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Data from the first physics run at the Relativistic Heavy-Ion Collider at Brookhaven National Laboratory, Au+Au collisions at sqrt[sNN]=130 GeV, have been analyzed by the STAR Collaboration using three-pion correlations with charged pions to study whether pions are emitted independently at freeze-out. We have made a high-statistics measurement of the three-pion correlation function and calculated the normalized three-particle correlator to obtain a quantitative measurement of the degree of chaoticity of the pion source. It is found that the degree of chaoticity seems to increase with increasing particle multiplicity.
The balance function is a new observable based on the principle that charge is locally conserved when particles are pair produced. Balance functions have been measured for charged particle pairs and identified charged pion pairs in Au+Au collisions at sqrt[sNN]=130 GeV at the Relativistic Heavy Ion Collider using STAR. Balance functions for peripheral collisions have widths consistent with model predictions based on a superposition of nucleon-nucleon scattering. Widths in central collisions are smaller, consistent with trends predicted by models incorporating late hadronization.
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.
Azimuthal anisotropy (v2) and two-particle angular correlations of high pT charged hadrons have been measured in Au+Au collisions at sqrt[sNN]=130 GeV for transverse momenta up to 6 GeV/c, where hard processes are expected to contribute significantly. The two-particle angular correlations exhibit elliptic flow and a structure suggestive of fragmentation of high pT partons. The monotonic rise of v2(pT) for pT<2 GeV/c is consistent with collective hydrodynamical flow calculations. At pT>3 GeV/c, a saturation of v2 is observed which persists up to pT=6 GeV/c.
Azimuthal anisotropy (v2) and two-particle angular correlations of high pT charged hadrons have been measured in Au+Au collisions at sqrt[sNN]=130 GeV for transverse momenta up to 6 GeV/c, where hard processes are expected to contribute significantly. The two-particle angular correlations exhibit elliptic flow and a structure suggestive of fragmentation of high pT partons. The monotonic rise of v2(pT) for pT<2 GeV/c is consistent with collective hydrodynamical flow calculations. At pT>3 GeV/c, a saturation of v2 is observed which persists up to pT=6 GeV/c.
Elliptic flow holds much promise for studying the early-time thermalization attained in ultrarelativistic nuclear collisions. Flow measurements also provide a means of distinguishing between hydrodynamic models and calculations which approach the low density (dilute gas) limit. Among the effects that can complicate the interpretation of elliptic flow measurements are azimuthal correlations that are unrelated to the reaction plane (nonflow correlations). Using data for Au + Au collisions at sqrt[sNN]=130 GeV from the STAR time projection chamber, it is found that four-particle correlation analyses can reliably separate flow and nonflow correlation signals. The latter account for on average about 15% of the observed second-harmonic azimuthal correlation, with the largest relative contribution for the most peripheral and the most central collisions. The results are also corrected for the effect of flow variations within centrality bins. This effect is negligible for all but the most central bin, where the correction to the elliptic flow is about a factor of 2. A simple new method for two-particle flow analysis based on scalar products is described. An analysis based on the distribution of the magnitude of the flow vector is also described.
We report the first observation of K*(892)0--> pi K in relativistic heavy ion collisions. The transverse momentum spectrum of (K*0+K*0)/2 from central Au+Au collisions at sqrt[sNN]=130 GeV is presented. The ratios of the K*0 yield derived from these data to the yields of negative hadrons, charged kaons, and phi mesons have been measured in central and minimum bias collisions and compared with model predictions and comparable e+e-, pp, and p-barp results. The data indicate no dramatic reduction of K*0 production in relativistic heavy ion collisions despite expected losses due to rescattering effects.
The STAR Collaboration reports the first observation of exclusive rho 0 photoproduction, AuAu-->AuAu rho 0, and rho 0 production accompanied by mutual nuclear Coulomb excitation, AuAu-->Au [star] Au [star] rho 0, in ultraperipheral heavy-ion collisions. The rho 0 have low transverse momenta, consistent with coherent coupling to both nuclei. The cross sections at sqrt[sNN]=130 GeV agree with theoretical predictions treating rho 0 production and Coulomb excitation as independent processes.
We report STAR results on the azimuthal anisotropy parameter v2 for strange particles K0S, Lambda , and Lambda -bar at midrapidity in Au+Au collisions at sqrt[sNN]=130 GeV at the Relativistic Heavy Ion Collider. The value of v2 as a function of transverse momentum, pt, of the produced particle and collision centrality is presented for both particles up to pt~3.0 GeV/c. A strong pt dependence in v2 is observed up to 2.0 GeV/c. The v2 measurement is compared with hydrodynamic model calculations. The physics implications of the pt integrated v2 magnitude as a function of particle mass are also discussed.
Inclusive transverse momentum distributions of charged hadrons within 0.2<pT<6.0 GeV/c have been measured over a broad range of centrality for Au+Au collisions at sqrt[sNN]=130 GeV. Hadron yields are suppressed at high pT in central collisions relative to peripheral collisions and to a nucleon-nucleon reference scaled for collision geometry. Peripheral collisions are not suppressed relative to the nucleon-nucleon reference. The suppression varies continuously at intermediate centralities. The results indicate significant nuclear medium effects on high-pT hadron production in heavy-ion collisions at high energy.
We report the first measurement of strange ( Lambda ) and antistrange ( Lambda -bar) baryon production from sqrt[sNN]=130 GeV Au+Au collisions at the Relativistic Heavy Ion Collider (RHIC). Rapidity density and transverse mass distributions at midrapidity are presented as a function of centrality. The yield of Lambda and Lambda -bar hyperons is found to be approximately proportional to the number of negative hadrons. The production of Lambda -bar hyperons relative to negative hadrons increases very rapidly with transverse momentum. The magnitude of the increase cannot be described by existing hadronic string fragmentation models alone.
We report the first measurement of inclusive antiproton production at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV by the STAR experiment at RHIC. The antiproton transverse mass distributions in the measured transverse momentum range of 0.25<pperp<0.95 GeV/c are found to fall less steeply for more central collisions. The extrapolated antiproton rapidity density is found to scale approximately with the negative hadron multiplicity density.
Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.
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< 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.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Rare copy-number variation (CNV) is an important source of risk for autism spectrum disorders (ASDs). We analyzed 2,446 ASD-affected families and confirmed an excess of genic deletions and duplications in affected versus control groups (1.41-fold, p = 1.0 × 10(-5)) and an increase in affected subjects carrying exonic pathogenic CNVs overlapping known loci associated with dominant or X-linked ASD and intellectual disability (odds ratio = 12.62, p = 2.7 × 10(-15), ∼3% of ASD subjects). Pathogenic CNVs, often showing variable expressivity, included rare de novo and inherited events at 36 loci, implicating ASD-associated genes (CHD2, HDAC4, and GDI1) previously linked to other neurodevelopmental disorders, as well as other genes such as SETD5, MIR137, and HDAC9. Consistent with hypothesized gender-specific modulators, females with ASD were more likely to have highly penetrant CNVs (p = 0.017) and were also overrepresented among subjects with fragile X syndrome protein targets (p = 0.02). Genes affected by de novo CNVs and/or loss-of-function single-nucleotide variants converged on networks related to neuronal signaling and development, synapse function, and chromatin regulation.
Introduction: Preclinical CT-guided radiotherapy platforms are increasingly used but the CT images are characterized by poor soft tissue contrast. The aim of this study was to develop a robust and accurate method of MRI-guided radiotherapy (MR-IGRT) delivery to abdominal targets in the mouse.
Methods: A multimodality cradle was developed for providing subject immobilisation and its performance was evaluated. Whilst CT was still used for dose calculations, target identification was based on MRI. Each step of the radiotherapy planning procedure was validated initially in vitro using BANG gel dosimeters. Subsequently, MR-IGRT of normal adrenal glands with a size-matched collimated beam was performed. Additionally, the SK-N-SH neuroblastoma xenograft model and the transgenic KPC model of pancreatic ductal adenocarcinoma were used to demonstrate the applicability of our methods for the accurate delivery of radiation to CT-invisible abdominal tumours.
Results: The BANG gel phantoms demonstrated a targeting efficiency error of 0.56 ± 0.18 mm. The in vivo stability tests of body motion during MR-IGRT and the associated cradle transfer showed that the residual body movements are within this MR-IGRT targeting error. Accurate MR-IGRT of the normal adrenal glands with a size-matched collimated beam was confirmed by γH2AX staining. Regression in tumour volume was observed almost immediately post MR-IGRT in the neuroblastoma model, further demonstrating accuracy of x-ray delivery. Finally, MR-IGRT in the KPC model facilitated precise contouring and comparison of different treatment plans and radiotherapy dose distributions not only to the intra-abdominal tumour but also to the organs at risk.
Conclusion: This is, to our knowledge, the first study to demonstrate preclinical MR-IGRT in intra-abdominal organs. The proposed MR-IGRT method presents a state-of-the-art solution to enabling robust, accurate and efficient targeting of extracranial organs in the mouse and can operate with a sufficiently high throughput to allow fractionated treatments to be given.
Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
(2017)
White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA Epilepsy study
(2019)
The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analyzed from 1,069 non-epileptic controls and 1,249 patients: temporal lobe epilepsy with hippocampal sclerosis (N=599), temporal lobe epilepsy with normal MRI (N=275), genetic generalized epilepsy (N=182) and nonlesional extratemporal epilepsy (N=193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fiber tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at p<0.001). Across “all epilepsies” lower fractional anisotropy was observed in most fiber tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. Less robust effects were seen with mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Those with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced differences in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and in mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of microstructural abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibers in a large multicentre study of epilepsy. Overall, epilepsy patients showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding new insights into pathological substrates that may be used to guide future therapeutic and genetic studies.