Language abilities in children with autism and language impairment: using narrative as a additional source of clinical information

Autistic Spectrum Disorder (ASD) and Specific Language Impairment (SLI) are disorders of communication that are sometimes thought to show similar structural language difficulties. Recent research has even suggested that they might be aetiologically related. However, it may be that standardized language tasks are not sensitive enough to detect similarities and differences accurately. This study involved 26 Greek children with either ASD or SLI and compared them on standardized measures of structural and pragmatic language as well as using a structured narrative task. Children with ASD were more impaired on receptive but not expressive scores from standardized language tests. In contrast, narrative measures showed significantly poorer ASD performance in expressive skills involving wider story-telling skill and in some sentence-level skills, in particular referencing, compared to peers with SLI. ASD and SLI groups also showed different relationships between structural language and other measures. The data suggests that narrative is a useful tool for revealing qualitative differences in language between overlapping communication disorders both at the clinical and theoretical level, since it provides information that is lost in more formalized testing. This may be particularly true where norms are not available or testing is difficult

Formation of regulatory modules by local sequence duplication

Turnover of regulatory sequence and function is an important part of molecular evolution. But what are the modes of sequence evolution leading to rapid formation and loss of regulatory sites? Here, we show that a large fraction of neighboring transcription factor binding sites in the fly genome have formed from a common sequence origin by local duplications. This mode of evolution is found to produce regulatory information: duplications can seed new sites in the neighborhood of existing sites. Duplicate seeds evolve subsequently by point mutations, often towards binding a different factor than their ancestral neighbor sites. These results are based on a statistical analysis of 346 cis-regulatory modules in the Drosophila melanogaster genome, and a comparison set of intergenic regulatory sequence in Saccharomyces cerevisiae. In fly regulatory modules, pairs of binding sites show significantly enhanced sequence similarity up to distances of about 50 bp. We analyze these data in terms of an evolutionary model with two distinct modes of site formation: (i) evolution from independent sequence origin and (ii) divergent evolution following duplication of a common ancestor sequence. Our results suggest that pervasive formation of binding sites by local sequence duplications distinguishes the complex regulatory architecture of higher eukaryotes from the simpler architecture of unicellular organisms

Identifying Cis-Regulatory Sequences by Word Profile Similarity

Recognizing regulatory sequences in genomes is a continuing challenge, despite a wealth of available genomic data and a growing number of experimentally validated examples.We discuss here a simple approach to search for regulatory sequences based on the compositional similarity of genomic regions and known cis-regulatory sequences. This method, which is not limited to searching for predefined motifs, recovers sequences known to be under similar regulatory control. The words shared by the recovered sequences often correspond to known binding sites. Furthermore, we show that although local word profile clustering is predictive for the regulatory sequences involved in blastoderm segmentation, local dissimilarity is a more universal feature of known regulatory sequences in Drosophila.Our method leverages sequence motifs within a known regulatory sequence to identify co-regulated sequences without explicitly defining binding sites. We also show that regulatory sequences can be distinguished from surrounding sequences by local sequence dissimilarity, a novel feature in identifying regulatory sequences across a genome. Source code for WPH-finder is available for download at http://rana.lbl.gov/downloads/wph.tar.gz

Benchmarking and Analysis of Protein Docking Performance in Rosetta v3.2

RosettaDock has been increasingly used in protein docking and design strategies in order to predict the structure of protein-protein interfaces. Here we test capabilities of RosettaDock 3.2, part of the newly developed Rosetta v3.2 modeling suite, against Docking Benchmark 3.0, and compare it with RosettaDock v2.3, the latest version of the previous Rosetta software package. The benchmark contains a diverse set of 116 docking targets including 22 antibody-antigen complexes, 33 enzyme-inhibitor complexes, and 60 ‘other’ complexes. These targets were further classified by expected docking difficulty into 84 rigid-body targets, 17 medium targets, and 14 difficult targets. We carried out local docking perturbations for each target, using the unbound structures when available, in both RosettaDock v2.3 and v3.2. Overall the performances of RosettaDock v2.3 and v3.2 were similar. RosettaDock v3.2 achieved 56 docking funnels, compared to 49 in v2.3. A breakdown of docking performance by protein complex type shows that RosettaDock v3.2 achieved docking funnels for 63% of antibody-antigen targets, 62% of enzyme-inhibitor targets, and 35% of ‘other’ targets. In terms of docking difficulty, RosettaDock v3.2 achieved funnels for 58% of rigid-body targets, 30% of medium targets, and 14% of difficult targets. For targets that failed, we carry out additional analyses to identify the cause of failure, which showed that binding-induced backbone conformation changes account for a majority of failures. We also present a bootstrap statistical analysis that quantifies the reliability of the stochastic docking results. Finally, we demonstrate the additional functionality available in RosettaDock v3.2 by incorporating small-molecules and non-protein co-factors in docking of a smaller target set. This study marks the most extensive benchmarking of the RosettaDock module to date and establishes a baseline for future research in protein interface modeling and structure prediction

Reduced Diversity and High Sponge Abundance on a Sedimented Indo-Pacific Reef System: Implications for Future Changes in Environmental Quality

