Tracking vibrational energy on curved shell structures of variable thickness in the mid-to-high frequency - a ray tracing approach

Modelling the vibro-acoustic properties of mechanical built-up structures is a challenging task. Commonly employed techniques, such as finite element methods, are robust only in the low frequency regime. Recently, Discrete Flow Mapping has been forwarded as a cost efficient alternative method for mid- to high-frequency vibro-acoustic modelling. Discrete Flow Mapping employs local ray tracing approximations, providing a good model of the ray dynamics in homogeneous, isotropic flat plates or on curved shells in the geodesic high-frequency limit. However, in the mid-frequency case when the wavelength approaches the shell’s local radius of curvature, the resulting ray dynamics depend on the curvature in a non-trivial way. In this work, we consider ray-tracing approaches for modelling vibrational energy transport in curved shells of variable thickness at mid-to-high frequencies. In particular, we analyse mid-frequency effects on the dispersion curves for curved shells of variable thickness, and identify novel reflection/transmission behaviour

Can linear collocation ever beat quadratic?

Computational approaches are becoming increasingly important in neuroscience, where complex, nonlinear systems modelling neural activity across multiple spatial and temporal scales are the norm. This paper considers collocation techniques for solving neural field models, which typically take the form of a partial integro-dfferential equation. In particular, we investigate and compare the convergence properties of linear and quadratic collocation on both regular grids and more general meshes not fixed to the regular Cartesian grid points. For regular grids we perform a comparative analysis against more standard techniques, in which the convolution integral is computed either by using Fourier based methods or via the trapezoidal rule. Perhaps surprisingly, we find that on regular, periodic meshes, linear collocation displays better convergence properties than quadratic collocation, and is in fact comparable with the spectral convergence displayed by both the Fourier based and trapezoidal techniques. However, for more general meshes we obtain superior convergence of the convolution integral using higher order methods, as expected

A numerical simulation of neural fields on curved geometries

Despite the highly convoluted nature of the human brain, neural field models typically treat the cortex as a planar two-dimensional sheet of neurons. Here, we present an approach for solving neural field equations on surfaces more akin to the cortical geometries typically obtained from neuroimaging data. Our approach involves solving the integral form of the partial integro-differential equation directly using collocation techniques alongside efficient numerical procedures for determining geodesic distances between neural units. To illustrate our methods, we study localised activity patterns in a two-dimensional neural field equation posed on a periodic square domain, the curved surface of a torus, and the cortical surface of a rat brain, the latter of which is constructed using neuroimaging data. Our results are twofold: Firstly, we find that collocation techniques are able to replicate solutions obtained using more standard Fourier based methods on a flat, periodic domain, independent of the underlying mesh. This result is particularly significant given the highly irregular nature of the type of meshes derived from modern neuroimaging data. And secondly, by deploying efficient numerical schemes to compute geodesics, our approach is not only capable of modelling macroscopic pattern formation on realistic cortical geometries, but can also be extended to include cortical architectures of more physiological relevance. Importantly, such an approach provides a means by which to investigate the influence of cortical geometry upon the nucleation and propagation of spatially localised neural activity and beyond. It thus promises to provide model-based insights into disorders like epilepsy, or spreading depression, as well as healthy cognitive processes like working memory or attention

Towards In Silico identification of genes contributing to similarity of patients’ multi-omics profiles: a case study of acute myeloid leukemia

We propose a computational framework for selecting biologically plausible genes identified by clustering of multi-omics data that reveal patients' similarity, thus giving researchers a more comprehensive view on any given disease. We employ spectral clustering of a similarity network created by fusion of three similarity networks, based on mRNA expression of immune genes, miRNA expression and DNA methylation data, using SNF_v2.1 software. For each cluster, we rank multi-omics features, ensuring the best separation between clusters, and select the top-ranked features that preserve clustering. To find genes targeted by DNA methylation and miRNAs found in the top-ranked features, we use chromosome-conformation capture data and miRNet 2.0 software, respectively. To identify informative genes, these combined sets of target genes are analyzed in terms of their enrichment in somatic/germline mutations, GO biological processes/pathways terms and known sets of genes considered to be important in relation to a given disease, as recorded in the Molecular Signature Database from GSEA. The protein-protein interaction (PPI) networks were analyzed to identify genes that are hubs of PPI networks. We used data recorded in The Cancer Genome Atlas for patients with acute myeloid leukemia to demonstrate our approach, and discuss our findings in the context of results in the literature

