Mergers of close primordial binaries

We study the production of main sequence mergers of tidally-synchronized primordial short-period binaries. The principal ingredients of our calculation are the angular momentum loss rates inferred from the spindown of open cluster stars and the distribution of binary properties in young open clusters. We compare our results with the expected number of systems that experience mass transfer in post-main sequence phases of evolution and compute the uncertainties in the theoretical predictions. We estimate that main-sequence mergers can account for the observed number of single blue stragglers in M67. Applied to the blue straggler population, this implies that such mergers are responsible for about one quarter of the population of halo blue metal poor stars, and at least one third of the blue stragglers in open clusters for systems older than 1 Gyr. The observed trends as a function of age are consistent with a saturated angular momentum loss rate for rapidly rotating tidally synchronized systems. The predicted number of blue stragglers from main sequence mergers alone is comparable to the number observed in globular clusters, indicating that the net effect of dynamical interactions in dense stellar environments is to reduce rather than increase the blue straggler population. A population of subturnoff mergers of order 3-4% of the upper main sequence population is also predicted for stars older than 4 Gyr, which is roughly comparable to the small population of highly Li-depleted halo dwarfs. Other observational tests are discussed.Comment: number of pages depends on font, margins, columns etc (58 with given format), 14 figures, submitted to the Astrophysical Journa

Vygotsky in English: What Still Needs to Be Done

At present readers of English have still limited access to Vygotsky’s writings. Existing translations are marred by mistakes and outright falsifications. Analyses of Vygotsky’s work tend to downplay the collaborative and experimental nature of his research. Several suggestions are made to improve this situation. New translations are certainly needed and new analyses should pay attention to the contextual nature of Vygotsky’s thinking and research practice

The GOAL study: a prospective examination of the impact of factor V Leiden and ABO(H) blood groups on haemorrhagic and thrombotic pregnancy outcomes

Factor V Leiden (FVL) and ABO(H) blood groups are the common influences on haemostasis and retrospective studies have linked FVL with pregnancy complications. However, only one sizeable prospective examination has taken place. As a result, neither the impact of FVL in unselected subjects, any interaction with ABO(H) in pregnancy, nor the utility of screening for FVL is defined. A prospective study of 4250 unselected pregnancies was carried out. A venous thromboembolism (VTE) rate of 1·23/1000 was observed, but no significant association between FVL and pre-eclampsia, intra-uterine growth restriction or pregnancy loss was seen. No influence of FVL and/or ABO(H) on ante-natal bleeding or intra-partum or postpartum haemorrhage was observed. However, FVL was associated with birth-weights >90th centile [odds ratio (OR) 1·81; 95% confidence interval (CI<sub>95</sub>) 1·04–3·31] and neonatal death (OR 14·79; CI<sub>95</sub> 2·71–80·74). No association with ABO(H) alone, or any interaction between ABO(H) and FVL was observed. We neither confirmed the protective effect of FVL on pregnancy-related blood loss reported in previous smaller studies, nor did we find the increased risk of some vascular complications reported in retrospective studies

Physical Orbit for Lambda Virginis and a Test of Stellar Evolution Models

Lambda Virginis (LamVir) is a well-known double-lined spectroscopic Am binary with the interesting property that both stars are very similar in abundance but one is sharp-lined and the other is broad-lined. We present combined interferometric and spectroscopic studies of LamVir. The small scale of the LamVir orbit (~20 mas) is well resolved by the Infrared Optical Telescope Array (IOTA), allowing us to determine its elements as well as the physical properties of the components to high accuracy. The masses of the two stars are determined to be 1.897 Msun and 1.721 Msun, with 0.7% and 1.5% errors respectively, and the two stars are found to have the same temperature of 8280 +/- 200 K. The accurately determined properties of LamVir allow comparisons between observations and current stellar evolution models, and reasonable matches are found. The best-fit stellar model gives LamVir a subsolar metallicity of Z=0.0097, and an age of 935 Myr. The orbital and physical parameters of LamVir also allow us to study its tidal evolution time scales and status. Although currently atomic diffusion is considered to be the most plausible cause of the Am phenomenon, the issue is still being actively debated in the literature. With the present study of the properties and evolutionary status of LamVir, this system is an ideal candidate for further detailed abundance analyses that might shed more light on the source of the chemical anomalies in these A stars.Comment: 43 Pages, 13 figures. Accepted for publication in Ap

A Consistency Test of Spectroscopic Gravities for Late-Type Stars

Chemical analyses of late-type stars are usually carried out following the classical recipe: LTE line formation and homogeneous, plane-parallel, flux-constant, and LTE model atmospheres. We review different results in the literature that have suggested significant inconsistencies in the spectroscopic analyses, pointing out the difficulties in deriving independent estimates of the stellar fundamental parameters and hence,detecting systematic errors. The trigonometric parallaxes measured by the HIPPARCOS mission provide accurate appraisals of the stellar surface gravity for nearby stars, which are used here to check the gravities obtained from the photospheric iron ionization balance. We find an approximate agreement for stars in the metallicity range -1 <= [Fe/H] <= 0, but the comparison shows that the differences between the spectroscopic and trigonometric gravities decrease towards lower metallicities for more metal-deficient dwarfs (-2.5 <= [Fe/H] <= -1.0), which casts a shadow upon the abundance analyses for extreme metal-poor stars that make use of the ionization equilibrium to constrain the gravity. The comparison with the strong-line gravities derived by Edvardsson (1988) and Fuhrmann (1998a) confirms that this method provides systematically larger gravities than the ionization balance. The strong-line gravities get closer to the physical ones for the stars analyzed by Fuhrmann, but they are even further away than the iron ionization gravities for the stars of lower gravities in Edvardsson's sample. The confrontation of the deviations of the iron ionization gravities in metal-poor stars reported here with departures from the excitation balance found in the literature, show that they are likely to be induced by the same physical mechanism(s).Comment: AAS LaTeX v4.0, 35 pages, 10 PostScript files; to appear in The Astrophysical Journa

A Novel Unsupervised Method to Identify Genes Important in the Anti-viral Response: Application to Interferon/Ribavirin in Hepatitis C Patients

Background: Treating hepatitis C with interferon/ribavirin results in a varied response in terms of decrease in viral titer and ultimate outcome. Marked responders have a sharp decline in viral titer within a few days of treatment initiation, whereas in other patients there is no effect on the virus (poor responders). Previous studies have shown that combination therapy modifies expression of hundreds of genes in vitro and in vivo. However, identifying which, if any, of these genes have a role in viral clearance remains challenging. Aims: The goal of this paper is to link viral levels with gene expression and thereby identify genes that may be responsible for early decrease in viral titer. Methods: Microarrays were performed on RNA isolated from PBMC of patients undergoing interferon/ribavirin therapy. Samples were collected at pre-treatment (day 0), and 1, 2, 7, 14 and 28 days after initiating treatment. A novel method was applied to identify genes that are linked to a decrease in viral titer during interferon/ribavirin treatment. The method uses the relationship between inter-patient gene expression based proximities and inter-patient viral titer based proximities to define the association between microarray gene expression measurements of each gene and viral-titer measurements. Results: We detected 36 unique genes whose expressions provide a clustering of patients that resembles viral titer based clustering of patients. These genes include IRF7, MX1, OASL and OAS2, viperin and many ISG's of unknown function. Conclusion: The genes identified by this method appear to play a major role in the reduction of hepatitis C virus during the early phase of treatment. The method has broad utility and can be used to analyze response to any group of factors influencing biological outcome such as antiviral drugs or anti-cancer agents where microarray data are available. © 2007 Brodsky et al

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Optimally splitting cases for training and testing high dimensional classifiers

<p>Abstract</p> <p>Background</p> <p>We consider the problem of designing a study to develop a predictive classifier from high dimensional data. A common study design is to split the sample into a training set and an independent test set, where the former is used to develop the classifier and the latter to evaluate its performance. In this paper we address the question of what proportion of the samples should be devoted to the training set. How does this proportion impact the mean squared error (MSE) of the prediction accuracy estimate?</p> <p>Results</p> <p>We develop a non-parametric algorithm for determining an optimal splitting proportion that can be applied with a specific dataset and classifier algorithm. We also perform a broad simulation study for the purpose of better understanding the factors that determine the best split proportions and to evaluate commonly used splitting strategies (1/2 training or 2/3 training) under a wide variety of conditions. These methods are based on a decomposition of the MSE into three intuitive component parts.</p> <p>Conclusions</p> <p>By applying these approaches to a number of synthetic and real microarray datasets we show that for linear classifiers the optimal proportion depends on the overall number of samples available and the degree of differential expression between the classes. The optimal proportion was found to depend on the full dataset size (n) and classification accuracy - with higher accuracy and smaller <it>n </it>resulting in more assigned to the training set. The commonly used strategy of allocating 2/3rd of cases for training was close to optimal for reasonable sized datasets (<it>n </it>≥ 100) with strong signals (i.e. 85% or greater full dataset accuracy). In general, we recommend use of our nonparametric resampling approach for determing the optimal split. This approach can be applied to any dataset, using any predictor development method, to determine the best split.</p

Preprocessing and analyzing genetic data with complex networks: An application to Obstructive Nephropathy

Many diseases have a genetic origin, and a great effort is being made to detect the genes that are responsible for their insurgence. One of the most promising techniques is the analysis of genetic information through the use of complex networks theory. Yet, a practical problem of this approach is its computational cost, which scales as the square of the number of features included in the initial dataset. In this paper, we propose the use of an iterative feature selection strategy to identify reduced subsets of relevant features, and show an application to the analysis of congenital Obstructive Nephropathy. Results demonstrate that, besides achieving a drastic reduction of the computational cost, the topologies of the obtained networks still hold all the relevant information, and are thus able to fully characterize the severity of the disease