The systemic lupus erythematosus IRF5 risk haplotype is associated with systemic sclerosis

Systemic sclerosis (SSc) is a fibrotic autoimmune disease in which the genetic component plays an important role. One of the strongest SSc association signals outside the human leukocyte antigen (HLA) region corresponds to interferon (IFN) regulatory factor 5 (IRF5), a major regulator of the type I IFN pathway. In this study we aimed to evaluate whether three different haplotypic blocks within this locus, which have been shown to alter the protein function influencing systemic lupus erythematosus (SLE) susceptibility, are involved in SSc susceptibility and clinical phenotypes. For that purpose, we genotyped one representative single-nucleotide polymorphism (SNP) of each block (rs10488631, rs2004640, and rs4728142) in a total of 3,361 SSc patients and 4,012 unaffected controls of Caucasian origin from Spain, Germany, The Netherlands, Italy and United Kingdom. A meta-analysis of the allele frequencies was performed to analyse the overall effect of these IRF5 genetic variants on SSc. Allelic combination and dependency tests were also carried out. The three SNPs showed strong associations with the global disease (rs4728142: P = 1.34×10<sup>−8</sup>, OR = 1.22, CI 95% = 1.14–1.30; rs2004640: P = 4.60×10<sup>−7</sup>, OR = 0.84, CI 95% = 0.78–0.90; rs10488631: P = 7.53×10<sup>−20</sup>, OR = 1.63, CI 95% = 1.47–1.81). However, the association of rs2004640 with SSc was not independent of rs4728142 (conditioned P = 0.598). The haplotype containing the risk alleles (rs4728142*A-rs2004640*T-rs10488631*C: P = 9.04×10<sup>−22</sup>, OR = 1.75, CI 95% = 1.56–1.97) better explained the observed association (likelihood P-value = 1.48×10<sup>−4</sup>), suggesting an additive effect of the three haplotypic blocks. No statistical significance was observed in the comparisons amongst SSc patients with and without the main clinical characteristics. Our data clearly indicate that the SLE risk haplotype also influences SSc predisposition, and that this association is not sub-phenotype-specific

Divisive Gain Modulation with Dynamic Stimuli in Integrate-and-Fire Neurons

The modulation of the sensitivity, or gain, of neural responses to input is an important component of neural computation. It has been shown that divisive gain modulation of neural responses can result from a stochastic shunting from balanced (mixed excitation and inhibition) background activity. This gain control scheme was developed and explored with static inputs, where the membrane and spike train statistics were stationary in time. However, input statistics, such as the firing rates of pre-synaptic neurons, are often dynamic, varying on timescales comparable to typical membrane time constants. Using a population density approach for integrate-and-fire neurons with dynamic and temporally rich inputs, we find that the same fluctuation-induced divisive gain modulation is operative for dynamic inputs driving nonequilibrium responses. Moreover, the degree of divisive scaling of the dynamic response is quantitatively the same as the steady-state responses—thus, gain modulation via balanced conductance fluctuations generalizes in a straight-forward way to a dynamic setting

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

The Minimal Scale Invariant Extension of the Standard Model

We perform a systematic analysis of an extension of the Standard Model that includes a complex singlet scalar field and is scale invariant at the tree level. We call such a model the Minimal Scale Invariant extension of the Standard Model (MSISM). The tree-level scale invariance of the model is explicitly broken by quantum corrections, which can trigger electroweak symmetry breaking and potentially provide a mechanism for solving the gauge hierarchy problem. Even though the scale invariant Standard Model is not a realistic scenario, the addition of a complex singlet scalar field may result in a perturbative and phenomenologically viable theory. We present a complete classification of the flat directions which may occur in the classical scalar potential of the MSISM. After calculating the one-loop effective potential of the MSISM, we investigate a number of representative scenarios and determine their scalar boson mass spectra, as well as their perturbatively allowed parameter space compatible with electroweak precision data. We discuss the phenomenological implications of these scenarios, in particular, whether they realize explicit or spontaneous CP violation, neutrino masses or provide dark matter candidates. In particular, we find a new minimal scale-invariant model of maximal spontaneous CP violation which can stay perturbative up to Planck-mass energy scales, without introducing an unnaturally large hierarchy in the scalar-potential couplings.Comment: 71 pages, 34 eps figures, numerical error corrected, clarifying comments adde

Psychological determinants of whole-body endurance performance

Background: No literature reviews have systematically identified and evaluated research on the psychological determinants of endurance performance, and sport psychology performance-enhancement guidelines for endurance sports are not founded on a systematic appraisal of endurance-specific research. Objective: A systematic literature review was conducted to identify practical psychological interventions that improve endurance performance and to identify additional psychological factors that affect endurance performance. Additional objectives were to evaluate the research practices of included studies, to suggest theoretical and applied implications, and to guide future research. Methods: Electronic databases, forward-citation searches, and manual searches of reference lists were used to locate relevant studies. Peer-reviewed studies were included when they chose an experimental or quasi-experimental research design, a psychological manipulation, endurance performance as the dependent variable, and athletes or physically-active, healthy adults as participants. Results: Consistent support was found for using imagery, self-talk, and goal setting to improve endurance performance, but it is unclear whether learning multiple psychological skills is more beneficial than learning one psychological skill. The results also demonstrated that mental fatigue undermines endurance performance, and verbal encouragement and head-to-head competition can have a beneficial effect. Interventions that influenced perception of effort consistently affected endurance performance. Conclusions: Psychological skills training could benefit an endurance athlete. Researchers are encouraged to compare different practical psychological interventions, to examine the effects of these interventions for athletes in competition, and to include a placebo control condition or an alternative control treatment. Researchers are also encouraged to explore additional psychological factors that could have a negative effect on endurance performance. Future research should include psychological mediating variables and moderating variables. Implications for theoretical explanations of endurance performance and evidence-based practice are described

A comparison of four clustering methods for brain expression microarray data

Background DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they produce can be an obstacle to interpretation of the results. Clustering the genes on the basis of similarity of their expression profiles can simplify the data, and potentially provides an important source of biological inference, but these methods have not been tested systematically on datasets from complex human tissues. In this paper, four clustering methods, CRC, k-means, ISA and memISA, are used upon three brain expression datasets. The results are compared on speed, gene coverage and GO enrichment. The effects of combining the clusters produced by each method are also assessed. Results k-means outperforms the other methods, with 100% gene coverage and GO enrichments only slightly exceeded by memISA and ISA. Those two methods produce greater GO enrichments on the datasets used, but at the cost of much lower gene coverage, fewer clusters produced, and speed. The clusters they find are largely different to those produced by k-means. Combining clusters produced by k-means and memISA or ISA leads to increased GO enrichment and number of clusters produced (compared to k-means alone), without negatively impacting gene coverage. memISA can also find potentially disease-related clusters. In two independent dorsolateral prefrontal cortex datasets, it finds three overlapping clusters that are either enriched for genes associated with schizophrenia, genes differentially expressed in schizophrenia, or both. Two of these clusters are enriched for genes of the MAP kinase pathway, suggesting a possible role for this pathway in the aetiology of schizophrenia. Conclusion Considered alone, k-means clustering is the most effective of the four methods on typical microarray brain expression datasets. However, memISA and ISA can add extra high-quality clusters to the set produced by k-means, so combining these three methods is the method of choice

The role of ARF6 in biliary atresia

Background & Aims: Altered extrahepatic bile ducts, gut, and cardiovascular anomalies constitute the variable phenotype of biliary atresia (BA). Methods: To identify potential susceptibility loci, Caucasian children, normal (controls) and with BA (cases) at two US centers were compared at >550000 SNP loci. Systems biology analysis was carried out on the data. In order to validate a key gene identified in the analysis, biliary morphogenesis was evaluated in 2-5-day post-fertilization zebrafish embryos after morpholino-antisense oligonucleotide knockdown of the candidate gene ADP ribosylation factor-6 (ARF6, Mo-arf6). Results: Among 39 and 24 cases at centers 1 and 2, respectively, and 1907 controls, which clustered together on principal component analysis, the SNPs rs3126184 and rs10140366 in a 3' flanking enhancer region for ARF6 demonstrated higher minor allele frequencies (MAF) in each cohort, and 63 combined cases, compared with controls (0.286 vs. 0.131, P = 5.94 x 10-7, OR 2.66; 0.286 vs. 0.13, P = 5.57 x 10-7, OR 2.66). Significance was enhanced in 77 total cases, which included 14 additional BA genotyped at rs3126184 only (p = 1.58 x 10-2, OR = 2.66). Pathway analysis of the 1000 top-ranked SNPs in CHP cases revealed enrichment of genes for EGF regulators (p<1 x 10-7), ERK/MAPK and CREB canonical pathways (p<1 x 10-34), and functional networks for cellular development and proliferation (p<1 x 10-45), further supporting the role of EGFR-ARF6 signaling in BA. In zebrafish embryos, Mo-arf6 injection resulted in a sparse intrahepatic biliary network, several biliary epithelial cell defects, and poor bile excretion to the gall bladder compared with uninjected embryos. Biliary defects were reproduced with the EGFR-blocker AG1478 alone or with Mo-arf6 at lower doses of each agent and rescued with arf6 mRNA. Conclusions: The BA-associated SNPs identify a chromosome 14q21.3 susceptibility locus encompassing the ARF6 gene. arf6 knockdown in zebrafish implicates early biliary dysgenesis as a basis for BA, and also suggests a role for EGFR signaling in BA pathogenesis

Spoligotyping and Drug Resistance Analysis of Mycobacterium tuberculosis Strains from National Survey in China

BACKGROUND: Tuberculosis (TB), caused by Mycobacterium tuberculosis complex (MTBC), is one of the major causes of death in the world today. Although China has the second largest global case rate of tuberculosis, a systematic study of TB prevalence in China has not been completed. From 2006 to 2007, the base line surveillance of tuberculosis was carried out by Ministry of Health, and more than 4000 representative strains were selected from 31 provinces in China. METHODOLOGY/PRINCIPAL FINDINGS: The aim of the present research was to survey the genotypes of representative Mycobacterium tuberculosis (M. tuberculosis) strains from China using spacer oligonucleotide typing (spoligotyping), and to analyze the relationship between genotype and drug resistance for the first time. A total of 4017 clinical isolates were collected from 2007 to 2008 throughout China. Among those M. tuberculosis isolates, 2500 (62.2%) isolates were Beijing genotypes. The percentage of Beijing genotypes in northern China was higher than in southern China (76.5% vs. 53.2%). Additionally, the frequencies of rifampin-resistant, ofloxacin-resistant and multidrug-resistant isolates were significantly higher in Beijing genotype strains than non-Beijing strains. Furthermore, a novel genotype named "China Southern genotype (CS)" was only isolated from Fujian and Guangdong provinces. Hence, it is very practical to uncover the reason for prevalence of the CS type in southern China. CONCLUSIONS/SIGNIFICANCE: In conclusion, Beijing family genotypes were still the predominant genotype throughout China, which exhibited a greater correlation with rifampin-resistance, ofloxacin-resistance and MDR phenotypes than other TB spoligotypes, and some regions of China showed several unique characters in the distribution of M. tuberculosis genotypes. Our research represents an important contribution for the TB control and research community, which completes broad pictures on drug resistance levels and distribution of M. tuberculosis strain types over China