Although highly successful on cosmological scales, Cold Dark Matter (CDM) models predict unobserved over-dense 'cusps' in dwarf galaxies and overestimate their formation rate. We consider an ultra-light axion-like scalar boson which promises to reduce these observational discrepancies at galactic scales. The model, known as Fuzzy Dark Matter (FDM), avoids cusps, suppresses small-scale power, and delays galaxy formation via macroscopic quantum pressure. We compare the substructure and density fluctuations of galactic dark matter haloes comprised of ultra-light axions to conventional CDM results. Besides self-gravitating subhaloes, FDM includes non-virialized over-dense wavelets formed by quantum interference patterns which are an efficient source of heating to galactic discs. We find that, in the solar neighborhood, wavelet heating is sufficient to give the oldest disc stars a velocity dispersion of ∼ 30 km s −1 within a Hubble time if energy is not lost from the disc, the velocity dispersion increasing with stellar age as σ D ∝ t 0.4 in agreement with observations. Furthermore, we calculate the radius-dependent velocity dispersion and corresponding scale height caused by the heating of this dynamical substructure in both CDM and FDM with the determination that these effects will produce a flaring that terminates the Milky Way disc at 15 − 20 kpc. Although the source of thickened discs is not known, the heating due to perturbations caused by dark substructure cannot exceed the total disc velocity dispersion. Therefore, this work provides a lower bound on the FDM particle mass of m a > 0.6 × 10 −22 eV. Furthermore, FDM wavelets with this particle mass should be considered a viable mechanism for producing the observed disc thickening with time.

BackgroundSkewness is an under-utilized statistical measure that captures the degree of asymmetry in the distribution of any dataset. This study applied a new metric based on skewness to identify regulators or genes that have outlier expression in large patient cohorts.ResultsWe investigated whether specific patterns of skewed expression were related to the enrichment of biological pathways or genomic properties like DNA methylation status. Our study used publicly available datasets that were generated using both RNA-sequencing and microarray technology platforms. For comparison, the datasets selected for this study also included different samples derived from control donors and cancer patients. When comparing the shift in expression skewness between cancer and control datasets, we observed an enrichment of pathways related to the immune function that reflects an increase towards positive skewness in the cancer relative to control datasets. A significant correlation was also detected between expression skewness and the top 500 genes corresponding to the most significant differential DNA methylation occurring in the promotor regions for four Cancer Genome Atlas cancer cohorts.ConclusionsOur results indicate that expression skewness can reveal new insights into transcription based on outlier and asymmetrical behaviour in large patient cohorts.