Origins of the sex differences in handedness and mental rotation ability : genetic, environmental and hormonal effects

In humans, well-replicated and robust sex differences in cognitive functions exist for handedness and mental rotation ability. A common characteristic in human cognitive functions is the lateralization of language functions. Handedness is a common measure of laterality and is related to language lateralization. The prevalence of left-handedness is higher in males than in females, the male to female ratio being about 1.2. Among cognitive abilities, the largest sex difference is evident in the Vandenberg and Kuse Mental Rotation Test (MRT), which requires the ability to rotate objects in mental space. On average, males achieve scores one standard deviation higher than females in the MRT. The present thesis investigated the origins of the sex differences in laterality and spatial ability as represented by handedness and mental rotation ability, respectively. Two population-based Finnish twin cohorts were utilized in this study. Handedness was studied in 25 810 twins and 4068 singletons born before 1958 from the Older Finnish Twin Cohort, and in 4736 twins born in 1983-87 from the FinnTwin12. MRT was studied in a sub-sample of 804 young adult participants from the FinnTwin12 sample. The main findings of this study were: 1) the prevalence of left-handedness was higher among males than among females in both singletons and in twins; 2) males had significantly higher scores than females in MRT; 3) about one quarter of the variance in handedness and about half of the variance in MRT was explained by genetic effects, whereas the remainder of the variance in these traits was explained by environmental effects unique to each individual. The magnitude of the genetic effects was similar in both sexes; 4) left-handedness was significantly less common in female co-twins of a male than in female co-twins of a female, and female co-twins of a male scored significantly higher than did female co-twins of a female in the Mental Rotation Test. This dissertation discusses whether these differences between females from opposite- and same-sex twin pairs are due to the prenatal transfer of testosterone from the male fetus in females with male co-twins or whether they arise from postnatal socialization effects.

Genetic variation in the LDL receptor-related protein 5 (LRP5) gene : Association with bone health and metabolic parameters

Bone mass accrual and maintenance are regulated by a complex interplay between genetic and environmental factors. Recent studies have revealed an important role for the low-density lipoprotein receptor-related protein 5 (LRP5) in this process. The aim of this thesis study was to identify novel variants in the LRP5 gene and to further elucidate the association of LRP5 and its variants with various bone health related clinical characteristics. The results of our studies show that loss-of-function mutations in LRP5 cause severe osteoporosis not only in homozygous subjects but also in the carriers of these mutations, who have significantly reduced bone mineral density (BMD) and increased susceptibility to fractures. In addition, we demonstrated for the first time that a common polymorphic LRP5 variant (p.A1330V) was associated with reduced peak bone mass, an important determinant of BMD and osteoporosis in later life. The results from these two studies are concordant with results seen in other studies on LRP5 mutations and in association studies linking genetic variation in LRP5 with BMD and osteoporosis. Several rare LRP5 variants were identified in children with recurrent fractures. Sequencing and multiplex ligation-dependent probe amplification (MLPA) analyses revealed no disease-causing mutations or whole-exon deletions. Our findings from clinical assessments and family-based genotype-phenotype studies suggested that the rare LRP5 variants identified are not the definite cause of fractures in these children. Clinical assessments of our study subjects with LPR5 mutations revealed an unexpectedly high prevalence of impaired glucose tolerance and dyslipidaemia. Moreover, in subsequent studies we discovered that common polymorphic LRP5 variants are associated with unfavorable metabolic characteristics. Changes in lipid profile were already apparent in pre-pubertal children. These results, together with the findings from other studies, suggest an important role for LRP5 also in glucose and lipid metabolism. Our results underscore the important role of LRP5 not only in bone mass accrual and maintenance of skeletal health but also in glucose and lipid metabolism. The role of LRP5 in bone metabolism has long been studied, but further studies with larger study cohorts are still needed to evaluate the specific role of LRP5 variants as metabolic risk factors.

