Sharp interface limits of phase-field models

The use of continuum phase-field models to describe the motion of well-defined interfaces is discussed for a class of phenomena, that includes order/disorder transitions, spinodal decomposition and Ostwald ripening, dendritic growth, and the solidification of eutectic alloys. The projection operator method is used to extract the ``sharp interface limit'' from phase field models which have interfaces that are diffuse on a length scale $\xi$. In particular,phase-field equations are mapped onto sharp interface equations in the limits $\xi \kappa \ll 1$ and $\xi v/D \ll 1$, where $\kappa$ and $v$ are respectively the interface curvature and velocity and $D$ is the diffusion constant in the bulk. The calculations provide one general set of sharp interface equations that incorporate the Gibbs-Thomson condition, the Allen-Cahn equation and the Kardar-Parisi-Zhang equation.Comment: 17 pages, 9 figure

A weakly overlapping domain decomposition preconditioner for the finite element solution of elliptic partial differential equations

We present a new two-level additive Schwarz domain decomposition preconditioner which is appropriate for use in the parallel finite element solution of elliptic partial differential equations (PDEs). As with most parallel domain decomposition methods each processor may be assigned one or more subdomains, and the preconditioner is such that the processors are able to solve their own subproblem(s) concurrently. The novel feature of the technique proposed here is that it requires just a single layer of overlap in the elements which make up each subdomain at each level of refinement, and it is shown that this amount of overlap is sufficient to yield an optimal preconditioner. Some numerical experiments-posed in both two and three space dimensions-are included to confirm that the condition number when using the new preconditioner is indeed independent of the level of mesh refinement on the test problems considered

The Moment Guided Monte Carlo method for the Boltzmann equation

In this work we propose a generalization of the Moment Guided Monte Carlo method developed in [11]. This approach permits to reduce the variance of the particle methods through a matching with a set of suitable macroscopic moment equations. In order to guarantee that the moment equations provide the correct solutions, they are coupled to the kinetic equation through a non equilibrium term. Here, at the contrary to the previous work in which we considered the simplified BGK operator, we deal with the full Boltzmann operator. Moreover, we introduce an hybrid setting which permits to entirely remove the resolution of the kinetic equation in the limit of infinite number of collisions and to consider only the solution of the compressible Euler equation. This modification additionally reduce the statistical error with respect to our previous work and permits to perform simulations of non equilibrium gases using only a few number of particles. We show at the end of the paper several numerical tests which prove the efficiency and the low level of numerical noise of the method.Comment: arXiv admin note: text overlap with arXiv:0908.026

The mineralocorticoid receptor: insights into its molecular and (patho)physiological biology

The last decade has witnessed tremendous progress in the understanding of the mineralocorticoid receptor (MR), its molecular mechanism of action, and its implications for physiology and pathophysiology. After the initial cloning of MR, and identification of its gene structure and promoters, it now appears as a major actor in protein-protein interaction networks. The role of transcriptional coregulators and the determinants of mineralocorticoid selectivity have been elucidated. Targeted oncogenesis and transgenic mouse models have identified unexpected sites of MR expression and novel roles for MR in non-epithelial tissues. These experimental approaches have contributed to the generation of new cell lines for the characterization of aldosterone signaling pathways, and have also facilitated a better understanding of MR physiology in the heart, vasculature, brain and adipose tissues. This review describes the structure, molecular mechanism of action and transcriptional regulation mediated by MR, emphasizing the most recent developments at the cellular and molecular level. Finally, through insights obtained from mouse models and human disease, its role in physiology and pathophysiology will be reviewed. Future investigations of MR biology should lead to new therapeutic strategies, modulating cell-specific actions in the management of cardiovascular disease, neuroprotection, mineralocorticoid resistance, and metabolic disorders

Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve

Familial Glucocorticoid Receptor Haploinsufficiency by Non-Sense Mediated mRNA Decay, Adrenal Hyperplasia and Apparent Mineralocorticoid Excess

Primary glucocorticoid resistance (OMIM 138040) is a rare hereditary disease that causes a generalized partial insensitivity to glucocorticoid action, due to genetic alterations of the glucocorticoid receptor (GR). Investigation of adrenal incidentalomas led to the discovery of a family (eight affected individuals spanning three generations), prone to cortisol resistance, bilateral adrenal hyperplasia, arterial hypertension and hypokalemia. This phenotype exacerbated over time, cosegregates with the first heterozygous nonsense mutation p.R469[R,X] reported to date for the GR, replacing an arginine (CGA) by a stop (TGA) at amino-acid 469 in the second zinc finger of the DNA-binding domain of the receptor. In vitro, this mutation leads to a truncated 50-kDa GR lacking hormone and DNA binding capacity, devoid of hormone-dependent nuclear translocation and transactivation properties. In the proband's fibroblasts, we provided evidence for the lack of expression of the defective allele in vivo. The absence of detectable mutated GR mRNA was accompanied by a 50% reduction in wild type GR transcript and protein. This reduced GR expression leads to a significantly below-normal induction of glucocorticoid-induced target genes, FKBP5 in fibroblasts. We demonstrated that the molecular mechanisms of glucocorticoid signaling dysfunction involved GR haploinsufficiency due to the selective degradation of the mutated GR transcript through a nonsense-mediated mRNA Decay that was experimentally validated on emetine-treated propositus' fibroblasts. GR haploinsufficiency leads to hypertension due to illicit occupation of renal mineralocorticoid receptor by elevated cortisol rather than to increased mineralocorticoid production reported in primary glucocorticoid resistance. Indeed, apparent mineralocorticoid excess was demonstrated by a decrease in urinary tetrahydrocortisone-tetrahydrocortisol ratio in affected patients, revealing reduced glucocorticoid degradation by renal activity of the 11β-hydroxysteroid dehydrogenase type 2, a GR regulated gene. We propose thus that GR haploinsufficiency compromises glucocorticoid sensitivity and may represent a novel genetic cause of subclinical hypercortisolism, incidentally revealed bilateral adrenal hyperplasia and mineralocorticoid-independent hypertension

Skin Vaccination against Cervical Cancer Associated Human Papillomavirus with a Novel Micro-Projection Array in a Mouse Model

Background: Better delivery systems are needed for routinely used vaccines, to improve vaccine uptake. Many vaccines contain alum or alum based adjuvants. Here we investigate a novel dry-coated densely-packed micro-projection array skin patch (Nanopatch (TM)) as an alternate delivery system to intramuscular injection for delivering an alum adjuvanted human papillomavirus (HPV) vaccine (Gardasil (R)) commonly used as a prophylactic vaccine against cervical cancer

Joint state and parameter estimation for distributed mechanical systems

We present a novel strategy to perform estimation for a dynamical mechanical system in standard operating conditions, namely, without ad hoc experimental testing. We adopt a sequential approach, and the joint state-parameter estimation procedure is based on a state estimator inspired from collocated feedback control. This type of state estimator is chosen due to its particular effectiveness and robustness, but the methodology proposed to adequately extend state estimation to joint state-parameter estimation is general, and - indeed -applicable with any other choice of state feedback observer. The convergence of the resulting joint estimator is mathematically established. In addition, we demonstrate its effectiveness with a biomechanical test problem defined to feature the same essential characteristics as a heart model, in which we identify localized contractility and stiffness parameters using measurements of a type that is available in medical imaging

Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance.

Esophageal adenocarcinoma (EAC) has a poor outcome, and targeted therapy trials have thus far been disappointing owing to a lack of robust stratification methods. Whole-genome sequencing (WGS) analysis of 129 cases demonstrated that this is a heterogeneous cancer dominated by copy number alterations with frequent large-scale rearrangements. Co-amplification of receptor tyrosine kinases (RTKs) and/or downstream mitogenic activation is almost ubiquitous; thus tailored combination RTK inhibitor (RTKi) therapy might be required, as we demonstrate in vitro. However, mutational signatures showed three distinct molecular subtypes with potential therapeutic relevance, which we verified in an independent cohort (n = 87): (i) enrichment for BRCA signature with prevalent defects in the homologous recombination pathway; (ii) dominant T>G mutational pattern associated with a high mutational load and neoantigen burden; and (iii) C>A/T mutational pattern with evidence of an aging imprint. These subtypes could be ascertained using a clinically applicable sequencing strategy (low coverage) as a basis for therapy selection.Whole-genome sequencing of esophageal adenocarcinoma samples was performed as part of the International Cancer Genome Consortium (ICGC) through the oEsophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium and was funded by Cancer Research UK. We thank the ICGC members for their input on verification standards as part of the benchmarking exercise. We thank the Human Research Tissue Bank, which is supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, from Addenbrooke’s Hospital and UCL. Also the University Hospital of Southampton Trust and the Southampton, Birmingham, Edinburgh and UCL Experimental Cancer Medicine Centres and the QEHB charities. This study was partly funded by a project grant from Cancer Research UK. R.C.F. is funded by an NIHR Professorship and receives core funding from the Medical Research Council and infrastructure support from the Biomedical Research Centre and the Experimental Cancer Medicine Centre. We acknowledge the support of The University of Cambridge, Cancer Research UK (C14303/A17197) and Hutchison Whampoa Limited. We would like to thank Dr. Peter Van Loo for providing the NGS version of ASCAT for copy number calling. We are grateful to all the patients who provided written consent for participation in this study and the staff at all participating centres. Some of the work was undertaken at UCLH/UCL who received a proportion of funding from the Department of Health’s NIHR Biomedical Research Centres funding scheme. The work at UCLH/UCL was also supported by the CRUK UCL Early Cancer Medicine Centre.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.365