Scale dependent spatial structuring of mountain river large bed elements maximizes flow resistance

Macro-roughness elements such as boulders and bedrock outcrops, collectively referred to as large bed elements (LBEs), are key features influencing hydrodynamics and morphodynamics in mountain rivers. Where LBEs are abundant and account for a substantial portion of total flow resistance, existing geomorphic theory, previous physical experiments, and limited field observations support the theory that LBE configurations adjust to maximize flow resistance. However, methods to explicitly map individual features along entire river segments are lacking, thus limiting analysis of LBE spatial structure in boulder-bedded rivers. In addressing these gaps, this study sought to develop a procedure for mapping LBEs from 3D point-clouds, explore LBE spatial structure in a real boulder-bedded river, and test the hypothesis that LBE configurations were organized to maximize flow resistance. The mapping procedure applied a ground classification algorithm to produce a roughness surface model, from which LBEs were extracted by a marker controlled watershed algorithm. Implementing the procedure, 42,176 LBEs were mapped in 13.2-km of the mountainous Yuba River (Northern California). Scale and discharge-dependent LBE concentration and spacing metrics were quantified for multiple laterally and/or hierarchically nested spatial domains and classified to differentiate three flow-resistance based hydrodynamic regimes: isolated roughness, wake interference, and skimming flow. Of these regimes, wake interference corresponds to a state of maximum resistance, so hypothesis testing involved determining if this regime was dominant. Results confirmed 25 of 28 segment- and reach-scale LBE concentrations were in the wake interference regime. However, spacing metrics classified 24 of these same spatial domains in the skimming flow regime. Concentration metrics, which quantify LBE density in a given spatial area, differ from spacing metrics, which represent LBE proximity to one another. While comparison of segment and reach-scale regime classifications by each metric concluded concentration was superior to spacing for regime classification purposes, these disparities leave open questions about this extremal model of geomorphic adjustment. Lastly, lateral variability of metrics across the river corridor had implications for discharge-dependent resistance

Lysophosphatidate Induces Chemo-Resistance by Releasing Breast Cancer Cells from Taxol-Induced Mitotic Arrest

Taxol is a microtubule stabilizing agent that arrests cells in mitosis leading to cell death. Taxol is widely used to treat breast cancer, but resistance occurs in 25-69% of patients and it is vital to understand how Taxol resistance develops to improve chemotherapy. The effects of chemotherapeutic agents are overcome by survival signals that cancer cells receive. We focused our studies on autotaxin, which is a secreted protein that increases tumor growth, aggressiveness, angiogenesis and metastasis. We discovered that autotaxin strongly antagonizes the Taxol-induced killing of breast cancer and melanoma cells by converting the abundant extra-cellular lipid, lysophosphatidylcholine, into lysophosphatidate. This lipid stimulates specific G-protein coupled receptors that activate survival signals.In this study we determined the basis of these antagonistic actions of lysophosphatidate towards Taxol-induced G2/M arrest and cell death using cultured breast cancer cells. Lysophosphatidate does not antagonize Taxol action in MCF-7 cells by increasing Taxol metabolism or its expulsion through multi-drug resistance transporters. Lysophosphatidate does not lower the percentage of cells accumulating in G2/M by decreasing exit from S-phase or selective stimulation of cell death in G2/M. Instead, LPA had an unexpected and remarkable action in enabling MCF-7 and MDA-MB-468 cells, which had been arrested in G2/M by Taxol, to normalize spindle structure and divide, thus avoiding cell death. This action involves displacement of Taxol from the tubulin polymer fraction, which based on inhibitor studies, depends on activation of LPA receptors and phosphatidylinositol 3-kinase.This work demonstrates a previously unknown consequence of lysophosphatidate action that explains why autotaxin and lysophosphatidate protect against Taxol-induced cell death and promote resistance to the action of this important therapeutic agent

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe