The Gomi legacy

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A novel CHD7 mutation in an adolescent presenting with growth and pubertal delay.

Mutations in the CHD7 gene, encoding for the chromodomain helicase DNA-binding protein 7, are found in approximately 60% of individuals with CHARGE syndrome (coloboma, heart defects, choanal atresia, retarded growth and development, genital hypoplasia, ear abnormalities and/or hearing loss). Herein, we present a clinical case of a 14-year-old male presenting for evaluation of poor growth and pubertal delay highlighting the diagnostic challenges of CHARGE syndrome. The patient was born full term and underwent surgery at 5 days of life for bilateral choanal atresia. Developmental milestones were normally achieved. At age 14 his height and weight were -2.04 and -1.74 standard deviation score respectively. He had anosmia as well as prepubertal testes and micropenis (4 cm×1 cm). The biological profile showed low basal serum testosterone and gonadotropins (testosterone, 0.2 nmol/L; luteinizing hormone, 0.5 U/L; follicle-stimulating hormone, 1.3 U/L), and otherwise normal pituitary function and normal imaging of the hypothalamic-pituitary area. The constellation of choanal atresia, anosmia, mild dysmorphic features, micropenis and delayed puberty were suggestive of CHARGE syndrome. Targeted genetic testing of CHD7 was performed revealing a de novo heterozygous CHD7 mutation (c.4234T>G [p.Tyr1412Asp]). Further paraclinical investigations confirmed CHARGE syndrome. Despite the presence of suggestive features, CHARGE syndrome remained undiagnosed in this patient until adolescence. Genetic testing helps clarify the phenotypic and genotypic spectrum to facilitate diagnosis, thus promoting optimal follow-up, treatment, and appropriate genetic counselling

Evolving Synaptic Plasticity with an Evolutionary Cellular Development Model

Since synaptic plasticity is regarded as a potential mechanism for memory formation and learning, there is growing interest in the study of its underlying mechanisms. Recently several evolutionary models of cellular development have been presented, but none have been shown to be able to evolve a range of biological synaptic plasticity regimes. In this paper we present a biologically plausible evolutionary cellular development model and test its ability to evolve different biological synaptic plasticity regimes. The core of the model is a genomic and proteomic regulation network which controls cells and their neurites in a 2D environment. The model has previously been shown to successfully evolve behaving organisms, enable gene related phenomena, and produce biological neural mechanisms such as temporal representations. Several experiments are described in which the model evolves different synaptic plasticity regimes using a direct fitness function. Other experiments examine the ability of the model to evolve simple plasticity regimes in a task -based fitness function environment. These results suggest that such evolutionary cellular development models have the potential to be used as a research tool for investigating the evolutionary aspects of synaptic plasticity and at the same time can serve as the basis for novel artificial computational systems

Nature of the Earth's earliest crust from hafnium isotopes in single detrital zircons

Continental crust forms from, and thus chemically depletes, the Earth's mantle. Evidence that the Earth's mantle was already chemically depleted by melting before the formation of today's oldest surviving crust has been presented in the form of Sm-Nd isotope studies of 3.8-4.0 billion years old rocks from Greenland(1-5) and Canada(5-7). But this interpretation has been questioned because of the possibility that subsequent perturbations may have re-equilibrated the neodymium-isotope compositions of these rocks(8). Independent and more robust evidence for the origin of the earliest crust and depletion of the Archaean mantle can potentially be provided by hafnium-isotope compositions of zircon, a mineral whose age can be precisely determined by U-Pb dating, and which can survive metamorphisms(4). But the amounts of hafnium in single zircon grains are too small for the isotopic composition to be precisely analysed by conventional methods. Here we report hafnium-isotope data, obtained using the new technique of multiple-collector plasma-source mass spectrometry(9), for 37 individual grains of the oldest known terrestrial zircons (from the Narryer Gneiss Complex, Australia, with U-Pb ages of up to 4.14 Gyr (refs 10-13)). We find that none of the grains has a depleted mantle signature, but that many were derived from a source with a hafnium-isotope composition similar to that of chondritic meteorites. Furthermore, more than half of the analysed grains seem to have formed by remelting of significantly older crust, indicating that crustal preservation and subsequent reworking might have been important processes from earliest times.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62681/1/399252a0.pd

Neural networks for genetic epidemiology: past, present, and future

During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN) are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes