Hyperinsulinism-hyperammonaemia syndrome: novel mutations in the GLUD1 gene and genotype-phenotype correlations

Background: Activating mutations in the GLUD1 gene (which encodes for the intra-mitochondrial enzyme glutamate dehydrogenase, GDH) cause the hyperinsulinism–hyperammonaemia (HI/HA) syndrome. Patients present with HA and leucine-sensitive hypoglycaemia. GDH is regulated by another intra-mitochondrial enzyme sirtuin 4 (SIRT4). Sirt4 knockout mice demonstrate activation of GDH with increased amino acid-stimulated insulin secretion. Objectives: To study the genotype–phenotype correlations in patients with GLUD1 mutations. To report the phenotype and functional analysis of a novel mutation (P436L) in the GLUD1 gene associated with the absence of HA. Patients and methods: Twenty patients with HI from 16 families had mutational analysis of the GLUD1 gene in view of HA (n=19) or leucine sensitivity (n=1). Patients negative for a GLUD1 mutation had sequence analysis of the SIRT4 gene. Functional analysis of the novel P436L GLUD1 mutation was performed. Results: Heterozygous missense mutations were detected in 15 patients with HI/HA, 2 of which are novel (N410D and D451V). In addition, a patient with a normal serum ammonia concentration (21 µmol/l) was heterozygous for a novel missense mutation P436L. Functional analysis of this mutation confirms that it is associated with a loss of GTP inhibition. Seizure disorder was common (43%) in our cohort of patients with a GLUD1 mutation. No mutations in the SIRT4 gene were identified. Conclusion: Patients with HI due to mutations in the GLUD1 gene may have normal serum ammonia concentrations. Hence, GLUD1 mutational analysis may be indicated in patients with leucine sensitivity; even in the absence of HA. A high frequency of epilepsy (43%) was observed in our patients with GLUD1 mutations

Does rapid urbanization aggravate health disparities? Reflections on the epidemiological transition in Pune, India

Background: Rapid urbanization in low- and middle-income countries reinforces risk and epidemiological transition in urban societies, which are characterized by high socioeconomic gradients. Limited availability of disaggregated morbidity data in these settings impedes research on epidemiological profiles of different population subgroups. Objective: The study aimed to analyze the epidemiological transition in the emerging megacity of Pune with respect to changing morbidity and mortality patterns, also taking into consideration health disparities among different socioeconomic groups. Design: A mixed-methods approach was used, comprising secondary analysis of mortality data, a survey among 900 households in six neighborhoods with different socioeconomic profiles, 46 in-depth interviews with laypeople, and expert interviews with 37 health care providers and 22 other health care workers. Results: The mortality data account for an epidemiological transition with an increasing number of deaths due to non-communicable diseases (NCDs) in Pune. The share of deaths due to infectious and parasitic diseases remained nearly constant, though the cause of deaths changed considerably within this group. The survey data and expert interviews indicated a slightly higher prevalence of diabetes and hypertension among higher socioeconomic groups, but a higher incidence and more frequent complications and comorbidities in lower socioeconomic groups. Although the self-reported morbidity for malaria, gastroenteritis, and tuberculosis did not show a socioeconomic pattern, experts estimated the prevalence in lower socioeconomic groups to be higher, though all groups in Pune would be affected. Conclusions: The rising burden of NCDs among all socioeconomic groups and the concurrent persistence of communicable diseases pose a major challenge for public health. Improvement of urban health requires a stronger focus on health promotion and disease prevention for all socioeconomic groups with a holistic understanding of urban health. In order to derive evidence-based solutions and interventions, routine surveillance data become indispensable

Comparison of Data Mining Techniques for Predicting Compressive Strength of Environmentally Friendly Concrete

This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/10.1061/%28ASCE%29CP.1943-5487.0000596 With its growing emphasis on sustainability, the construction industry is increasingly interested in environmentally friendly concrete produced by using alternative and/or recycled waste materials. However, the wide application of such concrete is hindered by the lack of understanding of the impacts of these materials on concrete properties. This research investigates and compares the performance of nine data mining models in predicting the compressive strength of a new type of concrete containing three alternative materials as fly ash, Haydite lightweight aggregate, and portland limestone cement. These models include three advanced predictive models (multilayer perceptron, support vector machines, and Gaussian processes regression), four regression tree models (M5P, REPTree, M5-Rules, and decision stump), and two ensemble methods (additive regression and bagging) with each of the seven individual models used as the base classifier

Application of the Shiono and Knight Method in asymmetric compound channels with different side slopes of the internal wall

The Shiono and Knight Method (SKM) is widely used to predict the lateral distribution of depth-averaged velocity and boundary shear stress for flows in compound channels. Three calibrating coefficients need to be estimated for applying the SKM, namely eddy viscosity coefficient (λ), friction factor (f) and secondary flow coefficient (k). There are several tested methods which can satisfactorily be used to estimate λ, f. However, the calibration of secondary flow coefficients k to account for secondary flow effects correctly is still problematic. In this paper, the calibration of secondary flow coefficients is established by employing two approaches to estimate correct values of k for simulating asymmetric compound channel with different side slopes of the internal wall. The first approach is based on Abril and Knight (2004) who suggest fixed values for main channel and floodplain regions. In the second approach, the equations developed by Devi and Khatua (2017) that relate the variation of the secondary flow coefficients with the relative depth (β) and width ratio (α) are used. The results indicate that the calibration method developed by Devi and Khatua (2017) is a better choice for calibrating the secondary flow coefficients than using the first approach which assumes a fixed value of k for different flow depths. The results also indicate that the boundary condition based on the shear force continuity can successfully be used for simulating rectangular compound channels, while the continuity of depth-averaged velocity and its gradient is accepted boundary condition in simulations of trapezoidal compound channels. However, the SKM performance for predicting the boundary shear stress over the shear layer region may not be improved by only imposing the suitable calibrated values of secondary flow coefficients. This is because difficulties of modelling the complex interaction that develops between the flows in the main channel and on the floodplain in this region

Comparative expression profile of orphan receptor tyrosine kinase ROR1 in Iranian patients with lymphoid and myeloid leukemias

It has recently been shown that ROR1, a member of the receptor tyrosine kinase family, is overexpressed in leukemic B cells of Chronic Lymphocytic Leukemia (CLL) and a subset of Acute Lymphoblastic Leukemia (ALL). In this comparative study the expression profile of ROR1 mRNA was investigated in Iranian patients with CLL and Acute Myelogenous Leukemia (AML) and the results were compared with those previously reported in our Iranian ALL patients. RT-PCR was performed on bone marrow and/or peripheral blood samples of 84 CLL and 12 AML patients. CLL samples were classified into immunoglobulin heavy chain variable region (IGHV) gene mutated (n = 55) and unmutated (n = 29) and also indolent (n = 42) and progressive (n = 39) subtypes. ROR1 expression was identified in 94% of our CLL patients, but none of the AML patients expressed ROR1. No significant differences were observed between different CLL subtypes for ROR1 expression. Taken together the present data and our previous results on ROR1 expression in ALL, our findings propose ROR1 as a tumor-associated antigen overexpressed in a large proportion of lymphoid (CLL and ALL), but not myeloid (AML) leukemias. Expression of ROR1 seems to be associated to lineage and differentiation stages of leukemic cells with a potential implication for immunotherapy.Tehran University of Medical SciencesPublishe

The nuclear receptors of Biomphalaria glabrata and Lottia gigantea: Implications for developing new model organisms

© 2015 Kaur et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedNuclear receptors (NRs) are transcription regulators involved in an array of diverse physiological functions including key roles in endocrine and metabolic function. The aim of this study was to identify nuclear receptors in the fully sequenced genome of the gastropod snail, Biomphalaria glabrata, intermediate host for Schistosoma mansoni and compare these to known vertebrate NRs, with a view to assessing the snail's potential as a invertebrate model organism for endocrine function, both as a prospective new test organism and to elucidate the fundamental genetic and mechanistic causes of disease. For comparative purposes, the genome of a second gastropod, the owl limpet, Lottia gigantea was also investigated for nuclear receptors. Thirty-nine and thirty-three putative NRs were identified from the B. glabrata and L. gigantea genomes respectively, based on the presence of a conserved DNA-binding domain and/or ligand-binding domain. Nuclear receptor transcript expression was confirmed and sequences were subjected to a comparative phylogenetic analysis, which demonstrated that these molluscs have representatives of all the major NR subfamilies (1-6). Many of the identified NRs are conserved between vertebrates and invertebrates, however differences exist, most notably, the absence of receptors of Group 3C, which includes some of the vertebrate endocrine hormone targets. The mollusc genomes also contain NR homologues that are present in insects and nematodes but not in vertebrates, such as Group 1J (HR48/DAF12/HR96). The identification of many shared receptors between humans and molluscs indicates the potential for molluscs as model organisms; however the absence of several steroid hormone receptors indicates snail endocrine systems are fundamentally different.The National Centre for the Replacement, Refinement and Reduction of Animals in Research, Grant Ref:G0900802 to CSJ, LRN, SJ & EJR [www.nc3rs.org.uk]

Application of the Shiono and Knight Method in asymmetric compound channels with different side slopes of the internal wall

The Shiono and Knight Method (SKM) is widely used to predict the lateral distribution of depth-averaged velocity and boundary shear stress for flows in compound channels. Three calibrating coefficients need to be estimated for applying the SKM, namely eddy viscosity coefficient (λ), friction factor (f) and secondary flow coefficient (k). There are several tested methods which can satisfactorily be used to estimate λ, f. However, the calibration of secondary flow coefficients k to account for secondary flow effects correctly is still problematic. In this paper, the calibration of secondary flow coefficients is established by employing two approaches to estimate correct values of k for simulating asymmetric compound channel with different side slopes of the internal wall. The first approach is based on Abril and Knight (2004) who suggest fixed values for main channel and floodplain regions. In the second approach, the equations developed by Devi and Khatua (2017) that relate the variation of the secondary flow coefficients with the relative depth (β) and width ratio (α) are used. The results indicate that the calibration method developed by Devi and Khatua (2017) is a better choice for calibrating the secondary flow coefficients than using the first approach which assumes a fixed value of k for different flow depths. The results also indicate that the boundary condition based on the shear force continuity can successfully be used for simulating rectangular compound channels, while the continuity of depth-averaged velocity and its gradient is accepted boundary condition in simulations of trapezoidal compound channels. However, the SKM performance for predicting the boundary shear stress over the shear layer region may not be improved by only imposing the suitable calibrated values of secondary flow coefficients. This is because difficulties of modelling the complex interaction that develops between the flows in the main channel and on the floodplain in this region

Observation of mesoscopic crystalline structures in a two-dimensional Rydberg gas

The ability to control and tune interactions in ultracold atomic gases has paved the way towards the realization of new phases of matter. Whereas experiments have so far achieved a high degree of control over short-ranged interactions, the realization of long-range interactions would open up a whole new realm of many-body physics and has become a central focus of research. Rydberg atoms are very well-suited to achieve this goal, as the van der Waals forces between them are many orders of magnitude larger than for ground state atoms. Consequently, the mere laser excitation of ultracold gases can cause strongly correlated many-body states to emerge directly when atoms are transferred to Rydberg states. A key example are quantum crystals, composed of coherent superpositions of different spatially ordered configurations of collective excitations. Here we report on the direct measurement of strong correlations in a laser excited two-dimensional atomic Mott insulator using high-resolution, in-situ Rydberg atom imaging. The observations reveal the emergence of spatially ordered excitation patterns in the high-density components of the prepared many-body state. They have random orientation, but well defined geometry, forming mesoscopic crystals of collective excitations delocalised throughout the gas. Our experiment demonstrates the potential of Rydberg gases to realise exotic phases of matter, thereby laying the basis for quantum simulations of long-range interacting quantum magnets.Comment: 10 pages, 7 figure

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196