Although coral reef health across the globe is declining as a result of anthropogenic impacts, relatively little is known of how environmental variability influences reef organisms other than corals and fish. Sponges are an important component of coral reef fauna that perform many important functional roles and changes in their abundance and diversity as a result of environmental change has the potential to affect overall reef ecosystem functioning. In this study, we examined patterns of sponge biodiversity and abundance across a range of environments to assess the potential key drivers of differences in benthic community structure. We found that sponge assemblages were significantly different across the study sites, but were dominated by one species Lamellodysidea herbacea (42% of all sponges patches recorded) and that the differential rate of sediment deposition was the most important variable driving differences in abundance patterns. Lamellodysidea herbacea abundance was positively associated with sedimentation rates, while total sponge abundance excluding Lamellodysidea herbacea was negatively associated with rates of sedimentation. Overall variation in sponge assemblage composition was correlated with a number of variables although each variable explained only a small amount of the overall variation. Although sponge abundance remained similar across environments, diversity was negatively affected by sedimentation, with the most sedimented sites being dominated by a single sponge species. Our study shows how some sponge species are able to tolerate high levels of sediment and that any transition of coral reefs to more sedimented states may result in a shift to a low diversity sponge dominated system, which is likely to have subsequent effects on ecosystem functioning. © 2014 Powell et al

The role of the bronchial microvasculature in the airway remodelling in asthma and COPD

In recent years, there has been increased interest in the vascular component of airway remodelling in chronic bronchial inflammation, such as asthma and COPD, and in its role in the progression of disease. In particular, the bronchial mucosa in asthmatics is more vascularised, showing a higher number and dimension of vessels and vascular area. Recently, insight has been obtained regarding the pivotal role of vascular endothelial growth factor (VEGF) in promoting vascular remodelling and angiogenesis. Many studies, conducted on biopsies, induced sputum or BAL, have shown the involvement of VEGF and its receptors in the vascular remodelling processes. Presumably, the vascular component of airway remodelling is a complex multi-step phenomenon involving several mediators. Among the common asthma and COPD medications, only inhaled corticosteroids have demonstrated a real ability to reverse all aspects of vascular remodelling. The aim of this review was to analyze the morphological aspects of the vascular component of airway remodelling and the possible mechanisms involved in asthma and COPD. We also focused on the functional and therapeutic implications of the bronchial microvascular changes in asthma and COPD

Enhancement of crystallization with nucleotide ligands identified by dye-ligand affinity chromatography

Ligands interacting with Mycobacterium tuberculosis recombinant proteins were identified through use of the ability of Cibacron Blue F3GA dye to interact with nucleoside/nucleotide binding proteins, and the effects of these ligands on crystallization were examined. Co-crystallization with ligands enhanced crystallization and enabled X-ray diffraction data to be collected to a resolution of at least 2.7 Å for 5 of 10 proteins tested. Additionally, clues about individual proteins’ functions were obtained from their interactions with each of a panel of ligands

Shifting Characterizations of the ‘Common People’ in Modern English Retranslations of Thucydides’ History of the Peloponnesian War: A corpus-based analysis

Little research has yet explored the impact of (re)translation on narrative characterization, that is, on the process through which the various actors depicted in a narrative are attributed particular traits and qualities. Moreover, the few studies that have been published on this topic are either rather more anecdotal than systematic, or their focus is primarily on the losses in character information that inevitably occur when a narrative is retold for a new audience in a new linguistic context. They do not explore how the translator’s own background knowledge and ideological beliefs might affect the characterization process for readers of their target-language text. Consequently, this paper seeks to make two contributions to the field: first, it presents a corpus-based methodology developed as part of the Genealogies of Knowledge project for the comparative analysis of characterization patterns in multiple retranslations of a single source text. Such an approach is valuable, it is argued, because it can enhance our ability to engage in a more systematic manner with the accumulation of characterization cues spread throughout a narrative. Second, the paper seeks to move discussions of the effects of translation on narrative characterization away from a paradigm of loss, deficiency and failure, promoting instead a perspective which embraces the productive role translators often play in reconfiguring the countless narratives through which we come to know, imagine and make sense of the past, our present and futures. The potential of this methodology and theoretical standpoint is illustrated through a case study exploring changes in the characterization of ‘the common people’ in two English-language versions of classical Greek historian Thucydides’ History of the Peloponnesian War, the first produced by Samuel Bloomfield in 1829 and the second by Steven Lattimore in 1998. Particular attention is paid to the referring expressions used by each translator—such as the multitude vs. the common people—as well as the specific attributes assigned to this narrative actor. In this way, the study attempts to gain deeper insight into the ways in which these translations reflect important shifts in attitudes within key political debates concerning the benefits and dangers of democracy

Fine-Tuning Enhancer Models to Predict Transcriptional Targets across Multiple Genomes

Networks of regulatory relations between transcription factors (TF) and their target genes (TG)- implemented through TF binding sites (TFBS)- are key features of biology. An idealized approach to solving such networks consists of starting from a consensus TFBS or a position weight matrix (PWM) to generate a high accuracy list of candidate TGs for biological validation. Developing and evaluating such approaches remains a formidable challenge in regulatory bioinformatics. We perform a benchmark study on 34 Drosophila TFs to assess existing TFBS and cis-regulatory module (CRM) detection methods, with a strong focus on the use of multiple genomes. Particularly, for CRM-modelling we investigate the addition of orthologous sites to a known PWM to construct phyloPWMs and we assess the added value of phylogenentic footprinting to predict contextual motifs around known TFBSs. For CRM-prediction, we compare motif conservation with network-level conservation approaches across multiple genomes. Choosing the optimal training and scoring strategies strongly enhances the performance of TG prediction for more than half of the tested TFs. Finally, we analyse a 35th TF, namely Eyeless, and find a significant overlap between predicted TGs and candidate TGs identified by microarray expression studies. In summary we identify several ways to optimize TF-specific TG predictions, some of which can be applied to all TFs, and others that can be applied only to particular TFs. The ability to model known TF-TG relations, together with the use of multiple genomes, results in a significant step forward in solving the architecture of gene regulatory networks