An experimentally-validated numerical model of diffusion and speciation of water in rhyolitic silicate melt

The diffusion of water through silicate melts is a key process in volcanic systems. Diffusion controls the growth of the bubbles that drive volcanic eruptions and determines the evolution of the spatial distribution of dissolved water during and after magma mingling, crystal growth, fracturing and fragmentation, and welding of pyroclasts. Accurate models for water diffusion are therefore essential for forward modelling of eruptive behaviour, and for inverse modelling to reconstruct eruptive and post-eruptive history from the spatial distribution of water in eruptive products. Existing models do not include the kinetics of the homogeneous species reaction that interconverts molecular () and hydroxyl () water; reaction kinetics are important because final species distribution depends on cooling history. Here we develop a flexible 1D numerical model for diffusion and speciation of water in silicate melts. We validate the model against FTIR transects of the spatial distribution of molecular, hydroxyl, and total water across diffusion-couple experiments of haplogranite composition, run at 800–1200°C and 5 kbar. We adopt a stepwise approach to analysing and modelling the data. First, we use the analytical Sauer-Freise method to determine the effective diffusivity of total water as a function of dissolved water concentration and temperature for each experiment and find that the dependence of on is linear for wt.% and exponential for wt.%. Second, we develop a 1D numerical forward model, using the method of lines, to determine a piece-wise function for that is globally-minimized against the entire experimental dataset. Third, we extend this numerical model to account for speciation of water and determine globally-minimized functions for diffusivity of molecular water and the equilibrium constant for the speciation reaction. Our approach includes three key novelties: 1) functions for diffusivities of and , and the speciation reaction, are minimized simultaneously against a large experimental dataset, covering a wide range of water concentration ( wt.%) and temperature (), such that the resulting functions are both mutually-consistent and broadly applicable; 2) the minimization allows rigorous and robust analysis of uncertainties such that the accuracy of the functions is quantified; 3) the model can be straightforwardly used to determine functions for diffusivity and speciation for other melt compositions pending suitable diffusion-couple experiments. The modelling approach is suitable for both forward and inverse modelling of diffusion processes in silicate melts; the model is available as a Matlab script from the electronic supplementary material

A whole-rock data set for the Skaergaard intrusion, East Greenland

We report a compilation of new and published whole-rock major and trace element analyses for 646 samples of the Skaergaard intrusion, East Greenland. The samples were collected in 14 stratigraphic profiles either from accessible and well-exposed surface areas or from drill core, and they cover most regions of the intrusion. This includes the Layered Series, the Upper Border Series, the Marginal Border Series and the Sandwich Horizon. The geochemical data were obtained by a combination of X-ray fluorescence and inductively coupled plasma mass spectrometry. This data set can, for example, be used to constrain processes of igneous differentiation and ore formation.

Melt diffusion-moderated crystal growth and its effect on euhedral crystal shapes

Crystal growth is often described as either interface-controlled or diffusion-controlled. Here, we study crystal growth in an intermediate scenario where reaction rates at the crystal-melt interface are similar to the rates of diffusive transport of ions through the melt to the advancing crystal surface. To this end, we experimentally investigated euhedral plagioclase crystal shapes in dry mafic (basaltic) and hydrous silicic (haplodacitic) melts. Aspect ratios and inferred relative growth rates of the 3D short (S) and intermediate (I) crystal dimensions vary significantly between mafic and silicic melts, with δS:δI = 1:6 – 1:20 in basalt and 1:2.5 – 1:8 in hydrous haplodacite. The lower aspect ratios of plagioclase grown in the silicic melt coincide with 10-100x lower melt diffusion rates than in the mafic melt. Using an anisotropic growth model, we show that such differences in melt diffusivity can explain the discrepancy in plagioclase aspect ratios: if interface reaction and melt diffusion rates are of similar magnitude, then the growth of a crystal facet with high interfacial reaction rates may be limited by melt diffusion while another facet of the same crystal with lower interfacial reaction rates may grow uninhibited by melt diffusivity. This selective control of melt diffusion on crystal growth rates results in progressively more equant crystal shapes as diffusivity decreases, consistent with our experimental observations. Importantly, crystals formed in this diffusion-moderated, intermediate growth regime may not show any classical diffusion-controlled growth features. The proposed model was developed for plagioclase microlites, but should be generalisable to all anisotropic microlite growth in volcanic rocks

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy

Introduction: Tumor lymphocyte infiltration is associated with clinical response to chemotherapy in estrogen receptor (ER) negative breast cancer. To identify variants in immunosuppressive pathway genes associated with prognosis after adjuvant chemotherapy for ER-negative patients, we studied stage I-III invasive breast cancer patients of European ancestry, including 9,334 ER-positive (3,151 treated with chemotherapy) and 2,334 ER-negative patients (1,499 treated with chemotherapy). Methods: We pooled data from sixteen studies from the Breast Cancer Association Consortium (BCAC), and employed two independent studies for replications. Overall 3,610 single nucleotide polymorphisms (SNPs) in 133 genes were genotyped as part of the Collaborative Oncological Gene-environment Study, in which phenotype and clinical data were collected and harmonized. Multivariable Cox proportional hazard regression was used to assess genetic associations with overall survival (OS) and breast

Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression.

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.ajhg.2015.05.002

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

The contribution of X-linked coding variation to severe developmental disorders

Abstract: Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders