Hard X-ray standing-wave photoemission insights into the structure of an epitaxial Fe/MgO multilayer magnetic tunnel junction

The Fe/MgO magnetic tunnel junction is a classic spintronic system, with current importance technologically and interest for future innovation. The key magnetic properties are linked directly to the structure of hard-to-access buried interfaces, and the Fe and MgO components near the surface are unstable when exposed to air, making a deeper probing, nondestructive, in-situ measurement ideal for this system. We have thus applied hard X-ray photoemission spectroscopy (HXPS) and standing-wave (SW) HXPS in the few kilo-electron-volt energy range to probe the structure of an epitaxially grown MgO/Fe superlattice. The superlattice consists of 9 repeats of MgO grown on Fe by magnetron sputtering on an MgO(001) substrate, with a protective Al2O3 capping layer. We determine through SW-HXPS that 8 of the 9 repeats are similar and ordered, with a period of 33 ± 4 Å, with the minor presence of FeO at the interfaces and a significantly distorted top bilayer with ca. 3 times the oxidation of the lower layers at the top MgO/Fe interface. There is evidence of asymmetrical oxidation on the top and bottom of the Fe layers. We find agreement with dark-field scanning transmission electron microscope (STEM) and X-ray reflectivity measurements. Through the STEM measurements, we confirm an overall epitaxial stack with dislocations and warping at the interfaces of ca. 5 Å. We also note a distinct difference in the top bilayer, especially MgO, with possible Fe inclusions. We thus demonstrate that SW-HXPS can be used to probe deep buried interfaces of novel magnetic devices with few-angstrom precision

Dark Radiation and Dark Matter in Large Volume Compactifications

We argue that dark radiation is naturally generated from the decay of the overall volume modulus in the LARGE volume scenario. We consider both sequestered and non-sequestered cases, and find that the axionic superpartner of the modulus is produced by the modulus decay and it can account for the dark radiation suggested by observations, while the modulus decay through the Giudice-Masiero term gives the dominant contribution to the total decay rate. In the sequestered case, the lightest supersymmetric particles produced by the modulus decay can naturally account for the observed dark matter density. In the non-sequestered case, on the other hand, the supersymmetric particles are not produced by the modulus decay, since the soft masses are of order the heavy gravitino mass. The QCD axion will then be a plausible dark matter candidate.Comment: 27 pages, 4 figures; version 3: version published in JHE

A Primer on Regression Methods for Decoding cis-Regulatory Logic

The rapidly emerging field of systems biology is helping us to understand the molecular determinants of phenotype on a genomic scale [1]. Cis-regulatory elements are major sequence-based determinants of biological processes in cells and tissues [2]. For instance, during transcriptional regulation, transcription factors (TFs) bind to very specific regions on the promoter DNA [2,3] and recruit the basal transcriptional machinery, which ultimately initiates mRNA transcription (Figure 1A). Learning cis-Regulatory Elements from Omics Data A vast amount of work over the past decade has shown that omics data can be used to learn cis-regulatory logic on a genome-wide scale [4-6]--in particular, by integrating sequence data with mRNA expression profiles. The most popular approach has been to identify over-represented motifs in promoters of genes that are coexpressed [4,7,8]. Though widely used, such an approach can be limiting for a variety of reasons. First, the combinatorial nature of gene regulation is difficult to explicitly model in this framework. Moreover, in many applications of this approach, expression data from multiple conditions are necessary to obtain reliable predictions. This can potentially limit the use of this method to only large data sets [9]. Although these methods can be adapted to analyze mRNA expression data from a pair of biological conditions, such comparisons are often confounded by the fact that primary and secondary response genes are clustered together--whereas only the primary response genes are expected to contain the functional motifs [10]. A set of approaches based on regression has been developed to overcome the above limitations [11-32]. These approaches have their foundations in certain biophysical aspects of gene regulation [26,33-35]. That is, the models are motivated by the expected transcriptional response of genes due to the binding of TFs to their promoters. While such methods have gathered popularity in the computational domain, they remain largely obscure to the broader biology community. The purpose of this tutorial is to bridge this gap. We will focus on transcriptional regulation to introduce the concepts. However, these techniques may be applied to other regulatory processes. We will consider only eukaryotes in this tutorial

Influence of the calcium concentration in the presence of organic phosphorus on the physicochemical compatibility and stability of all-in-one admixtures for neonatal use

<p>Abstract</p> <p>Background</p> <p>Preterm infants need high amounts of calcium and phosphorus for bone mineralization, which is difficult to obtain with parenteral feeding due to the low solubility of these salts. The objective of this study was to evaluate the physicochemical compatibility of high concentrations of calcium associated with organic phosphate and its influence on the stability of AIO admixtures for neonatal use.</p> <p>Methods</p> <p>Three TPN admixture formulas were prepared in multilayered bags. The calcium content of the admixtures was adjusted to 0, 46.5 or 93 mg/100 ml in the presence of a fixed organic phosphate concentration as well as lipids, amino acids, inorganic salts, glucose, vitamins and oligoelements at pH 5.5. Each admixture was stored at 4°C, 25°C or 37°C and evaluated over a period of 7 days. The physicochemical stability parameters evaluated were visual aspect, pH, sterility, osmolality, peroxide formation, precipitation, and the size of lipid globules.</p> <p>Results</p> <p>Color alterations occurred from the first day on, and reversible lipid film formation from the third day of study for the admixtures stored at 25°C and 37°C. According to the parameters evaluated, the admixtures were stable at 4°C; and none of them presented precipitated particles due to calcium/phosphate incompatibility or lipid globules larger than 5 μm, which is the main parameter currently used to evaluate lipid emulsion stability. The admixtures maintained low peroxide levels and osmolarity was appropriate for parenteral administration.</p> <p>Conclusion</p> <p>The total calcium and calcium/phosphorus ratios studied appeared not to influence the physicochemical compatibility and stability of AIO admixtures.</p

Machine learning for regulatory analysis and transcription factor target prediction in yeast

High throughput technologies, including array-based chromatin immunoprecipitation, have rapidly increased our knowledge of transcriptional maps—the identity and location of regulatory binding sites within genomes. Still, the full identification of sites, even in lower eukaryotes, remains largely incomplete. In this paper we develop a supervised learning approach to site identification using support vector machines (SVMs) to combine 26 different data types. A comparison with the standard approach to site identification using position specific scoring matrices (PSSMs) for a set of 104 Saccharomyces cerevisiae regulators indicates that our SVM-based target classification is more sensitive (73 vs. 20%) when specificity and positive predictive value are the same. We have applied our SVM classifier for each transcriptional regulator to all promoters in the yeast genome to obtain thousands of new targets, which are currently being analyzed and refined to limit the risk of classifier over-fitting. For the purpose of illustration we discuss several results, including biochemical pathway predictions for Gcn4 and Rap1. For both transcription factors SVM predictions match well with the known biology of control mechanisms, and possible new roles for these factors are suggested, such as a function for Rap1 in regulating fermentative growth. We also examine the promoter melting temperature curves for the targets of YJR060W, and show that targets of this TF have potentially unique physical properties which distinguish them from other genes. The SVM output automatically provides the means to rank dataset features to identify important biological elements. We use this property to rank classifying k-mers, thereby reconstructing known binding sites for several TFs, and to rank expression experiments, determining the conditions under which Fhl1, the factor responsible for expression of ribosomal protein genes, is active. We can see that targets of Fhl1 are differentially expressed in the chosen conditions as compared to the expression of average and negative set genes. SVM-based classifiers provide a robust framework for analysis of regulatory networks. Processing of classifier outputs can provide high quality predictions and biological insight into functions of particular transcription factors. Future work on this method will focus on increasing the accuracy and quality of predictions using feature reduction and clustering strategies. Since predictions have been made on only 104 TFs in yeast, new classifiers will be built for the remaining 100 factors which have available binding data

