Annihilation vs. Decay: Constraining dark matter properties from a gamma-ray detection

Most proposed dark matter candidates are stable and are produced thermally in the early Universe. However, there is also the possibility of unstable (but long-lived) dark matter, produced thermally or otherwise. We propose a strategy to distinguish between dark matter annihilation and/or decay in the case that a clear signal is detected in gamma-ray observations of Milky Way dwarf spheroidal galaxies with gamma-ray experiments. The sole measurement of the energy spectrum of an indirect signal would render the discrimination between these cases impossible. We show that by examining the dependence of the intensity and energy spectrum on the angular distribution of the emission, the origin could be identified as decay, annihilation, or both. In addition, once the type of signal is established, we show how these measurements could help to extract information about the dark matter properties, including mass, annihilation cross section, lifetime, dominant annihilation and decay channels, and the presence of substructure. Although an application of the approach presented here would likely be feasible with current experiments only for very optimistic dark matter scenarios, the improved sensitivity of upcoming experiments could enable this technique to be used to study a wider range of dark matter models.Comment: 29 pp, 8 figs; replaced to match published version (minor changes and some new references

An integrated multi-omic analysis of iPSC-derived motor neurons from C9ORF72 ALS patients

Neurodegenerative diseases are challenging for systems biology because of the lack of reliable animal models or patient samples at early disease stages. Induced pluripotent stem cells (iPSCs) could address these challenges. We investigated DNA, RNA, epigenetics, and proteins in iPSC-derived motor neurons from patients with ALS carrying hexanucleotide expansions in C9ORF72. Using integrative computational methods combining all omics datasets, we identified novel and known dysregulated pathways. We used a C9ORF72 Drosophila model to distinguish pathways contributing to disease phenotypes from compensatory ones and confirmed alterations in some pathways in postmortem spinal cord tissue of patients with ALS. A different differentiation protocol was used to derive a separate set of C9ORF72 and control motor neurons. Many individual -omics differed by protocol, but some core dysregulated pathways were consistent. This strategy of analyzing patient-specific neurons provides disease-related outcomes with small numbers of heterogeneous lines and reduces variation from single-omics to elucidate network-based signatures.Genetics of disease, diagnosis and treatmen

The Diversity and Causality of Welfare State Reforms Explored with Fuzzy-Sets

comparative methodology, fuzzy-sets, welfare state reforms, social expenditures, socio-economic performance,