Language and social/emotional problems identified at a universal developmental assessment at 30 months

Non peer reviewedPublisher PD

Polychlorinated biphenyls, cytochrome P450 1A1 (CYP1A1) polymorphisms, and breast cancer risk among African American women and white women in North Carolina: a population-based case-control study

INTRODUCTION: Epidemiologic studies have not shown a strong relationship between blood levels of polychlorinated biphenyls (PCBs) and breast cancer risk. However, two recent studies showed a stronger association among postmenopausal white women with the inducible M2 polymorphism in the cytochrome P450 1A1 (CYP1A1) gene. METHODS: In a population-based case-control study, we evaluated breast cancer risk in relation to PCBs and the CYP1A1 polymorphisms M1 (also known as CYP1A1*2A), M2 (CYP1A1*2C), M3 (CYP1A1*3), and M4 (CYP1A1*4). The study population consisted of 612 patients (242 African American, 370 white) and 599 controls (242 African American, 357 white). RESULTS: There was no evidence of strong joint effects between CYP1A1 M1-containing genotypes and total PCBs in African American or white women. Statistically significant multiplicative interactions were observed between CYP1A1 M2-containing genotypes and elevated plasma total PCBs among white women (P value for likelihood ratio test = 0.02). Multiplicative interactions were also observed between CYP1A1 M3-containing genotypes and elevated total PCBs among African American women (P value for likelihood ratio test = 0.10). CONCLUSIONS: Our results confirm previous reports that CYP1A1 M2-containing genotypes modify the association between PCB exposure and risk of breast cancer. We present additional evidence suggesting that CYP1A1 M3-containing genotypes modify the effects of PCB exposure among African American women. Additional studies are warranted, and meta-analyses combining results across studies will be needed to generate more precise estimates of the joint effects of PCBs and CYP1A1 genotypes

Automated Discrimination of Brain Pathological State Attending to Complex Structural Brain Network Properties: The Shiverer Mutant Mouse Case

Neuroimaging classification procedures between normal and pathological subjects are sparse and highly dependent of an expert's clinical criterion. Here, we aimed to investigate whether possible brain structural network differences in the shiverer mouse mutant, a relevant animal model of myelin related diseases, can reflect intrinsic individual brain properties that allow the automatic discrimination between the shiverer and normal subjects. Common structural networks properties between shiverer (C3Fe.SWV Mbpshi/Mbpshi, n = 6) and background control (C3HeB.FeJ, n = 6) mice are estimated and compared by means of three diffusion weighted MRI (DW-MRI) fiber tractography algorithms and a graph framework. Firstly, we found that brain networks of control group are significantly more clustered, modularized, efficient and optimized than those of the shiverer group, which presented significantly increased characteristic path length. These results are in line with previous structural/functional complex brain networks analysis that have revealed topologic differences and brain network randomization associated to specific states of human brain pathology. In addition, by means of network measures spatial representations and discrimination analysis, we show that it is possible to classify with high accuracy to which group each subject belongs, providing also a probability value of being a normal or shiverer subject as an individual anatomical classifier. The obtained correct predictions (e.g., around 91.6–100%) and clear spatial subdivisions between control and shiverer mice, suggest that there might exist specific network subspaces corresponding to specific brain disorders, supporting also the point of view that complex brain network analyses constitutes promising tools in the future creation of interpretable imaging biomarkers

Effects of methylphenidate on attention in Wistar rats treated with the neurotoxin N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine (DSP4)

The aim of this study was to assess the effects of the neurotoxin N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine (DSP4) on attention in rats as measured using the 5-choice-serial-reaction-time task (5CSRTT) and to investigate whether methylphenidate has effects on DSP4-treated rats. Methylphenidate is a noradrenaline and dopamine reuptake inhibitor and commonly used in the pharmacological treatment of individuals with attention deficit/hyperactivity disorder (ADHD). Wistar rats were trained in the 5CSRTT and treated with one of three doses of DSP4 or saline. Following the DSP4 treatment rats were injected with three doses of methylphenidate or saline and again tested in the 5CSRTT. The treatment with DSP4 caused a significant decline of performance in the number of correct responses and a decrease in response accuracy. A reduction in activity could also be observed. Whether or not the cognitive impairments are due to attention deficits or changes in explorative behaviour or activity remains to be investigated. The treatment with methylphenidate had no beneficial effect on the rats’ performance regardless of the DSP4 treatment. In the group without DSP4 treatment, methylphenidate led to a reduction in response accuracy and bidirectional effects in regard to parameters related to attention. These findings support the role of noradrenaline in modulating attention and call for further investigations concerning the effects of methylphenidate on attentional processes in rats

