated with the supernova, it suggests SN2010O is the explosion of the second star in a Wolf-Rayet X-ray binary, such as Cyg X-3, IC 10 X-1 and NGC 300 X-1.Comment: Accepted version. To appear in MNRAS

Domain Walls and the Creation of Strings

The phenomenon of creation of strings, occurring when particles pass through a domain wall and related to the Hanany-Witten effect via dualities, is discussed in ten and nine dimensions. We consider both the particle actions in massive backgrounds as well as the 1/4-supersymmetric particle-string-domain wall supergravity solutions and discuss their physical interpretation. In 10D we discuss the D0-F1-D8 system in massive IIA theory while in 9D the SL(2,R)-generalisation is constructed. It consists of (p,q)-particles, (r,s)-strings and the double domain wall solution of the three different 9D gauged supergravities where a subgroup of SL(2,R) is gauged.Comment: v1: 22 pages, 3 figures. v2: footnote and reference adde

Spinning particles in the vacuum C metric

The motion of a spinning test particle given by the Mathisson-Papapetrou equations is studied on an exterior vacuum C metric background spacetime describing the accelerated motion of a spherically symmetric gravitational source. We consider circular orbits of the particle around the direction of acceleration of the source. The symmetries of this configuration lead to the reduction of the differential equations of motion to algebraic relations. The spin supplementary conditions as well as the coupling between the spin of the particle and the acceleration of the source are discussed.Comment: IOP macros used, eps figures n.

Attempting to distinguish between endogenous and contaminating cytokeratins in a corneal proteomic study

<p>Abstract</p> <p>Background</p> <p>The observation of cytokeratins (CK's) in mass spectrometry based studies raises the question of whether the identified CK is a true endogenous protein from the sample or simply represents a contaminant. This issue is especially important in proteomic studies of the corneal epithelium where several CK's have previously been reported to mark the stages of differentiation from corneal epithelial stem cell to the differentiated cell.</p> <p>Methods</p> <p>Here we describe a method to distinguish very likely endogenous from uncertain endogenous CK's in a mass spectrometry based proteomic study. In this study the CK identifications from 102 human corneal samples were compared with the number of human CK identifications found in 102 murine thymic lymphoma samples.</p> <p>Results</p> <p>It was anticipated that the CK's that were identified with a frequency of <5%, <it>i.e. </it>in less than one spot for every 20 spots analysed, are very likely to be endogenous and thereby represent a 'biologically significant' identification. CK's observed with a frequency >5% are uncertain endogenous since they may represent true endogenous CK's but the probability of contamination is high and therefore needs careful consideration. This was confirmed by comparison with a study of mouse samples where all identified human CK's are contaminants.</p> <p>Conclusions</p> <p>CK's 3, 4, 7, 8, 11, 12, 13, 15, 17, 18, 19, 20 and 23 are very likely to be endogenous proteins if identified in a corneal study, whilst CK's 1, 2e, 5, 6A, 9, 10, 14 and 16 may be endogenous although some are likely to be contaminants in a proteomic study. Further immunohistochemical analysis and a search of the current literature largely supported the distinction.</p

NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence

Binding of peptides to Major Histocompatibility Complex (MHC) molecules is the single most selective step in the recognition of pathogens by the cellular immune system. The human MHC class I system (HLA-I) is extremely polymorphic. The number of registered HLA-I molecules has now surpassed 1500. Characterizing the specificity of each separately would be a major undertaking.Here, we have drawn on a large database of known peptide-HLA-I interactions to develop a bioinformatics method, which takes both peptide and HLA sequence information into account, and generates quantitative predictions of the affinity of any peptide-HLA-I interaction. Prospective experimental validation of peptides predicted to bind to previously untested HLA-I molecules, cross-validation, and retrospective prediction of known HIV immune epitopes and endogenous presented peptides, all successfully validate this method. We further demonstrate that the method can be applied to perform a clustering analysis of MHC specificities and suggest using this clustering to select particularly informative novel MHC molecules for future biochemical and functional analysis.Encompassing all HLA molecules, this high-throughput computational method lends itself to epitope searches that are not only genome- and pathogen-wide, but also HLA-wide. Thus, it offers a truly global analysis of immune responses supporting rational development of vaccines and immunotherapy. It also promises to provide new basic insights into HLA structure-function relationships. The method is available at http://www.cbs.dtu.dk/services/NetMHCpan

HLA Class I Binding 9mer Peptides from Influenza A Virus Induce CD4+ T Cell Responses

BACKGROUND: Identification of human leukocyte antigen class I (HLA-I) restricted cytotoxic T cell (CTL) epitopes from influenza virus is of importance for the development of new effective peptide-based vaccines. METHODOLOGY/PRINCIPAL FINDINGS: In the present work, bioinformatics was used to predict 9mer peptides derived from available influenza A viral proteins with binding affinity for at least one of the 12 HLA-I supertypes. The predicted peptides were then selected in a way that ensured maximal coverage of the available influenza A strains. One hundred and thirty one peptides were synthesized and their binding affinities for the HLA-I supertypes were measured in a biochemical assay. Influenza-specific T cell responses towards the peptides were quantified using IFNgamma ELISPOT assays with peripheral blood mononuclear cells (PBMC) from adult healthy HLA-I typed donors as responder cells. Of the 131 peptides, 21 were found to induce T cell responses in 19 donors. In the ELISPOT assay, five peptides induced responses that could be totally blocked by the pan-specific anti-HLA-I antibody W6/32, whereas 15 peptides induced responses that could be completely blocked in the presence of the pan-specific anti-HLA class II (HLA-II) antibody IVA12. Blocking of HLA-II subtype reactivity revealed that 8 and 6 peptide responses were blocked by anti-HLA-DR and -DP antibodies, respectively. Peptide reactivity of PBMC depleted of CD4(+) or CD8(+) T cells prior to the ELISPOT culture revealed that effectors are either CD4(+) (the majority of reactivities) or CD8(+) T cells, never a mixture of these subsets. Three of the peptides, recognized by CD4(+) T cells showed binding to recombinant DRA1*0101/DRB1*0401 or DRA1*0101/DRB5*0101 molecules in a recently developed biochemical assay. CONCLUSIONS/SIGNIFICANCE: HLA-I binding 9mer influenza virus-derived peptides induce in many cases CD4(+) T cell responses restricted by HLA-II molecules