A Multitrait–Multimethod Analysis of the Construct Validity of Child Anxiety Disorders in a Clinical Sample

The present study examines the construct validity of separation anxiety disorder (SAD), social phobia (SoP), panic disorder (PD), and generalized anxiety disorder (GAD) in a clinical sample of children. Participants were 174 children, 6 to 17 years old (94 boys) who had undergone a diagnostic evaluation at a university hospital based clinic. Parent and child ratings of symptom severity were assessed using the Multidimensional Anxiety Scale for Children (MASC). Diagnostician ratings were obtained from the Anxiety Disorders Interview Schedule for Children and Parents (ADIS: C/P). Discriminant and convergent validity were assessed using confirmatory factor analytic techniques to test a multitrait–multimethod model. Confirmatory factor analyses supported the current classification of these child anxiety disorders. The disorders demonstrated statistical independence from each other (discriminant validity of traits), the model fit better when the anxiety syndromes were specified than when no specific syndromes were specified (convergent validity), and the methods of assessment yielded distinguishable, unique types of information about child anxiety (discriminant validity of methods). Using a multi-informant approach, these findings support the distinctions between childhood anxiety disorders as delineated in the current classification system, suggesting that disagreement between informants in psychometric studies of child anxiety measures is not due to poor construct validity of these anxiety syndromes

ProteinHistorian: Tools for the Comparative Analysis of Eukaryote Protein Origin

The evolutionary history of a protein reflects the functional history of its ancestors. Recent phylogenetic studies identified distinct evolutionary signatures that characterize proteins involved in cancer, Mendelian disease, and different ontogenic stages. Despite the potential to yield insight into the cellular functions and interactions of proteins, such comparative phylogenetic analyses are rarely performed, because they require custom algorithms. We developed ProteinHistorian to make tools for performing analyses of protein origins widely available. Given a list of proteins of interest, ProteinHistorian estimates the phylogenetic age of each protein, quantifies enrichment for proteins of specific ages, and compares variation in protein age with other protein attributes. ProteinHistorian allows flexibility in the definition of protein age by including several algorithms for estimating ages from different databases of evolutionary relationships. We illustrate the use of ProteinHistorian with three example analyses. First, we demonstrate that proteins with high expression in human, compared to chimpanzee and rhesus macaque, are significantly younger than those with human-specific low expression. Next, we show that human proteins with annotated regulatory functions are significantly younger than proteins with catalytic functions. Finally, we compare protein length and age in many eukaryotic species and, as expected from previous studies, find a positive, though often weak, correlation between protein age and length. ProteinHistorian is available through a web server with an intuitive interface and as a set of command line tools; this allows biologists and bioinformaticians alike to integrate these approaches into their analysis pipelines. ProteinHistorian's modular, extensible design facilitates the integration of new datasets and algorithms. The ProteinHistorian web server, source code, and pre-computed ages for 32 eukaryotic genomes are freely available under the GNU public license at http://lighthouse.ucsf.edu/ProteinHistorian/

Physical properties of naked DNA influence nucleosome positioning and correlate with transcription start and termination sites in yeast

Abstract Background In eukaryotic organisms, DNA is packaged into chromatin structure, where most of DNA is wrapped into nucleosomes. DNA compaction and nucleosome positioning have clear functional implications, since they modulate the accessibility of genomic regions to regulatory proteins. Despite the intensive research effort focused in this area, the rules defining nucleosome positioning and the location of DNA regulatory regions still remain elusive. Results Naked (histone-free) and nucleosomal DNA from yeast were digested by microccocal nuclease (MNase) and sequenced genome-wide. MNase cutting preferences were determined for both naked and nucleosomal DNAs. Integration of their sequencing profiles with DNA conformational descriptors derived from atomistic molecular dynamic simulations enabled us to extract the physical properties of DNA on a genomic scale and to correlate them with chromatin structure and gene regulation. The local structure of DNA around regulatory regions was found to be unusually flexible and to display a unique pattern of nucleosome positioning. Ab initio physical descriptors derived from molecular dynamics were used to develop a computational method that accurately predicts nucleosome enriched and depleted regions. Conclusions Our experimental and computational analyses jointly demonstrate a clear correlation between sequence-dependent physical properties of naked DNA and regulatory signals in the chromatin structure. These results demonstrate that nucleosome positioning around TSS (Transcription Start Site) and TTS (Transcription Termination Site) (at least in yeast) is strongly dependent on DNA physical properties, which can define a basal regulatory mechanism of gene expression

Differential Expression of CD163 on Monocyte Subsets in Healthy and HIV-1 Infected Individuals