Assessing Tuberculosis Case Fatality Ratio: A Meta-Analysis

Background: Recently, the tuberculosis (TB) Task Force Impact Measurement acknowledged the need to review the assumptions underlying the TB mortality estimates published annually by the World Health Organization (WHO). TB mortality is indirectly measured by multiplying estimated TB incidence with estimated case fatality ratio (CFR). We conducted a meta-analysis to estimate the TB case fatality ratio in TB patients having initiated TB treatment. Methods: We searched for eligible studies in the PubMed and Embase databases through March 4(th) 2011 and by reference listing of relevant review articles. Main analyses included the estimation of the pooled percentages of: a) TB patients dying due to TB after having initiated TB treatment and b) TB patients dying during TB treatment. Pooled percentages were estimated using random effects regression models on the combined patient population from all studies. Main Results: We identified 69 relevant studies of which 22 provided data on mortality due to TB and 59 provided data on mortality during TB treatment. Among HIV infected persons the pooled percentage of TB patients dying due to TB was 9.2% (95% Confidence Interval (CI): 3.7%-14.7%) and among HIV uninfected persons 3.0% (95% CI: 21.2%-7.4%) based on the results of eight and three studies respectively providing data for this analyses. The pooled percentage of TB patients dying during TB treatment was 18.8% (95% CI: 14.8%-22.8%) among HIV infected patients and 3.5% (95% CI: 2.0%-4.92%) among HIV uninfected patients based on the results of 27 and 19 studies respectively. Conclusion: The results of the literature review are useful in generating prior distributions of CFR in countries with vital registration systems and have contributed towards revised estimates of TB mortality This literature review did not provide us with all data needed for a valid estimation of TB CFR in TB patients initiating TB treatmen

Association Testing Of Copy Number Variants in Schizophrenia and Autism Spectrum Disorders

Background: Autism spectrum disorders and schizophrenia have been associated with an overlapping set of copynumber variant loci, but the nature and degree of overlap in copy number variants (deletions compared toduplications) between these two disorders remains unclear.Methods: We systematically evaluated three lines of evidence: (1) the statistical bases for associations of autismspectrum disorders and schizophrenia with a set of the primary CNVs thus far investigated, from previous studies;(2) data from case series studies on the occurrence of these CNVs in autism spectrum disorders, especially amongchildren, and (3) data on the extent to which the CNVs were associated with intellectual disability anddevelopmental, speech, or language delays. We also conducted new analyses of existing data on these CNVs inautism by pooling data from seven case control studies.Results: Four of the CNVs considered, dup 1q21.1, dup 15q11-q13, del 16p11.2, and dup 22q11.21, showed clearstatistical evidence as autism risk factors, whereas eight CNVs, del 1q21.1, del 3q29, del 15q11.2, del 15q13.3, dup16p11.2, dup 16p13.1, del 17p12, and del 22q11.21, were strongly statistically supported as risk factors forschizophrenia. Three of the CNVs, dup 1q21.1, dup 16p11.2, and dup 16p13.1, exhibited statistical support as riskfactors for both autism and schizophrenia, although for each of these CNVs statistical significance was nominal fortests involving one of the two disorders. For the CNVs that were statistically associated with schizophrenia but werenot statistically associated with autism, a notable number of children with the CNVs have been diagnosed withautism or ASD; children with these CNVs also demonstrate a high incidence of intellectual disability anddevelopmental, speech, or language delays.Conclusions: These findings suggest that although CNV loci notably overlap between autism and schizophrenia,the degree of strongly statistically supported overlap in specific CNVs at these loci remains limited. These analysesalso suggest that relatively severe premorbidity to CNV-associated schizophrenia in children may sometimes bediagnosed as autism spectrum disorder