Cardiovascular magnetic resonance in systemic hypertension

Systemic hypertension is a highly prevalent potentially modifiable cardiovascular risk factor. Imaging plays an important role in the diagnosis of underlying causes for hypertension, in assessing cardiovascular complications of hypertension, and in understanding the pathophysiology of the disease process. Cardiovascular magnetic resonance (CMR) provides accurate and reproducible measures of ventricular volumes, mass, function and haemodynamics as well as uniquely allowing tissue characterization of diffuse and focal fibrosis. In addition, CMR is well suited for exclusion of common secondary causes for hypertension. We review the current and emerging clinical and research applications of CMR in hypertension

Biochemistry and physiology of gastrointestinal somatostatin

Somatostatin, a tetradecapeptide initially isolated from the ovine hypothalamus, is widely distributed throughout the gastrointestinal tract where it may act as a hormone, local chemical messenger, or neurotransmitter to elicit many physiological actions. Release of somatostatin from D cells in the gut is regulated by mechanisms that are both dependent on and independent of cAMP. In most cases somatostatin acts to inhibit the function of its target cells. It performs this action in part via pertussis-toxin-sensitive inhibitory guanine nucleotide-binding proteins that regulate adenylate cyclase activity. Other mechanisms may involve sites of action distal to intracellular second messenger systems .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44411/1/10620_2005_Article_BF01536041.pd

Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy

Background The World Health Organization (WHO) Surgical Safety Checklist has fostered safe practice for 10 years, yet its place in emergency surgery has not been assessed on a global scale. The aim of this study was to evaluate reported checklist use in emergency settings and examine the relationship with perioperative mortality in patients who had emergency laparotomy. Methods In two multinational cohort studies, adults undergoing emergency laparotomy were compared with those having elective gastrointestinal surgery. Relationships between reported checklist use and mortality were determined using multivariable logistic regression and bootstrapped simulation. Results Of 12 296 patients included from 76 countries, 4843 underwent emergency laparotomy. After adjusting for patient and disease factors, checklist use before emergency laparotomy was more common in countries with a high Human Development Index (HDI) (2455 of 2741, 89.6 per cent) compared with that in countries with a middle (753 of 1242, 60.6 per cent; odds ratio (OR) 0.17, 95 per cent c.i. 0.14 to 0.21, P <0001) or low (363 of 860, 422 per cent; OR 008, 007 to 010, P <0.001) HDI. Checklist use was less common in elective surgery than for emergency laparotomy in high-HDI countries (risk difference -94 (95 per cent c.i. -11.9 to -6.9) per cent; P <0001), but the relationship was reversed in low-HDI countries (+121 (+7.0 to +173) per cent; P <0001). In multivariable models, checklist use was associated with a lower 30-day perioperative mortality (OR 0.60, 0.50 to 073; P <0.001). The greatest absolute benefit was seen for emergency surgery in low- and middle-HDI countries. Conclusion Checklist use in emergency laparotomy was associated with a significantly lower perioperative mortality rate. Checklist use in low-HDI countries was half that in high-HDI countries.Peer reviewe

Analysis of paediatric visual acuity using Bayesian copula models with sinh-arcsinh marginal densities

We analyse paediatric ophthalmic data from a large sample of children aged between 3 and 8 years. We modify the Bayesian additive conditional bivariate copula regression model of Klein and Kneib [1] by using sinh-arcsinh marginal densities with location, scale and shape parameters that depend smoothly on a covariate. We perform Bayesian inference about the unknown quantities of our model using a specially tailored Markov chain Monte Carlo algorithm. We gain new insights about the processes which determine transformations in visual acuity with respect to age, including the nature of joint changes in both eyes as modelled with the age-related copula dependence parameter. We analyse posterior predictive distributions to identify children with unusual sight characteristics, distinguishing those who are bivariate, but not univariate outliers. In this way we provide an innovative tool that enables clinicians to identify children with unusual sight who may otherwise be missed. We compare our simultaneous Bayesian method with the two-step frequentist generalized additive modelling approach of Vatter and Chavez-Demoulin [2]