A simple syllogism-solving test: empirical findings and implications for g research

It has been reported that the ability to solve syllogisms is highly g-loaded. In the present study, using a self-administered shortened version of a syllogism-solving test, the BAROCO Short, we examined whether robust findings generated by previous research regarding IQ scores were also applicable to BAROCO Short scores. Five syllogism-solving problems were included in a questionnaire as part of a postal survey conducted by the Keio Twin Research Center. Data were collected from 487 pairs of twins (1021 individuals) who were Japanese junior high or high school students (ages 13–18) and from 536 mothers and 431 fathers. Four findings related to IQ were replicated: 1) The mean level increased gradually during adolescence, stayed unchanged from the 30s to the early 50s, and subsequently declined after the late 50s. 2) The scores for both children and parents were predicted by the socioeconomic status of the family. 3) The genetic effect increased, although the shared environmental effect decreased during progression from adolescence to adulthood. 4) Children's scores were genetically correlated with school achievement. These findings further substantiate the close association between syllogistic reasoning ability and g.

Genetic variation in GABRB3 is associated with Asperger syndrome and multiple endophenotypes relevant to autism.

BACKGROUND: Autism spectrum conditions (ASC) are associated with deficits in social interaction and communication, alongside repetitive, restricted, and stereotyped behavior. ASC is highly heritable. The gamma-aminobutyric acid (GABA)-ergic system has been associated consistently with atypicalities in autism, in both genetic association and expression studies. A key component of the GABA-ergic system is encoded by the GABRB3 gene, which has been previously implicated both in ASC and in individual differences in empathy. METHODS: In this study, 45 genotyped single nucleotide polymorphisms (SNPs) within GABRB3 were tested for association with Asperger syndrome (AS), and related quantitative traits measured through the following tests: the Empathy Quotient (EQ), the Autism Spectrum Quotient (AQ), the Systemizing Quotient-Revised (SQ-R), the Embedded Figures Test (EFT), the Reading the Mind in the Eyes Test (RMET), and the Mental Rotation Test (MRT). Two-loci, three-loci, four-loci haplotype analyses, and one seven-loci haplotype analysis were also performed in the AS case--control sample. RESULTS: Three SNPs (rs7180158, rs7165604, rs12593579) were significantly associated with AS, and two SNPs (rs9806546, rs11636966) were significantly associated with EQ. Two SNP-SNP pairs, rs12438141-rs1035751 and rs12438141-rs7179514, showed significant association with variation in the EFT scores. One SNP-SNP pair, rs7174437-rs1863455, was significantly associated with variation in the MRT scores. Additionally, a few haplotypes, including a 19 kb genomic region that formed a linkage disequilibrium (LD) block in our sample and contained several nominally significant SNPs, were found to be significantly associated with AS. CONCLUSION: The current study confirms the role of GABRB3 as an important candidate gene in both ASC and normative variation in related endophenotypes.

Genetic variation in the oxytocin receptor (OXTR) gene is associated with Asperger Syndrome

Background Autism Spectrum Conditions (ASC) are a group of neurodevelopmental conditions characterized by impairments in communication and social interaction, alongside unusually repetitive behaviors and narrow interests. ASC are highly heritable and have complex patterns of inheritance where multiple genes are involved, alongside environmental and epigenetic factors. Asperger Syndrome (AS) is a subgroup of these conditions, where there is no history of language or cognitive delay. Animal models suggest a role for oxytocin (OXT) and oxytocin receptor (OXTR) genes in social-emotional behaviors, and several studies indicate that the oxytocin/oxytocin receptor system is altered in individuals with ASC. Previous studies have reported associations between genetic variations in the OXTR gene and ASC. Methods The present study tested for an association between nine single nucleotide polymorphisms (SNPs) in the OXTR gene and AS in 530 individuals of Caucasian origin, using SNP association test and haplotype analysis. Results There was a significant association between rs2268493 in OXTR and AS. Multiple haplotypes that include this SNP (rs2268493-rs2254298, rs2268490-rs2268493-rs2254298, rs2268493-rs2254298-rs53576, rs237885-rs2268490-rs2268493-rs2254298, rs2268490-rs2268493-rs2254298-rs53576) were also associated with AS. rs2268493 has been previously associated with ASC and putatively alters several transcription factor-binding sites and regulates chromatin states, either directly or through other variants in linkage disequilibrium (LD). Conclusions This study reports a significant association of the sequence variant rs2268493 in the OXTR gene and associated haplotypes with AS.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.