CD163, a haptoglobin-hemoglobin (Hp-Hb) scavenger receptor, expressed by monocytes and macrophages, is important in resolution of inflammation. Age-related non-AIDS co-morbidities in HIV-infected individuals, particularly dementia and cardiovascular disease, result in part from effects of HIV-1 infection on monocyte and macrophage biology. CD163 co-expression on CD14+CD16++ monocytes has been proposed as a useful biomarker for HIV-1 disease progression and the presence of HIV associated dementia. Here we investigated CD163 expression on monocyte subsets ex vivo, on cultured macrophages, and soluble in plasma, in the setting of HIV-1 infection. Whole blood immunophenotyping revealed CD163 expression on CD14++CD16- monocytes but not on CD14+CD16++ monocytes (P = 0.004), supported by CD163 mRNA levels. Incubation with M-CSF induced CD163 protein expression on CD14+CD16++ monocytes to the same extent as CD14++CD16− monocytes. CD163 expression on CD14++CD16+ monocytes from HIV-infected subjects was significantly higher than from uninfected individuals, with a trend towards increased expression on CD14++CD16− monocytes (P = 0.019 and 0.069 respectively), which is accounted for by HIV-1 therapy including protease inhibitors. Shedding of CD163 was shown to predominantly occur from the CD14++CD16− subset after Ficoll isolation and LPS stimulation. Soluble CD163 concentration in plasma from HIV-1 infected donors was similar to HIV-1 uninfected donors. Monocyte CD163 expression in HIV-1 infected patients showed a complicated relationship with classical measures of disease progression. Our findings clarify technical issues regarding CD163 expression on monocyte subsets and further elucidates its role in HIV-associated inflammation by demonstrating that CD163 is readily lost from CD14++CD16− monocytes and induced in pro-inflammatory CD14+CD16++ monocytes by M-CSF. Our data show that all monocyte subsets are potentially capable of differentiating into CD163-expressing anti-inflammatory macrophages given appropriate stimuli. Levels of CD163 expression on monocytes may be a potential biomarker reflecting efforts by the immune system to resolve immune activation and inflammation in HIV-infected individuals

Differential Expression of CD163 on Monocyte Subsets in Healthy and HIV-1 Infected Individuals

CD163, a haptoglobin-hemoglobin (Hp-Hb) scavenger receptor, expressed by monocytes and macrophages, is important in resolution of inflammation. Age-related non-AIDS co-morbidities in HIV-infected individuals, particularly dementia and cardiovascular disease, result in part from effects of HIV-1 infection on monocyte and macrophage biology. CD163 co-expression on CD14+CD16++ monocytes has been proposed as a useful biomarker for HIV-1 disease progression and the presence of HIV associated dementia. Here we investigated CD163 expression on monocyte subsets ex vivo, on cultured macrophages, and soluble in plasma, in the setting of HIV-1 infection. Whole blood immunophenotyping revealed CD163 expression on CD14++CD16- monocytes but not on CD14+CD16++ monocytes (P = 0.004), supported by CD163 mRNA levels. Incubation with M-CSF induced CD163 protein expression on CD14+CD16++ monocytes to the same extent as CD14++CD16− monocytes. CD163 expression on CD14++CD16+ monocytes from HIV-infected subjects was significantly higher than from uninfected individuals, with a trend towards increased expression on CD14++CD16− monocytes (P = 0.019 and 0.069 respectively), which is accounted for by HIV-1 therapy including protease inhibitors. Shedding of CD163 was shown to predominantly occur from the CD14++CD16− subset after Ficoll isolation and LPS stimulation. Soluble CD163 concentration in plasma from HIV-1 infected donors was similar to HIV-1 uninfected donors. Monocyte CD163 expression in HIV-1 infected patients showed a complicated relationship with classical measures of disease progression. Our findings clarify technical issues regarding CD163 expression on monocyte subsets and further elucidates its role in HIV-associated inflammation by demonstrating that CD163 is readily lost from CD14++CD16− monocytes and induced in pro-inflammatory CD14+CD16++ monocytes by M-CSF. Our data show that all monocyte subsets are potentially capable of differentiating into CD163-expressing anti-inflammatory macrophages given appropriate stimuli. Levels of CD163 expression on monocytes may be a potential biomarker reflecting efforts by the immune system to resolve immune activation and inflammation in HIV-infected individuals

Venous gas embolism as a predictive tool for improving CNS decompression safety

A key process in the pathophysiological steps leading to decompression sickness (DCS) is the formation of inert gas bubbles. The adverse effects of decompression are still not fully understood, but it seems reasonable to suggest that the formation of venous gas emboli (VGE) and their effects on the endothelium may be the central mechanism leading to central nervous system (CNS) damage. Hence, VGE might also have impact on the long-term health effects of diving. In the present review, we highlight the findings from our laboratory related to the hypothesis that VGE formation is the main mechanism behind serious decompression injuries. In recent studies, we have determined the impact of VGE on endothelial function in both laboratory animals and in humans. We observed that the damage to the endothelium due to VGE was dose dependent, and that the amount of VGE can be affected both by aerobic exercise and exogenous nitric oxide (NO) intervention prior to a dive. We observed that NO reduced VGE during decompression, and pharmacological blocking of NO production increased VGE formation following a dive. The importance of micro-nuclei for the formation of VGE and how it can be possible to manipulate the formation of VGE are discussed together with the effects of VGE on the organism. In the last part of the review we introduce our thoughts for the future, and how the enigma of DCS should be approached

The Princeton Protein Orthology Database (P-POD): A Comparative Genomics Analysis Tool for Biologists

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic relationships among predicted orthologs (based on the OrthoMCL method) to a query gene from any of eight eukaryotic organisms, and to see the orthologs in a wider evolutionary context (based on the Jaccard clustering method). In addition to the phylogenetic information, the database contains experimental results manually collected from the literature that can be compared to the computational analyses, as well as links to relevant human disease and gene information via the OMIM, model organism, and sequence databases. Our aim is for the P-POD resource to be extremely useful to typical experimental biologists wanting to learn more about the evolutionary context of their favorite genes. P-POD is based on the commonly used Generic Model Organism Database (GMOD) schema and can be downloaded in its entirety for installation on one's own system. Thus, bioinformaticians and software developers may also find P-POD useful because they can use the P-POD database infrastructure when developing their own comparative genomics resources and database tools

Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde