Leptons from Dark Matter Annihilation in Milky Way Subhalos

Numerical simulations of dark matter collapse and structure formation show that in addition to a large halo surrounding the baryonic component of our galaxy, there also exists a significant number of subhalos that extend hundreds of kiloparsecs beyond the edge of the observable Milky Way. We find that for dark matter (DM) annihilation models, galactic subhalos can significantly modify the spectrum of electrons and positrons as measured at our galactic position. Using data from the recent Via Lactea II simulation we include the subhalo contribution of electrons and positrons as boundary source terms for simulations of high energy cosmic ray propagation with a modified version of the publicly available GALPROP code. Focusing on the DM DM -> 4e annihilation channel, we show that including subhalos leads to a better fit to both the Fermi and PAMELA data. The best fit gives a dark matter particle mass of 1.2 TeV, for boost factors of 90 in the main halo and 1950-3800 in the subhalos (depending on assumptions about the background), in contrast to the 0.85 TeV mass that gives the best fit in the main halo-only scenario. These fits suggest that at least a third of the observed electron cosmic rays from DM annihilation could come from subhalos, opening up the possibility of a relaxation of recent stringent constraints from inverse Compton gamma rays originating from the high-energy leptons.Comment: 8 pages, 13 figures; added referenc

Identification of Cancer Related Genes Using a Comprehensive Map of Human Gene Expression

Rapid accumulation and availability of gene expression datasets in public repositories have enabled large-scale meta-analyses of combined data. The richness of cross-experiment data has provided new biological insights, including identification of new cancer genes. In this study, we compiled a human gene expression dataset from ∼40,000 publicly available Affymetrix HG-U133Plus2 arrays. After strict quality control and data normalisation the data was quantified in an expression matrix of ∼20,000 genes and ∼28,000 samples. To enable different ways of sample grouping, existing annotations where subjected to systematic ontology assisted categorisation and manual curation. Groups like normal tissues, neoplasmic tissues, cell lines, homoeotic cells and incompletely differentiated cells were created. Unsupervised analysis of the data confirmed global structure of expression consistent with earlier analysis but with more details revealed due to increased resolution. A suitable mixed-effects linear model was used to further investigate gene expression in solid tissue tumours, and to compare these with the respective healthy solid tissues. The analysis identified 1,285 genes with systematic expression change in cancer. The list is significantly enriched with known cancer genes from large, public, peer-reviewed databases, whereas the remaining ones are proposed as new cancer gene candidates. The compiled dataset is publicly available in the ArrayExpress Archive. It contains the most diverse collection of biological samples, making it the largest systematically annotated gene expression dataset of its kind in the public domai

Blastocyst quality and reproductive and perinatal outcomes : a multinational multicentre observational study

Funding H.Z. is supported by a Monash Research Scholarship. B.W.J.M. is supported by an NHMRC Investigator grant (GNT1176437). R.W. is supported by an NHMRC Emerging Leadership Investigator grant (2009767).Peer reviewedPublisher PD