Lensed galaxies in Abell 370 I. Modeling the number counts and redshift distribution of background sources

We present new observations of the cluster-lens Abell 370: a deep HST/WFPC2 F675W image and ESO 3.6m spectroscopy of faint galaxies. These observations shade new lights on the statistical properties of faint lensed galaxies. In particular, we spectroscopically confirm the multiple image nature of the B2--B3 gravitational pair (Kneib et al. 1993), and determine a redshift of z=0.806 which is in very good agreement with earlier predictions. A refined mass model of the cluster core (that includes cluster galaxy halos) is presented, based on a number of newly identified multiple images. Following Bezecourt et al. (1998a), we combine the new cluster mass model with a spectrophotometric prescription for galaxy evolution to predict the arclets number counts and redshift distribution in the HST image. In particular, the ellipticity distribution of background sources is taken into account, in order to properly estimate the statistical number and redshift distribution of arclets. We show that the redshift distribution of arclets, and particularly its high redshift tail can be used as a strong constraint to disentangle different galaxy evolution scenario. A hierarchical model which includes a number density evolution is favored by our analysis. Finally, we compute the depletion curves in the faint galaxies number counts and discuss its wavelength dependence.Comment: 10 pages, Astronomy and Astrophysics in pres

Evaluating the effectiveness of therapy based around Shape Coding to develop the use of regular past tense morphemes in two children with language impairments

It has been suggested that difficulties with tense and agreement marking are a core feature of language impairment. Hence, studies are required that analyse the effectiveness of intervention in this area, including consideration of whether changes seen in therapy sessions generalize to spontaneous speech. This study assessed the effectiveness of therapy based around Shape Coding in developing the use of the regular past tense morpheme -ed in two school-aged children with language impairments. It also considered whether participants benefited from additional generalization therapy in order to start using target forms in their spontaneous speech. The former was assessed using a sentence completion task and the latter by a conversational task with blind assessors. One participant improved markedly in sentence completion but did not gain in the conversation task until after the generalization therapy. The other made more modest gains on the sentence completion task and seemed to generalize to the conversation task without recourse to the generalization therapy. Larger studies are required to confirm these interpretations and to determine whether they are applicable to the wider population of children with language impairments

Effectiveness of vocabulary intervention for older children with (developmental) language disorder

BACKGROUND: Children with developmental language disorder (DLD) frequently have difficulties with word learning and understanding vocabulary. For these children, this can significantly impact on social interactions, daily activities and academic progress. Although there is literature providing a rationale for targeting word learning in such children, there is little evidence for the effectiveness of specific interventions in this area for children with identified DLD. AIMS: To establish whether direct one-to-one intervention for children with DLD over 9 years of age leads to improved abilities to identify, comprehend, define, and use nouns and verbs targeted in intervention as compared with non-targeted control items and whether or not the participants’ rating of their own knowledge of the words changes with intervention. METHODS & PROCEDURES: Twenty-five children and young people with language disorder (aged 9;4–16;1) participated in the study: 18 with DLD and seven with a language disorder associated with autism spectrum disorder (ASD). Two assessments of different levels were created: a higher ability (less frequent words) and a lower ability (more frequent words). Participants’ speech and language therapists (SLTs) decided which level would be the most appropriate for each participant. Four tasks were carried out as part of the assessment and the scores were used to identify which words each participant worked on. Participants received one 30-min session per week one-to-one with their own SLT for 7 weeks, plus a 5-min revision session in between each main session. During each of the first five sessions, participants learned two new words; the two final sessions were spent revising the 10 words which had been targeted. OUTCOMES & RESULTS: Post-intervention assessment showed an increase in scores for both treated and control words. However, progress on treated words was significantly greater than on control words (d = 1.07), indicating effectiveness of intervention. The difference between progress on targeted and control words was found both for nouns (d = 1.29) and verbs (d = 0.64), but the effect size was larger for nouns. Whether or not the participants had an associated ASD did not affect the results. The children's self-rating of their knowledge of the targeted words was also significantly higher than for control words post-intervention. CONCLUSIONS & IMPLICATIONS: The intervention delivered one-to-one by the participants’ usual SLT was effective in teaching new vocabulary to older children with language disorders. This shows that older children with language disorders can make progress with direct one-to-one intervention focused on vocabulary

Predictive modelling using pathway scores: robustness and significance of pathway collections

Background Transcriptomic data is often used to build statistical models which are predictive of a given phenotype, such as disease status. Genes work together in pathways and it is widely thought that pathway representations will be more robust to noise in the gene expression levels. We aimed to test this hypothesis by constructing models based on either genes alone, or based on sample specific scores for each pathway, thus transforming the data to a ‘pathway space’. We progressively degraded the raw data by addition of noise and examined the ability of the models to maintain predictivity. Results Models in the pathway space indeed had higher predictive robustness than models in the gene space. This result was independent of the workflow, parameters, classifier and data set used. Surprisingly, randomised pathway mappings produced models of similar accuracy and robustness to true mappings, suggesting that the success of pathway space models is not conferred by the specific definitions of the pathway. Instead, predictive models built on the true pathway mappings led to prediction rules with fewer influential pathways than those built on randomised pathways. The extent of this effect was used to differentiate pathway collections coming from a variety of widely used pathway databases. Conclusions Prediction models based on pathway scores are more robust to degradation of gene expression information than the equivalent models based on ungrouped genes. While models based on true pathway scores are not more robust or accurate than those based on randomised pathways, true pathways produced simpler prediction rules, emphasizing a smaller number of pathways

Single sample pathway analysis in metabolomics: performance evaluation and application

Background Single sample pathway analysis (ssPA) transforms molecular level omics data to the pathway level, enabling the discovery of patient-specific pathway signatures. Compared to conventional pathway analysis, ssPA overcomes the limitations by enabling multi-group comparisons, alongside facilitating numerous downstream analyses such as pathway-based machine learning. While in transcriptomics ssPA is a widely used technique, there is little literature evaluating its suitability for metabolomics. Here we provide a benchmark of established ssPA methods (ssGSEA, GSVA, SVD (PLAGE), and z-score) alongside the evaluation of two novel methods we propose: ssClustPA and kPCA, using semi-synthetic metabolomics data. We then demonstrate how ssPA can facilitate pathway-based interpretation of metabolomics data by performing a case-study on inflammatory bowel disease mass spectrometry data, using clustering to determine subtype-specific pathway signatures. Results While GSEA-based and z-score methods outperformed the others in terms of recall, clustering/dimensionality reduction-based methods provided higher precision at moderate-to-high effect sizes. A case study applying ssPA to inflammatory bowel disease data demonstrates how these methods yield a much richer depth of interpretation than conventional approaches, for example by clustering pathway scores to visualise a pathway-based patient subtype-specific correlation network. We also developed the sspa python package (freely available at https://pypi.org/project/sspa/), providing implementations of all the methods benchmarked in this study. Conclusion This work underscores the value ssPA methods can add to metabolomic studies and provides a useful reference for those wishing to apply ssPA methods to metabolomics data

Bayesian Deconvolution and Quantification of Metabolites from J-Resolved NMR Spectroscopy

Two-dimensional (2D) nuclear magnetic resonance (nmr) methods have become increasingly popular in metabolomics, since they have considerable potential to accurately identify and quantify metabolites within complex biological samples. 2D 1 H J-resolved (jres) nmr spectroscopy is a widely used method that expands overlapping resonances into a second dimension. However, existing analytical processing methods do not fully exploit the information in the jres spectrum and, more importantly, do not provide measures of uncertainty associated with the estimates of quantities of interest, such as metabolite concentration. Combining the data-generating mechanisms and the extensive prior knowledge available in online databases, we develop a Bayesian method to analyse 2D jres data, which allows for automatic deconvolution, identification and quantification of metabolites. The model extends and improves previous work on one-dimensional nmr spectral data. Our approach is based on a combination of B-spline tight wavelet frames and theoretical templates, and thus enables the automatic incorporation of expert knowledge within the inferential framework. Posterior inference is performed through specially devised Markov chain Monte Carlo methods. We demonstrate the performance of our approach via analyses of datasets from serum and urine, showing the advantages of our proposed approach in terms of identification and quantification of metabolites

Galaxies at z=4 and the Formation of Population II

We report the discovery of four high-redshift objects (3.3 < z < 4) observed behind the rich cluster CL0939+4713 (Abell 851). One object (DG 433) has a redshift of z=3.3453; the other three objects have redshifts of z\approx 4: A0 at z=3.9819, DG 353 and P1/P2 at z=3.9822. It is possible that all four objects are being lensed in some way by the cluster, DG 433 being weakly sheared, A0 being strongly sheared, and DG 353 and P1/P2 being an image pair of a common source object; detailed modelling of the cluster potential will be necessary to confirm this hypothesis. The weakness of common stellar wind features like N V and especially C IV in the spectra of these objects argues for sub-solar metallicities, at least as low as the SMC. DG 353 and DG 433, which have ground-based colors, are moderately dusty [E_{int}(B-V) < 0.15], similar to other z>3 galaxies. Star formation rates range from 2.5 (7.8) h^{-2} to 22. (78.) h^{-2} M_{\odot}/yr, for q_0=0.5 (0.05), depending on assumptions about gravitational lensing and extinction, also typical of other z>3 galaxies. These objects are tenatively identified as the low-metallicity proto-spheroid clumps that will merge to form the Population II components of today's spheroids.Comment: 16 pages, including 2 PostScript figures. Needs aaspp4.sty (included). Accepted for publication in the Astrophysical Journa

B stars as a diagnostic of star-formation at low and high redshift

We have extended the evolutionary synthesis models by Leitherer et al. (1999b) by including a new library of B stars generated from the IUE high-dispersion spectra archive. We present the library and show how the stellar spectral properties vary according to luminosity classes and spectral types. We have generated synthetic UV spectra for prototypical young stellar populations varying the IMF and the star formation law. Clear signs of age effects are seen in all models. The contribution of B stars in the UV line spectrum is clearly detected, in particular for greater ages when O stars have evolved. With the addition of the new library we are able to investigate the fraction of stellar and interstellar contributions and the variation in the spectral shapes of intense lines. We have used our models to date the spectrum of the local super star cluster NGC1705-1. Photospheric lines of CIII1247, SiIII1417, and SV1502 were used as diagnostics to date the burst of NGC 1705-1 at 10 Myr. We have selected the star-forming galaxy 1512-cB58 as a first application of the new models to high-z galaxies. This galaxy is at z=2.723, it is gravitationally lensed, and its high signal-to-noise Keck spectrum show features typical of local starburst galaxies, such as NGC 1705-1. Models with continuous star formation were found to be more adequate for 1512-cB58 since there are spectral features typical of a composite stellar population of O and B stars. A model with Z =0.4Z_solar and an IMF with alpha=2.8 reproduces the stellar features of the 1512-cB58 spectrum.Comment: 23 pages with figures, see http://sol.stsci.edu/~demello/welcomeb.htm

A Multiwavelength Analysis of the Strong Lensing Cluster RCS 022434-0002.5 at z=0.778

We present the results of two (101 ks total) Chandra observations of the z=0.778 optically selected lensing cluster RCS022434-0002.5, along with weak lensing and dynamical analyses of this object. An X-ray spectrum extracted within R(2500) (362 h(70)^(-1) kpc) results in an integrated cluster temperature of 5.1 (+0.9,-0.5) keV. The surface brightness profile of RCS022434-0002.5 indicates the presence of a slight excess of emission in the core. A hardness ratio image of this object reveals that this central emission is primarily produced by soft X-rays. Further investigation yields a cluster cooling time of 3.3 times 10^9 years, which is less than half of the age of the universe at this redshift given the current LCDM cosmology. A weak lensing analysis is performed using HST images, and our weak lensing mass estimate is found to be in good agreement with the X-ray determined mass of the cluster. Spectroscopic analysis reveals that RCS022434-0002.5 has a velocity dispersion of 900 +/- 180 km/s, consistent with its X-ray temperature. The core gas mass fraction of RCS022434-0002.5 is, however, found to be three times lower than expected universal values. The radial distribution of X-ray point sources within R(200) of this cluster peaks at ~0.7 R(200), possibly indicating that the cluster potential is influencing AGN activity at that radius. Correlations between X-ray and radio (VLA) point source positions are also examined.Comment: 32 pages, 9 figures. Accepted for publication in The Astrophysical Journa