Changes in physical activity following a genetic-based internet-delivered personalized intervention: randomized controlled trial (Food4Me)

Background: There is evidence that physical activity (PA) can attenuate the influence of the fat mass- and obesity-associated (FTO) genotype on the risk to develop obesity. However, whether providing personalized information on FTO genotype leads to changes in PA is unknown. Objective: The purpose of this study was to determine if disclosing FTO risk had an impact on change in PA following a 6-month intervention. Methods: The single nucleotide polymorphism (SNP) rs9939609 in the FTO gene was genotyped in 1279 participants of the Food4Me study, a four-arm, Web-based randomized controlled trial (RCT) in 7 European countries on the effects of personalized advice on nutrition and PA. PA was measured objectively using a TracmorD accelerometer and was self-reported using the Baecke questionnaire at baseline and 6 months. Differences in baseline PA variables between risk (AA and AT genotypes) and nonrisk (TT genotype) carriers were tested using multiple linear regression. Impact of FTO risk disclosure on PA change at 6 months was assessed among participants with inadequate PA, by including an interaction term in the model: disclosure (yes/no) × FTO risk (yes/no). Results: At baseline, data on PA were available for 874 and 405 participants with the risk and nonrisk FTO genotypes, respectively. There were no significant differences in objectively measured or self-reported baseline PA between risk and nonrisk carriers. A total of 807 (72.05%) of the participants out of 1120 in the personalized groups were encouraged to increase PA at baseline. Knowledge of FTO risk had no impact on PA in either risk or nonrisk carriers after the 6-month intervention. Attrition was higher in nonrisk participants for whom genotype was disclosed (P=.01) compared with their at-risk counterparts. Conclusions: No association between baseline PA and FTO risk genotype was observed. There was no added benefit of disclosing FTO risk on changes in PA in this personalized intervention. Further RCT studies are warranted to confirm whether disclosure of nonrisk genetic test results has adverse effects on engagement in behavior change.

Consensus Statement: Chromosomal Microarray Is a First-Tier Clinical Diagnostic Test for Individuals with Developmental Disabilities or Congenital Anomalies

Chromosomal microarray (CMA) is increasingly utilized for genetic testing of individuals with unexplained developmental delay/intellectual disability (DD/ID), autism spectrum disorders (ASD), or multiple congenital anomalies (MCA). Performing CMA and G-banded karyotyping on every patient substantially increases the total cost of genetic testing. The International Standard Cytogenomic Array (ISCA) Consortium held two international workshops and conducted a literature review of 33 studies, including 21,698 patients tested by CMA. We provide an evidence-based summary of clinical cytogenetic testing comparing CMA to G-banded karyotyping with respect to technical advantages and limitations, diagnostic yield for various types of chromosomal aberrations, and issues that affect test interpretation. CMA offers a much higher diagnostic yield (15%-20%) for genetic testing of individuals with unexplained DD/ID, ASD, or MCA than a G-banded karyotype (similar to 3%, excluding Down syndrome and other recognizable chromosomal syndromes), primarily because of its higher sensitivity for submicroscopic deletions and duplications. Truly balanced rearrangements and low-level mosaicism are generally not detectable by arrays, but these are relatively infrequent causes of abnormal phenotypes in this population (<1%). Available evidence strongly supports the use of CMA in place of G-banded karyotyping as the first-tier cytogenetic diagnostic test for patients with DD/ID, ASD, or MCA. G-banded karyotype analysis should be reserved for patients with obvious chromosomal syndromes (e.g., Down syndrome), a family history of chromosomal rearrangement, or a history of multiple miscarriages.