Genetic characterization of Indian type O FMD virus 3A region in context with host cell preference

The 3A region of foot-and-mouth disease virus has been implicated in host range and virulence. For example, amino acid deletions in the porcinophilic strain (O/TAW/97) at 93-102 aa of the 153 codons long 3A protein have been recognized as the determinant of species specificity. In the present study, 18 type 0 FMDV isolates from India were adapted in different cell culture systems and the 3A sequence was analyzed. These isolates had complete 3A coding sequence (153 aa) and did not exhibit growth restriction in cells based on species of origin. The 3A region was found to be highly conserved at N-terminal half (1-75 aa) but exhibited variability or substitutions towards C-terminal region (80-153). Moreover the amino acid substitutions were more frequent in recent Indian buffalo isolates but none of the Indian isolates showed deletion in 3A protein, which may be the reason for the absence of host specificity in vitro. Further inclusive analysis of 3A region will reveal interesting facts about the variability of FMD virus 3A region in an endemic environment. (C) 2010 Elsevier B.V. All rights reserved.

Analysis of Dynamic Heterogeneity in a Glass Former from the Spatial Correlations of Mobility

The growth of characteristic length scales associated with dynamic heterogeneity in glass-forming liquids is investigated in an extensive computational study of a four-point, time-dependent structure factor defined from spatial correlations of mobility, for a model liquid for system sizes extending up to 351 232 particles, in constant-energy and constant-temperature ensembles. Our estimates for dynamic correlation lengths and susceptibilities are consistent with previous results from finite size scaling. We find scaling exponents that are inconsistent with predictions from inhomogeneous mode coupling theory and a recent simulation confirmation of these predictions.

Genetic algorithm for satellite customer assignment

The problem of assigning customers to satellite channels is considered. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of this approach with the standard optimization method is presented to show the advantages of this approach in terms of computation time

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Communication: Evidence of dynamic heterogeneity in glassy polymer monolayers from interface microrheology measurements

We have developed a novel nanoparticle tracking based interface microrheology technique to perform in situ studies on confined complex fluids. To demonstrate the power of this technique, we show, for the first time, how in situ glass formation in polymers confined at air-water interface can be directly probed by monitoring variation of the mean square displacement of embedded nanoparticles as a function of surface density. We have further quantified the appearance of dynamic heterogeneity and hence vitrification in polymethyl methacrylate monolayers above a certain surface density, through the variation of non-Gaussian parameter of the probes. (C) 2010 American Institute of Physics. [doi:10.1063/1.3471584].

Cognitive Functioning in Alcohol and Other Substance Use Disorders in Young Adulthood : A Genetic Epidemiological Study

Alcohol and other substance use disorders (SUDs) result in great costs and suffering for individuals and families and constitute a notable public health burden. A multitude of factors, ranging from biological to societal, are associated with elevated risk of SUDs, but at the level of individuals, one of the best predictors is a family history of SUDs. Genetically informative twin and family studies have consistently indicated this familial risk to be mainly genetic. In addition, behavioral and temperamental factors such as early initiation of substance use and aggressiveness are associated with the development of SUDs. These familial, behavioral and temperamental risk factors often co-occur, but their relative importance is not well known. People with SUDs have also been found to differ from healthy controls in various domains of cognitive functioning, with poorer verbal ability being among the most consistent findings. However, representative population-based samples have rarely been used in neuropsychological studies of SUDs. In addition, both SUDs and cognitive abilities are influenced by genetic factors, but whether the co-variation of these traits might be partly explained by overlapping genetic influences has not been studied. Problematic substance use also often co-occurs with low educational level, but it is not known whether these outcomes share part of their underlying genetic influences. In addition, educational level may moderate the genetic etiology of alcohol problems, but gene-environment interactions between these phenomena have also not been widely studied. The incidence of SUDs peaks in young adulthood rendering epidemiological studies in this age group informative. This thesis investigated cognitive functioning and other correlates of SUDs in young adulthood in two representative population-based samples of young Finnish adults, one of which consisted of monozygotic and dizygotic twin pairs enabling genetically informative analyses. Using data from the population-based Mental Health in Early Adulthood in Finland (MEAF) study (n=605), the lifetime prevalence of DSM-IV any substance dependence or abuse among persons aged 21—35 years was found to be approximately 14%, with a majority of the diagnoses being alcohol use disorders. Several correlates representing the domains of behavioral and affective factors, parental factors, early initiation of substance use, and educational factors were individually associated with SUDs. The associations between behavioral and affective factors (attention or behavior problems at school, aggression, anxiousness) and SUDs were found to be largely independent of factors from other domains, whereas daily smoking and low education were still associated with SUDs after adjustment for behavioral and affective factors. Using a wide array of neuropsychological tests in the MEAF sample and in a subsample (n=602) of the population-based FinnTwin16 (FT16) study, consistent evidence of poorer verbal cognitive ability related to SUDs was found. In addition, participants with SUDs performed worse than those without disorders in a task assessing psychomotor processing speed in the MEAF sample, whereas no evidence of more specific cognitive deficits was found in either sample. Biometrical structural equation models of the twin data suggested that both alcohol problems and verbal ability had moderate heritabilities (0.54—0.72), and that their covariation could be explained by correlated genetic influences (genetic correlations -0.20 to -0.31). The relationship between educational level and alcohol problems, studied in the full epidemiological FT16 sample (n=4,858), was found to reflect both genetic correlation and gene-environment interaction. The co-occurrence of low education and alcohol problems was influenced by overlapping genetic factors. In addition, higher educational level was associated with increased relative importance of genetic influences on alcohol problems, whereas environmental influences played a more important role in young adults with lower education. In conclusion, SUDs, especially alcohol abuse and dependence, are common among young Finnish adults. Behavioral and affective factors are robustly related to SUDs independently of many other factors, and compared to healthy peers, young adults who have had SUDs during their life exhibit significantly poorer verbal cognitive ability, and possibly less efficient psychomotor processing. Genetic differences between individuals explain a notable proportion of individual differences in risk of alcohol dependence, verbal ability, and educational level, and the co-occurrence of alcohol problems with poorer verbal cognition and low education is influenced by shared genetic backgrounds. Finally, various environmental factors related to educational level in young adulthood moderate the relative importance of genetic factors influencing the risk of alcohol problems, possibly reflecting differences in social control mechanisms related to educational level.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Chicken prealbumin: Nature of its heterogeneity and binding of plasma retinol-binding protein and thyroid hormones

