Physics-based analysis of Affymetrix microarray data

We analyze publicly available data on Affymetrix microarrays spike-in experiments on the human HGU133 chipset in which sequences are added in solution at known concentrations. The spike-in set contains sequences of bacterial, human and artificial origin. Our analysis is based on a recently introduced molecular-based model [E. Carlon and T. Heim, Physica A 362, 433 (2006)] which takes into account both probe-target hybridization and target-target partial hybridization in solution. The hybridization free energies are obtained from the nearest-neighbor model with experimentally determined parameters. The molecular-based model suggests a rescaling that should result in a "collapse" of the data at different concentrations into a single universal curve. We indeed find such a collapse, with the same parameters as obtained before for the older HGU95 chip set. The quality of the collapse varies according to the probe set considered. Artificial sequences, chosen by Affymetrix to be as different as possible from any other human genome sequence, generally show a much better collapse and thus a better agreement with the model than all other sequences. This suggests that the observed deviations from the predicted collapse are related to the choice of probes or have a biological origin, rather than being a problem with the proposed model.Comment: 11 pages, 10 figure

Space-Varying Coefficient Models for Brain Imaging

The methodological development and the application in this paper originate from diffusion tensor imaging (DTI), a powerful nuclear magnetic resonance technique enabling diagnosis and monitoring of several diseases as well as reconstruction of neural pathways. We reformulate the current analysis framework of separate voxelwise regressions as a 3d space-varying coefficient model (VCM) for the entire set of DTI images recorded on a 3d grid of voxels. Hence by allowing to borrow strength from spatially adjacent voxels, to smooth noisy observations, and to estimate diffusion tensors at any location within the brain, the three-step cascade of standard data processing is overcome simultaneously. We conceptualize two VCM variants based on B-spline basis functions: a full tensor product approach and a sequential approximation, rendering the VCM numerically and computationally feasible even for the huge dimension of the joint model in a realistic setup. A simulation study shows that both approaches outperform the standard method of voxelwise regressions with subsequent regularization. Due to major efficacy, we apply the sequential method to a clinical DTI data set and demonstrate the inherent ability of increasing the rigid grid resolution by evaluating the incorporated basis functions at intermediate points. In conclusion, the suggested fitting methods clearly improve the current state-of-the-art, but ameloriation of local adaptivity remains desirable

A developmental investigation of the relationship between appraisals and peer self-esteem in children experiencing peer-aggression

Transactional models of stress and coping emphasize the role played by cognitive appraisals in determining psychological adjustment (Lazarus, 1999). This proposition has been supported by research examining young people's adjustment in relation to family conflict and break-up (Grych et al., 1992). Furthermore, this literature suggests that there is a change in the relationship between appraisals and adjustment at around 10 years of age: specificity of appraisal type (e.g. threat, blame) becomes relevant to outcome after 10 years, whereas before 10 there are either no effects of appraisal on adjustment or a diffuse effect of 'negative' appraisals more generally (Jouriles et al., 2000). However, it is currently unclear whether this developmental progression can be generalized from familial- to social-stressors experienced by children and young people. The current study therefore evaluates the model within the context of a commonly experienced social childhood stressor: peer-aggression

Molecular Dynamics Simulations of Detonation Instability

After making modifications to the Reactive Empirical Bond Order potential for Molecular Dynamics (MD) of Brenner et al. in order to make the model behave in a more conventional manner, we discover that the new model exhibits detonation instability, a first for MD. The instability is analyzed in terms of the accepted theory.Comment: 7 pages, 6 figures. Submitted to Phys. Rev. E Minor edits. Removed parenthetical statement about P^\nu from conclusion

Review on the epidemiology and dynamics of BSE epidemics

The paper describes how the comprehensive surveillance of bovine spongiform encephalopathy (BSE) and studies carried out on these data has enhanced our knowledge of the epidemiology of BSE. Around 7 000 BSE cases were detected through the screening of about 50 million cattle with rapid tests in Europe. It confirmed that the clinical surveillance had a poor capacity to detect cases, and also showed the discrepancy of this passive surveillance efficiency between regions and production types (dairy/beef). Other risk factors for BSE were being in a dairy herd (three times more than beef), having a young age at first calving (for dairy cattle), being autumn-born (dairy and beef), and being in a herd with a very high milk yield. These findings focus the risk on the feeding regimen of calves/heifers. Several epidemiological studies across countries suggest that the feedborne source related to meat and bone meal (MBM) is the only substantiated route of infection ¿ even after the feed ban ¿, while it is not possible to exclude maternal transmission or milk replacers as a source of some infections. In most European countries, the average age of the cases is increasing over time and the prevalence decreasing, which reflects the effectiveness of control measures. Consistent results on the trend of the epidemic were obtained using back-calculation modelling, the R0 approach and Age-Period-Cohort models. Furthermore, active surveillance also resulted in the finding of atypical cases. These are distinct from previously found BSE and classified in two different forms based on biochemical characteristics; their prevalence is very low (36 cases up to 1st September 2007), affected animals were old and some of them displayed clinical signs. The origin and possibility of natural transmission is unknown

Varying Coefficient Tensor Models for Brain Imaging

We revisit a multidimensional varying-coefficient model (VCM), by allowing regressor coefficients to vary smoothly in more than one dimension, thereby extending the VCM of Hastie and Tibshirani. The motivating example is 3-dimensional, involving a special type of nuclear magnetic resonance measurement technique that is being used to estimate the diffusion tensor at each point in the human brain. We aim to improve the current state of the art, which is to apply a multiple regression model for each voxel separately using information from six or more volume images. We present a model, based on P-spline tensor products, to introduce spatial smoothness of the estimated diffusion tensor. Since the regression design matrix is space-invariant, a 4-dimensional tensor product model results, allowing more efficient computation with penalized array regression

Transfer Functions and Penetrations of Five Differential Mobility Analyzers for Sub-2 nm Particle Classification

The transfer functions and penetrations of five differential mobility analyzers (DMAs) for sub-2 nm particle classification were evaluated in this study. These DMAs include the TSI nanoDMA, the Caltech radial DMA (RDMA) and nanoRDMA, the Grimm nanoDMA, and the Karlsruhe-Vienna DMA. Measurements were done using tetra-alkyl ammonium ion standards with mobility diameters of 1.16, 1.47, and 1.70 nm. These monomobile ions were generated by electrospray followed by high resolution mobility classification. Measurements were focused at an aerosol-to-sheath flow ratio of 0.1. A data inversion routine was developed to obtain the true transfer function for each test DMA, and these measured transfer functions were compared with theory. DMA penetration efficiencies were also measured. An approximate model for diffusional deposition, based on the modified Gormley and Kennedy equation using an effective length, is given for each test DMA. These results quantitatively characterize the performance of the test DMAs in classifying sub-2 nm particles and can be readily used for DMA data inversion