Evidence of a genetic bottleneck in an El Nino affected population of South American fur seals, Arctocephalus australis

The South American fur seal, Arctocephalus australis, was one of the earliest otariid seals to be exploited by humans: at least 6000 years ago on the Atlantic coast and 4000 on the Pacific coast of South America. More than 750,000 fur seals were killed in Uruguay until 1991. However, a climatological phenomenon-the severe 1997-1998 El Nino Southern Oscillation (ENSO)-was responsible for the decline of 72% Of the Peruvian fur seal population due to starvation as a consequence of warming of sea-surface temperatures and primary productivity reduction. Currently, there is no precise information on global population size or on the species` conservation status. The present study includes the first bottleneck test for the Pacific and Atlantic populations of A. australis based on the analysis of seven microsatellite loci. Genetic bottleneck compromises the evolutionary potential of a population to respond to environmental changes. The perspective becomes even more alarming due to current global warming models that predict stronger and more frequent ENSO events in the future. Our analysis found moderate support for deviation from neutrality-equilibrium for the Pacific population of fur seals and none for the Atlantic population. This difference among population reflects different demographic histories, and is consistent with a greater reduction in population size in the Pacific. Such an event could be a result of the synergic effects of recurrent ENSO events and the anthropogenic impact (sealing and prey overfishing) on this population.

Genetic and Functional Evidence Implicating DLL1 as the Gene That Influences Susceptibility to Visceral Leishmaniasis at Chromosome 6q27

Background. Visceral leishmaniasis (VL) is caused by Leishmania donovani and Leishmania infantum chagasi. Genome-wide linkage studies from Sudan and Brazil identified a putative susceptibility locus on chromosome 6q27. Methods. Twenty-two single-nucleotide polymorphisms (SNPs) at genes PHF10, C6orf70, DLL1, FAM120B, PSMB1, and TBP were genotyped in 193 VL cases from 85 Sudanese families, and 8 SNPs at genes PHF10, C6orf70, DLL1, PSMB1, and TBP were genotyped in 194 VL cases from 80 Brazilian families. Family-based association, haplotype, and linkage disequilibrium analyses were performed. Multispecies comparative sequence analysis was used to identify conserved noncoding sequences carrying putative regulatory elements. Quantitative reverse-transcription polymerase chain reaction measured expression of candidate genes in splenic aspirates from Indian patients with VL compared with that in the control spleen sample. Results. Positive associations were observed at PHF10, C6orf70, DLL1, PSMB1, and TBP in Sudan, but only at DLL1 in Brazil (combined P = 3 x 10(-4) at DLL1 across Sudan and Brazil). No functional coding region variants were observed in resequencing of 22 Sudanese VL cases. DLL1 expression was significantly (P = 2 x 10(-7)) reduced (mean fold change, 3.5 [SEM, 0.7]) in splenic aspirates from patients with VL, whereas other 6q27 genes showed higher levels (1.27 x 10(-6) < P < .01) than did the control spleen sample. A cluster of conserved noncoding sequences with putative regulatory variants was identified in the distal promoter of DLL1. Conclusions. DLL1, which encodes Delta-like 1, the ligand for Notch3, is strongly implicated as the chromosome 6q27 VL susceptibility gene.

Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar)

BACKGROUND: Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. RESULTS: Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. CONCLUSIONS: Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro-environmental changes (diet, climatic region, etc.) may make genetic heterogeneity of variance a less stable trait over time and space.

Genetic diversity of natural populations of Anemopaegma arvense (Bignoniaceae) in the Cerrado of São Paulo State, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Blood serum components and serum protein test of Hybro-PG broilers of different ages

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Test-day milk yield as a selection criterion for dairy buffaloes (Bubalus bubalis Artiodactyla, Bovidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)