Language and sociability: insights from Williams syndrome

One of the most compelling features of Williams syndrome (WS) is the widely reported excessive sociability, accompanied by a relative proficiency in expressive language, which stands in stark contrast with significant intellectual and nonverbal impairments. It has been proposed that the unique language skills observed in WS are implicated in the strong drive to interact and communicate with others, which has been widely documented in WS. Nevertheless, this proposition has yet to be empirically examined. The present study aimed at investigating the relationship between a brain index of language processing and judgments of approachability of faces, as a proxy for sociability, in individuals with WS as contrasted to typical controls. Results revealed a significant and substantial association between the two in the WS, but not in the control group, supporting the hitherto untested notion that language use in WS might be uniquely related to their excessive social drive

The Evolution of Compact Binary Star Systems

We review the formation and evolution of compact binary stars consisting of white dwarfs (WDs), neutron stars (NSs), and black holes (BHs). Binary NSs and BHs are thought to be the primary astrophysical sources of gravitational waves (GWs) within the frequency band of ground-based detectors, while compact binaries of WDs are important sources of GWs at lower frequencies to be covered by space interferometers (LISA). Major uncertainties in the current understanding of properties of NSs and BHs most relevant to the GW studies are discussed, including the treatment of the natal kicks which compact stellar remnants acquire during the core collapse of massive stars and the common envelope phase of binary evolution. We discuss the coalescence rates of binary NSs and BHs and prospects for their detections, the formation and evolution of binary WDs and their observational manifestations. Special attention is given to AM CVn-stars -- compact binaries in which the Roche lobe is filled by another WD or a low-mass partially degenerate helium-star, as these stars are thought to be the best LISA verification binary GW sources.Comment: 105 pages, 18 figure

Regulation of Drosophila FMRFamide neuropeptide gene expression

Physiologically important peptides are often encoded in precursors that contain several gene products; thus, regulation of expression of polypeptide proteins is crucial to transduction pathways. Differential processing of precursors by cell- or tissue-specific proteolytic enzymes can yield messengers with diverse distributions and dissimilar activities. FMRFamide-related peptides (FaRPs) are present throughout the animal kingdom and affect both neural and gastrointestinal functions. Organisms have several genes encoding numerous FaRPs with a common C-terminal structure but different N-terminal amino acid extensions. We have isolated SDNFMRFamide, DPKQDFMRFamide, and TPAEDFMRFamide contained in the Drosophila FMRFamide gene. To investigate the regulation of expression of FMRFamide peptides, we generated antisera to distinguish among the three neuropeptides. We have previously reported the distribution of SDNFMRFamide and DPKQDFMRFamide. In this article, we describe TPAEDFMRFamide expression. TPAEDFMRFamide antisera stain cells in embryonic, larval, pupal, and adult thoracic and abdominal ganglia. In addition, TPAEDFMRFamide-immunoreactive material is present in a lateral protocerebrum cell in adult. Thus, TPAEDFMRFamide antisera staining of neural tissue is different from SDNFMRFamide or DPKQDFMRFamide. In addition, TPAEDFMRFamide antisera stain larval, pupal, and adult gut, while SDNFMRFamide and DPKQDFMRFamide do not. TPAEDFMRFamide immunoreactivity is present in cells stained by FMRFamide antisera. Taken together, these data support the conclusion that TPAEDFMRFamide is differentially processed from the FMRFamide polypeptide protein precursor and may act in both neural and gastrointestinal tissue. © 1999 John Wiley & Sons, Inc. J Neurobiol 39: 347–358, 1999Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34479/1/2_ftp.pd

Statistical machines for trauma hospital outcomes research: Application to the PRospective, Observational, Multi-center Major trauma Transfusion (PROMMTT) study

Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated). We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating on parameters that have more direct policy implications, these potentially automated approaches allow methodological standardization across similar comparativeness effectiveness studies

Chromosomal Aberrations in Bladder Cancer: Fresh versus Formalin Fixed Paraffin Embedded Tissue and Targeted FISH versus Wide Microarray-Based CGH Analysis

Bladder carcinogenesis is believed to follow two alternative pathways driven by the loss of chromosome 9 and the gain of chromosome 7, albeit other nonrandom copy number alterations (CNAs) were identified. However, confirmation studies are needed since many aspects of this model remain unclear and considerable heterogeneity among cases has emerged. One of the purposes of this study was to evaluate the performance of a targeted test (UroVysion assay) widely used for the detection of Transitional Cell Carcinoma (TCC) of the bladder, in two different types of material derived from the same tumor. We compared the results of UroVysion test performed on Freshly Isolated interphasic Nuclei (FIN) and on Formalin Fixed Paraffin Embedded (FFPE) tissues from 22 TCCs and we didn't find substantial differences. A second goal was to assess the concordance between array-CGH profiles and the targeted chromosomal profiles of UroVysion assay on an additional set of 10 TCCs, in order to evaluate whether UroVysion is an adequately sensitive method for the identification of selected aneuploidies and nonrandom CNAs in TCCs. Our results confirmed the importance of global genomic screening methods, that is array based CGH, to comprehensively determine the genomic profiles of large series of TCCs tumors. However, this technique has yet some limitations, such as not being able to detect low level mosaicism, or not detecting any change in the number of copies for a kind of compensatory effect due to the presence of high cellular heterogeneity. Thus, it is still advisable to use complementary techniques such as array-CGH and FISH, as the former is able to detect alterations at the genome level not excluding any chromosome, but the latter is able to maintain the individual data at the level of single cells, even if it focuses on few genomic regions