Gravitational contribution to fermion masses

In the context of a nonlinear gauge theory of the Poincar\'e group, we show that covariant derivatives of Dirac fields include a coupling to the translational connections, manifesting itself in the matter action as a universal background mass contribution to fermions.Comment: revtex4, 9 pages, no figures, to be published in Eur.Phys.J.C, 200

Hamiltonian Poincar\'e Gauge Theory of Gravitation

We develop a Hamiltonian formalism suitable to be applied to gauge theories in the presence of Gravitation, and to Gravity itself when considered as a gauge theory. It is based on a nonlinear realization of the Poincar\'e group, taken as the local spacetime group of the gravitational gauge theory, with $SO(3)$ as the classification subgroup. The Wigner--like rotation induced by the nonlinear approach singularizes out the role of time and allows to deal with ordinary $SO(3)$ vectors. We apply the general results to the Einstein--Cartan action. We study the constraints and we obtain Einstein's classical equations in the extremely simple form of time evolution equations of the coframe. As a consequence of our approach, we identify the gauge--theoretical origin of the Ashtekar variables.Comment: 38 pages, plainTe

Unimpaired attentional disengagement in toddlers with autism spectrum disorder

A prominent hypothesis holds that ‘sticky’ attention early in life in children with autism spectrum disorder (ASD) limits their ability to explore and learn about the world. Under this hypothesis, the core clinical symptoms of ASD – restricted interests, repetitive behaviors and impaired social/communication abilities – could all result from impaired attentional disengagement during development. However, the existence of disengagement deficits in children with ASD is controversial, and a recent study found no deficit in 5- to 12-year-olds with ASD. Nonetheless, the possibility remains that disengagement is impaired earlier in development in children with ASD, altering their developmental trajectory even if the attentional deficit itself is remediated or compensated for by the time children with ASD reach school age. Here, we tested this possibility by characterizing attentional disengagement in a group of toddlers just diagnosed with ASD (age 21 to 37 months). We found strikingly similar performance between the ASD and age-matched typically developing (TD) toddlers, and no evidence of impaired attentional disengagement. These results show that even at a young age when the clinical symptoms of ASD are first emerging, disengagement abilities are intact. Sticky attention is not a fundamental characteristic of ASD, and probably does not play a causal role in its etiology.Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (Award F32-HD075427

De novo and rare inherited mutations implicate the transcriptional coregulator TCF20/SPBP in autism spectrum disorder

BACKGROUND: Autism spectrum disorders (ASDs) are common and have a strong genetic basis, yet the cause of ∼70-80% ASDs remains unknown. By clinical cytogenetic testing, we identified a family in which two brothers had ASD, mild intellectual disability and a chromosome 22 pericentric inversion, not detected in either parent, indicating de novo mutation with parental germinal mosaicism. We hypothesised that the rearrangement was causative of their ASD and localised the chromosome 22 breakpoints. METHODS: The rearrangement was characterised using fluorescence in situ hybridisation, Southern blotting, inverse PCR and dideoxy-sequencing. Open reading frames and intron/exon boundaries of the two physically disrupted genes identified, TCF20 and TNRC6B, were sequenced in 342 families (260 multiplex and 82 simplex) ascertained by the International Molecular Genetic Study of Autism Consortium (IMGSAC). RESULTS: IMGSAC family screening identified a de novo missense mutation of TCF20 in a single case and significant association of a different missense mutation of TCF20 with ASD in three further families. Through exome sequencing in another project, we independently identified a de novo frameshifting mutation of TCF20 in a woman with ASD and moderate intellectual disability. We did not identify a significant association of TNRC6B mutations with ASD. CONCLUSIONS: TCF20 encodes a transcriptional coregulator (also termed SPBP) that is structurally and functionally related to RAI1, the critical dosage-sensitive protein implicated in the behavioural phenotypes of the Smith-Magenis and Potocki-Lupski 17p11.2 deletion/duplication syndromes, in which ASD is frequently diagnosed. This study provides the first evidence that mutations in TCF20 are also associated with ASD

Deriving the mass of particles from Extended Theories of Gravity in LHC era

We derive a geometrical approach to produce the mass of particles that could be suitably tested at LHC. Starting from a 5D unification scheme, we show that all the known interactions could be suitably deduced as an induced symmetry breaking of the non-unitary GL(4)-group of diffeomorphisms. The deformations inducing such a breaking act as vector bosons that, depending on the gravitational mass states, can assume the role of interaction bosons like gluons, electroweak bosons or photon. The further gravitational degrees of freedom, emerging from the reduction mechanism in 4D, eliminate the hierarchy problem since generate a cut-off comparable with electroweak one at TeV scales. In this "economic" scheme, gravity should induce the other interactions in a non-perturbative way.Comment: 30 pages, 1 figur

A genome-wide scan for common alleles affecting risk for autism

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm&lt; 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest

Use of machine learning to shorten observation-based screening and diagnosis of autism

The Autism Diagnostic Observation Schedule-Generic (ADOS) is one of the most widely used instruments for behavioral evaluation of autism spectrum disorders. It is composed of four modules, each tailored for a specific group of individuals based on their language and developmental level. On average, a module takes between 30 and 60 min to deliver. We used a series of machine-learning algorithms to study the complete set of scores from Module 1 of the ADOS available at the Autism Genetic Resource Exchange (AGRE) for 612 individuals with a classification of autism and 15 non-spectrum individuals from both AGRE and the Boston Autism Consortium (AC). Our analysis indicated that 8 of the 29 items contained in Module 1 of the ADOS were sufficient to classify autism with 100% accuracy. We further validated the accuracy of this eight-item classifier against complete sets of scores from two independent sources, a collection of 110 individuals with autism from AC and a collection of 336 individuals with autism from the Simons Foundation. In both cases, our classifier performed with nearly 100% sensitivity, correctly classifying all but two of the individuals from these two resources with a diagnosis of autism, and with 94% specificity on a collection of observed and simulated non-spectrum controls. The classifier contained several elements found in the ADOS algorithm, demonstrating high test validity, and also resulted in a quantitative score that measures classification confidence and extremeness of the phenotype. With incidence rates rising, the ability to classify autism effectively and quickly requires careful design of assessment and diagnostic tools. Given the brevity, accuracy and quantitative nature of the classifier, results from this study may prove valuable in the development of mobile tools for preliminary evaluation and clinical prioritization—in particular those focused on assessment of short home videos of children—that speed the pace of initial evaluation and broaden the reach to a significantly larger percentage of the population at risk