Dataset for the proteomic inventory and quantitative analysis of the breast cancer hypoxic secretome associated with osteotropism

The cancer secretome includes all of the macromolecules secreted by cells into their microenvironment. Cancer cell secretomes are significantly different to that of normal cells reflecting the changes that normal cells have undergone during their transition to malignancy. More importantly, cancer secretomes are known to be active mediators of both local and distant host cells and play an important role in the progression and dissemination of cancer. Here we have quantitatively profiled both the composition of breast cancer secretomes associated with osteotropism, and their modulation under normoxic and hypoxic conditions. We detect and quantify 162 secretome proteins across all conditions which show differential hypoxic induction and association with osteotropism. Mass Spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000397 and the complete proteomic, bioinformatic and biological analyses are reported in Cox et al. (2015) [1]

The impact of non-stationarities in the climate system on the definition of 'a normal wind year': a case study from the Baltic

Wind speeds over the Baltic significantly increased over the second half of the 20th century (C20th), with the majority of the increase being focused on the upper quartile of the wind speed distribution and in the southwest of the region. These changes have potentially profound implications for the wind energy resource. For example, based on the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis data it is shown that, owing to this non-stationarity, using the normalization period of 1987–98 to determine the wind resource (as in the Danish wind index) leads to overestimation of the wind energy index (and hence the wind energy resource) in western Denmark relative to 1958–2001 by approximately 10%. To address whether the increased prevalence of high wind speeds at the end of the C20th will be maintained in the future, we provide a first prognosis of annual wind indices from the HadCM3 coupled atmosphere–ocean general circulation model. The results suggest the 21st century (C21st) will be similar to the 1958–2001 period with respect to the wind energy density, but that the northeastern Baltic will exhibit slightly higher wind energy indices over the course of the C21st relative to the latter half of the C20th, whereas the southwest of the Baltic exhibits some evidence of declining wind indices towards the end of the C21st. These changes may indicate a tendency in HadCM3 towards more northerly tracking of mid-latitude cyclones in the future, possibly due to evolution of the North Atlantic oscillation. As a caveat to this finding, it should be noted that the NCEP–NCAR and European Centre for Medium-Range Weather Forecasts reanalysis data sets and HadCM3 simulations, although exhibiting commonalities during the period of overlap, differ quantitatively in terms of the spatial fields and empirical cumulative probability distributions at individual grid cells

Winds of change?: Projections of near-surface winds under climate change scenarios

Changes in near–surface wind speeds due to global climate change may have profound geophysical and societal impacts. However, Global Climate Models (GCMs) are unable to replicate the historically observed magnitude and spatial variability of wind speeds, so we apply a downscaling technique to generate probability distributions of wind speeds at sites in northern Europe for historical periods (1961–1990 and 1982–2000) and two future periods (2046–2065, 2081–2100). Projections for the twenty-first century (C21st) indicate no evidence of substantial evolution relative to the end of the twentieth century (C20th), although there is increased divergence of results from downscaling of different GCMs toward the end of C21st. Predicted changes in the downscaled mean and 90th percentile wind speeds are small (\u3c±15%) and are comparable to the current variability manifest in downscaling from different GCMs