Petrogenesis of crustal wehrlites in the Oman ophiolite: Experiments and natural rocks

In the Wadi Haymiliyah of the Oman ophiolite (Haylayn block), discordant wehrlite bodies ranging in size from tens to hundreds of meters intrude the lower crust at different levels. We combined investigations on natural wehrlites from the Wadi Haymiliyah section with an experimental study on the phase relations in a wehrlitic system in order to constrain the petrogenesis of the crustal wehrlites of the Oman ophiolite. Secondary ion mass spectrometry analyses of clinopyroxenes from different wehrlite bodies imply that the clinopyroxenes were crystallized from tholeiitic, mid-ocean ridge (MORB)–type melts. The presence of primary magmatic amphiboles in some wehrlites suggests a formation under hydrous conditions. Significantly enhanced 87Sr/86Sr isotope ratios of separates from these amphiboles imply that the source of the corresponding magmatic fluids was either seawater or subduction zone–related. The experiments revealed that under wet conditions at relatively low temperatures, a MORB magma has the potential to produce wehrlite in the ocean crust by accumulation of early olivine and clinopyroxene. These show typically high Mg# which is a consequence of the oxidizing effect of the prevailing high aH2O. First plagioclases crystallizing after clinopyroxene under wet conditions are high in An content, in contrast to the corresponding dry system. Trace element compositions of clinopyroxenes of those wehrlites from the Moho transition zone are too depleted in HREE to be in equilibrium with present-day MORB, implying a genetic relation to the V2 lavas of the Oman ophiolite, which are interpreted to be the result of fluidenhanced melting of previously depleted mantle. We present a model on the petrogenesis of the crustal wehrlites in an upper mantle wedge above an initial, shallow subduction zone at the beginning of the intraoceanic thrusting

Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists

Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the diverse chemotypes present in PPIs. Here, we developed a novel pharmacophore-based interactive screening technology that builds on the role anchor residues, or deeply buried hot spots, have in PPIs, and redesigns these entry points with anchor-biased virtual multicomponent reactions, delivering tens of millions of readily synthesizable novel compounds. Application of this approach to the MDM2/p53 cancer target led to high hit rates, resulting in a large and diverse set of confirmed inhibitors, and co-crystal structures validate the designed compounds. Our unique open-access technology promises to expand chemical space and the exploration of the human interactome by leveraging in-house small-scale assays and user-friendly chemistry to rationally design ligands for PPIs with known structure. © 2012 Koes et al

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available