Mutational analysis of DAX1 in patients with hypogonadotropic hypogonadism or pubertal delay

Although delayed puberty is relatively common and often familial, its molecular and pathophysiologic basis is poorly understood. In contrast, the molecular mechanisms underlying some forms of hypogonadotropic hypogonadism (HH) are clearer, following the description of mutations in the genes KAL, GNRHR, and PROP1. Mutations in another gene, DAX1 (AHC), cause X-linked adrenal hypoplasia congenita and HH. Affected boys usually present with primary adrenal failure in infancy or childhood and HH at the expected time of puberty.DAX1 mutations have also been reported to occur with a wider spectrum of clinical presentations. These cases include female carriers of DAX1 mutations with marked pubertal delay and a male with incomplete BH and mild adrenal insufficiency in adulthood. Given this emerging phenotypic spectrum of clinical presentation in men and women with DAX1 mutations, we hypothesized that DAX1 might be a candidate gene for mutation in patients with idiopathic sporadic or familial HH or constitutional delay of puberty. Direct sequencing of DAX1 was performed in 106 patients, including 85 (80 men and 5 women) with sporadic HH or constitutional delay of puberty and patients from 21 kindreds with familial forms of these disorders. No DAX1 mutations were found in these groups of patients, although silent single nucleotide polymorphisms were identified (T114C, G498A). This study suggests that mutations in DAX1 are unlikely to be a common cause of HH or pubertal delay in the absence of a concomitant history of adrenal insufficiency

Grassroots football club stakeholders' sponsorship: the role of happiness and shared values

Purpose: This research serves to determine causal configurations of corporate social responsibility (CSR) conditions that best influences grassroots football club stakeholders to meet a sponsor's goals through promotional activity. Design/methodology/approach: The research uses a case study of the Essex Alliance League, a local amateur football league in England. Firstly, semi-structured interviews were held with multiple stakeholders to understand the ecosystem of grassroots football. From here, further semi-structured interviews were held with club sponsors to identify the conditions of CSR. This allowed the research to then issue a survey from which results were analysed and discussed using fuzzy set Qualitative Comparative Analysis (fsQCA). Findings: The ecosystem of grassroots football is formed by a myriad of stakeholders operating at a national level, all the way to more local governance structures within which the business-club relationship exists. Sponsors identified three main conditions of CSR: shared values, self-congruity, and happiness. However, following fsQCA, two pathways were found: (1) presence of shared values, and (2) presence of happiness with the absence of self-congruity. Practical implications: For practitioners, adaptations can be made for clubs to attract and maintain sponsorship as businesses seek to use grassroots sport as a channel for their own CSR objectives. To attract long term sponsorship, club managers are recommended to maintain long-term relationships with business owners especially in relation to personal values, fit, and happiness. As such, the responsibility of the club to ensure its stakeholders engage in promotional activity on behalf of their sponsor will help in maximising the financial value over multiple seasons. Originality/value: Where fertile ground for academic analysis in grassroots football is present, this research investigates CSR activity at this level of football, where most research is more concerned with professional levels of the game. Furthermore, this research reaches into the sport ecosystem through an understanding of co-created values between organisations in this exchange of shared values to meet common objectives

Interaction imaging with amplitude-dependence force spectroscopy

Knowledge of surface forces is the key to understanding a large number of processes in fields ranging from physics to material science and biology. The most common method to study surfaces is dynamic atomic force microscopy (AFM). Dynamic AFM has been enormously successful in imaging surface topography, even to atomic resolution, but the force between the AFM tip and the surface remains unknown during imaging. Here, we present a new approach that combines high accuracy force measurements and high resolution scanning. The method, called amplitude-dependence force spectroscopy (ADFS) is based on the amplitude-dependence of the cantilever's response near resonance and allows for separate determination of both conservative and dissipative tip-surface interactions. We use ADFS to quantitatively study and map the nano-mechanical interaction between the AFM tip and heterogeneous polymer surfaces. ADFS is compatible with commercial atomic force microscopes and we anticipate its wide-spread use in taking AFM toward quantitative microscopy

Clinical and functional effects of mutations in the DAX-1 gene in patients with adrenal hypoplasia congenita

Adrenal hypoplasia congenita (AHC) is an X-linked disorder caused by mutations in a gene referred to as DAX-1. AHC is characterized by adrenal insufficiency and failure to undergo puberty because of hypogonadotropic hypogonadism. The DAX-1 protein is structurally related to orphan nuclear receptors, although it lacks the characteristic zinc finger DNA-binding domain that is highly conserved in other members of this family. In this report, we describe the clinical features and genetic alterations in six families with AHC. These patients reveal the variable clinical presentation of adrenal insufficiency in AHC and underscore the importance of considering this diagnosis. Nonsense mutations that introduce a stop codon were found in three cases (W171X, W171X, Y399X). Frameshift mutations (405delT, 501delA, and 702delC), each of which resulted in a premature stop codon at amino acid 263, were found in the other three families. Three of these mutations (Y399X, 405delT, 702delC) are novel. Using transient gene expression assays to assess DAX-1 function, these mutations were shown to eliminate the ability of DAX-1 to repress the transcription of genes that are stimulated by a related nuclear receptor, steroidogenic factor-1. These studies reveal the variable clinical presentation of DAX-1 mutations and emphasize the value genetic testing in boys with primary adrenal insufficiency and suspected X-linked AHC

Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems

We present the results of the first application in the naval architecture field of a methodology based on active subspaces properties for parameter space reduction. The physical problem considered is the one of the simulation of the hydrodynamic flow past the hull of a ship advancing in calm water. Such problem is extremely relevant at the preliminary stages of the ship design, when several flow simulations are typically carried out by the engineers to assess the dependence of the hull total resistance on the geometrical parameters of the hull, and others related with flows and hull properties. Given the high number of geometric and physical parameters which might affect the total ship drag, the main idea of this work is to employ the active subspaces properties to identify possible lower dimensional structures in the parameter space. Thus, a fully automated procedure has been implemented to produce several small shape perturbations of an original hull CAD geometry, in order to exploit the resulting shapes and to run high fidelity flow simulations with different structural and physical parameters as well, and then collect data for the active subspaces analysis. The free form deformation procedure used to morph the hull shapes, the high fidelity solver based on potential flow theory with fully nonlinear free surface treatment, and the active subspaces analysis tool employed in this work have all been developed and integrated within SISSA mathLab as open source tools. The contribution will also discuss several details of the implementation of such tools, as well as the results of their application to the selected target engineering problem

A Low Dimensional Description of Globally Coupled Heterogeneous Neural Networks of Excitatory and Inhibitory Neurons

Neural networks consisting of globally coupled excitatory and inhibitory nonidentical neurons may exhibit a complex dynamic behavior including synchronization, multiclustered solutions in phase space, and oscillator death. We investigate the conditions under which these behaviors occur in a multidimensional parametric space defined by the connectivity strengths and dispersion of the neuronal membrane excitability. Using mode decomposition techniques, we further derive analytically a low dimensional description of the neural population dynamics and show that the various dynamic behaviors of the entire network can be well reproduced by this reduced system. Examples of networks of FitzHugh-Nagumo and Hindmarsh-Rose neurons are discussed in detail

Approaching the diagnosis of growth-restricted neonates: a cohort study

<p>Abstract</p> <p>Background</p> <p>The consequences of <it>in utero </it>growth restriction have been attracting scholarly attention for the past two decades. Nevertheless, the diagnosis of growth-restricted neonates is as yet an unresolved issue. Aim of this study is the evaluation of the performance of simple, common indicators of nutritional status, which are used in the identification of growth-restricted neonates.</p> <p>Methods</p> <p>In a cohort of 418 consecutively born term and near term neonates, four widely used anthropometric indices of body proportionality and subcutaneous fat accretion were applied, singly and in combination, as diagnostic markers for the detection of growth-restricted babies. The concordance of the indices was assessed in terms of positive and negative percent agreement and of Cohen's kappa.</p> <p>Results</p> <p>The agreement between the anthropometric indices was overall poor with a highest positive percent agreement of 62.5% and a lowest of 27.9% and the κ ranging between 0.19 and 0.58. Moreover, 6% to 32% of babies having abnormal values in just one index were apparently well-grown and the median birth weight centile of babies having abnormal values of either of two indices was found to be as high as the 46^thcentile for gestational age (95%CI 35.5 to 60.4 and 29.8 to 63.9, respectively). On the contrary, the combination of anthropometric indices appeared to have better distinguishing properties among apparently and not apparently well-grown babies. The median birth weight centile of babies having abnormal values in two (or more) indices was the 11^thcentile for gestational age (95%CI 6.3 to 16.3).</p> <p>Conclusions</p> <p>Clinical assessment and anthropometric indices in combination can define a reference standard with better performance compared to the same indices used in isolation. This approach offers an easy-to-use tool for bedside diagnosis of <it>in utero </it>growth restriction.</p

Maintaining extensivity in evolutionary multiplex networks

In this paper, we explore the role of network topology on maintaining the extensive property of entropy. We study analytically and numerically how the topology contributes to maintaining extensivity of entropy in multiplex networks, i.e. networks of subnetworks (layers), by means of the sum of the positive Lyapunov exponents, HKS, a quantity related to entropy. We show that extensivity relies not only on the interplay between the coupling strengths of the dynamics associated to the intra (short-range) and inter (long-range) interactions, but also on the sum of the intra-degrees of the nodes of the layers. For the analytically treated networks of size N, among several other results, we show that if the sum of the intra-degrees (and the sum of inter-degrees) scales as N?+1, ? > 0, extensivity can be maintained if the intra-coupling (and the inter-coupling) strength scales as N??, when evolution is driven by the maximisation of HKS. We then verify our analytical results by performing numerical simulations in multiplex networks formed by electrically and chemically coupled neurons

Do brain networks evolve by maximizing their information flow capacity?

We propose a working hypothesis supported by numerical simulations that brain networks evolve based on the principle of the maximization of their internal information flow capacity. We find that synchronous behavior and capacity of information flow of the evolved networks reproduce well the same behaviors observed in the brain dynamical networks of Caenorhabditis elegans and humans, networks of Hindmarsh-Rose neurons with graphs given by these brain networks. We make a strong case to verify our hypothesis by showing that the neural networks with the closest graph distance to the brain networks of Caenorhabditis elegans and humans are the Hindmarsh-Rose neural networks evolved with coupling strengths that maximize information flow capacity. Surprisingly, we find that global neural synchronization levels decrease during brain evolution, reflecting on an underlying global no Hebbian-like evolution process, which is driven by no Hebbian-like learning behaviors for some of the clusters during evolution, and Hebbian-like learning rules for clusters where neurons increase their synchronization