Cognitive modelling and the behaviour genetics of reading

While it is well known that reading is highly heritable, less has been understood about the bases of these genetic influences. In this paper, we review the research that we have been conducting in recent years to examine genetic and environmental influences on the particular reading processes specified in the dual-route cognitive model of reading. We argue that a detailed understanding of the role of genetic factors in reading acquisition requires the delineation and measurement of precise phenotypes, derived from well-articulated models of the reading process. We report evidence for independent genetic influences on the lexical and nonlexical reading processes represented in the dual-route model, based on studies of children with particular subtypes of dyslexia, and on univariate and multivariate genetic modelling of reading performance in the normally reading population.

The generational transmission of socioeconomic inequalities in child cognitive development and emotional health

Socioeconomic inequalities in the health of adults have been largely attributed to lifestyle inequalities. The cognitive development (CD) and emotional health (EH) of the child provides a basis for many of the health-related behaviours which are observed in adulthood. There has been relatively little attention paid to the way CID and EH are transmitted in the foetal and childhood periods, even though these provide a foundation for subsequent socioeconomic inequalities in adult health. The Mater-University of Queensland Study of Pregnancy (MUSP) is a large, prospective, pre-birth cohort study which enrolled 8556 pregnant women at their first clinic visit over the period 1981-1983. These mothers (and their children) have been followed up at intervals until 14 years after the birth. The socioeconomic status of the child was measured using maternal age, family income, and marital status and the grandfathers' occupational status. Measures of child CD and child EH were obtained at 5 and 14 years of age. Child smoking at 14 years of age was also determined. Family income was related to all measures of child CD and EH and smoking, independently of all other indicators of the socioeconomic status of the child. In addition, the grandfathers' occupational status was independently related to child CD (at 5 and 14 years of age). Children from socioeconomically disadvantaged families (previous generations' socioeconomic status as well as current socioeconomic status) begin their lives with a poorer platform of health and a reduced capacity to benefit from the economic and social advances experienced by the rest of society. (C) 2003 Elsevier Ltd. All rights reserved.

Cognitive disorders and neurogenesis deficits in Huntington's disease mice are rescued by fluoxetine

Huntington's disease (HD) is a neurodegenerative disorder caused by an expanded CAG trinucleotide repeat encoding an extended polyglutamine tract in the huntingtin protein. Affected individuals display progressive motor, cognitive and psychiatric symptoms (including depression), leading to terminal decline. Given that transgenic HD mice have decreased hippocampal cell proliferation and that a deficit in neurogenesis has been postulated as an underlying cause of depression, we hypothesized that decreased hippocampal neurogenesis contributes to depressive symptoms and cognitive decline in HD. Fluoxetine, a serotonin-reuptake inhibitor commonly prescribed for the treatment of depression, is known to increase neurogenesis in the dentate gyrus of wild-type mouse hippocampus. Here we show that hippocampal-dependent cognitive and depressive-like behavioural symptoms occur in HD mice, and that the administration of fluoxetine produces a marked improvement in these deficits. Furthermore, fluoxetine was found to rescue deficits of neurogenesis and volume loss in the dentate gyrus of HD mice.

Socioeconomic position, cognitive function, and clustering of cardiovascular risk factors in adolescence: Findings from the Mater University Study of Pregnancy and its outcomes

Objectives: The objectives of this study were to examine the extent of clustering of smoking, high levels of television watching, overweight, and high blood pressure among adolescents and whether this clustering varies by socioeconomic position and Cognitive function. Methods: This study was a cross-sectional analysis of 3613 (1742 females) participants of an Australian birth cohort who were examined at age 14. Results: Three hundred fifty-three (9.8%) of the participants had co-occurrence of three or four risk factors. Risk factors clustered in these adolescents with a greater number of participants than would be predicted by assumptions of independence having no risk factors and three or four risk factors. The extent of clustering tended to be greater in those from lower-income families and among those with lower cognitive function. The age-adjusted ratio of observed to expected cooccurrence of three or four risk factors was 2.70 (95% confidence interval [Cl], 1.80-4.06) among those from low-income families and 1.70 (95% Cl, 1.34-2.16) among those from more affluent families. The ratio among those with low Raven's scores (nonverbal reasoning) was 2.36 (95% Cl, 1.69-3.30) and among those with higher scores was 1.51 (95% Cl, 1.19-1.92); similar results for the WRAT 3 score (reading ability) were 2.69 (95% Cl, 1.85-3.94) and 1.68 (95% Cl, 1.34-2.11). Clustering did not differ by sex. Conclusion: Among adolescents, coronary heart disease risk factors cluster, and there is some evidence that this clustering is greater among those from families with low income and those who have lower cognitive function.

Modeling of adsorption on nongraphitized carbon surface: GCMC simulation studies and comparison with experimental data

We model nongraphitized carbon black surfaces and investigate adsorption of argon on these surfaces by using the grand canonical Monte Carlo simulation. In this model, the nongraphitized surface is modeled as a stack of graphene layers with some carbon atoms of the top graphene layer being randomly removed. The percentage of the surface carbon atoms being removed and the effective size of the defect ( created by the removal) are the key parameters to characterize the nongraphitized surface. The patterns of adsorption isotherm and isosteric heat are particularly studied, as a function of these surface parameters as well as pressure and temperature. It is shown that the adsorption isotherm shows a steplike behavior on a perfect graphite surface and becomes smoother on nongraphitized surfaces. Regarding the isosteric heat versus loading, we observe for the case of graphitized thermal carbon black the increase of heat in the submonolayer coverage and then a sharp decline in the heat when the second layer is starting to form, beyond which it increases slightly. On the other hand, the isosteric heat versus loading for a highly nongraphitized surface shows a general decline with respect to loading, which is due to the energetic heterogeneity of the surface. It is only when the fluid-fluid interaction is greater than the surface energetic factor that we see a minimum-maximum in the isosteric heat versus loading. These simulation results of isosteric heat agree well with the experimental results of graphitization of Spheron 6 (Polley, M. H.; Schaeffer, W. D.; Smith, W. R. J. Phys. Chem. 1953, 57, 469; Beebe, R. A.; Young, D. M. J. Phys. Chem. 1954, 58, 93). Adsorption isotherms and isosteric heat in pores whose walls have defects are also studied from the simulation, and the pattern of isotherm and isosteric heat could be used to identify the fingerprint of the surface.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

Identification of success and failure factors for technology transfer in biotechnology: case studies and surveys from Academic Sinica in Taiwan

Academia Sinica is the leading research institute in Taiwan founded in 1928. Its Office of Technology Transfer (OTT) was established in 1998. It made great efforts to dramatically turn around the technology transfer activity of Academia Sinica, especially in biotechnology. Academia Sinica has more than 80 cases of experience in biotechnology transfer with companies in Taiwanese industry in the past five years. The purpose of this study is to identify potential success and failure factors for biotechnology transfer in Taiwan. Eight cases were studied through in-depth interview. The results of the analysis were used to design two surveys to further investigate 81 cases (48 successful and 33 failure cases) of biotechnology transfer in Academia Sinica from 1999–2003. The results indicated that 10 of the 14 success factors were cited in more than 40% of the cases as contributing to the success of technology transfer. By contrast, only 5 out of 16 key factors were present in more than 30% of the failure cases.