The heterogeneity of chicken prealbumin (PA) has been shown to be due to the occurrence of three different plasma proteins (PA1 PA2 and PA3). Equilibrium dialysis studies revealed that the thyroid hormones bind specifically to PA2. These hormones bind at the same site on PA2. Circular dichroism studies failed to reveal conformational changes on interaction of retinol-binding protein and thyroid hormone with PA2. Both retinol-binding protein and thyroid hormone are independently transported by PA2.

Determinants of Cognitive Impairment in Old Age and Their Genetic Architecture

Cognitive health is of central importance for independent and balanced old age, while memory disorders represent the leading cause of intensive and long-term care among the Finnish elderly. The aims of this study were to analyse the effect of height, body mass index, weight change, metabolic conditions and coffee drinking in midlife on cognitive performance in old age among a sample of 2606 Finnish twins aged 65 years or older who had participated in a telephone interview to assess their cognitive status. Since coffee drinking associates with several metabolic conditions and Finns are known to be the greatest consumers of coffee in the world, the heritability and stability of coffee drinking was analysed in the whole Older Finnish Twin Cohort (n=10716). In order to investigate the association between height and cognitive performance in a population with more supportive childhood living conditions, a total of 2161 Danish twins were included in this study. A greater height was found to clearly associate with better cognitive performance in Finnish subjects, but less so among the Danish sample, which may reflect the childhood environmental differences between these cohorts. In the Finnish subjects, there was greater variance in cognitive performance among shorter subjects, and environmental factors were found to play a greater role in their cognitive performance, whereas the cognitive performance of taller participants was mainly explained by genetic factors. Midlife metabolic variables that were found to be significantly associated with a poorer cognitive performance in old age included a higher body mass index and three metabolic conditions: cardiovascular disease, hypertension and, most significantly of all, diabetes. Moreover, both weight gain and loss, even to a lesser degree than suggested previously, were found to be associated with poorer cognition. Furthermore, evidence of a causal relationship between midlife cardiovascular disease and cognitive performance in old age was demonstrated among discordant twin pairs. Conversely, no effect of coffee drinking in midlife on cognitive performance in old age was observed, although coffee drinking was demonstrated to be stable in the study population. The heritability of coffee drinking was found to differ across sexes and age groups, being 51% in men and 52% in women in the whole study population. This study supports the contention that cognitive performance in old age reflects the effects of multiple genetic and environmental exposures, including their complex interactions during the life-span. The demonstrated associations and evidence of a causal pathway between potentially preventable exposures and poorer cognitive performance highlight the importance of preventive medicine.