Diffuse glioma growth: a guerilla war

In contrast to almost all other brain tumors, diffuse gliomas infiltrate extensively in the neuropil. This growth pattern is a major factor in therapeutic failure. Diffuse infiltrative glioma cells show some similarities with guerilla warriors. Histopathologically, the tumor cells tend to invade individually or in small groups in between the dense network of neuronal and glial cell processes. Meanwhile, in large areas of diffuse gliomas the tumor cells abuse pre-existent “supply lines” for oxygen and nutrients rather than constructing their own. Radiological visualization of the invasive front of diffuse gliomas is difficult. Although the knowledge about migration of (tumor)cells is rapidly increasing, the exact molecular mechanisms underlying infiltration of glioma cells in the neuropil have not yet been elucidated. As the efficacy of conventional methods to fight diffuse infiltrative glioma cells is limited, a more targeted (“search & destroy”) tactic may be needed for these tumors. Hopefully, the study of original human glioma tissue and of genotypically and phenotypically relevant glioma models will soon provide information about the Achilles heel of diffuse infiltrative glioma cells that can be used for more effective therapeutic strategies

LiDAR-derived snowpack data sets from mixed conifer forests across the Western United States

Airborne-based Light Detection and Ranging (LiDAR) offers the potential to measure snow depth and vegetation structure at high spatial resolution over large extents and thereby increase our ability to quantify snow water resources. Here we present airborne LiDAR data products at four Critical Zone Observatories (CZO) in the Western United States: Jemez River Basin, NM, Boulder Creek Watershed, CO, Kings River Experimental Watershed, CA, and Wolverton Basin, CA. We make publicly available snow depth data products (1 m2 resolution) derived from LiDAR with an estimated accuracy of <30 cm compared to limited in situ snow depth observations. © 2014. American Geophysical Union. All Rights Reserved

LiDAR-derived snowpack data sets from mixed conifer forests across the Western United States

Airborne-based Light Detection and Ranging (LiDAR) offers the potential to measure snow depth and vegetation structure at high spatial resolution over large extents and thereby increase our ability to quantify snow water resources. Here we present airborne LiDAR data products at four Critical Zone Observatories (CZO) in the Western United States: Jemez River Basin, NM, Boulder Creek Watershed, CO, Kings River Experimental Watershed, CA, and Wolverton Basin, CA. We make publicly available snow depth data products (1 m2 resolution) derived from LiDAR with an estimated accuracy of <30 cm compared to limited in situ snow depth observations. © 2014. American Geophysical Union. All Rights Reserved

Spatial variation of the rain–snow temperature threshold across the Northern Hemisphere

Land surface models often use a spatially uniform air temperature threshold when partitioning rain and snow. Here Jennings et al. show that the threshold varies significantly across the Northern Hemisphere and that threshold selection is a large source of uncertainty in snowfall simulations