DNA Molecule Classification Using Feature Primitives

BACKGROUND: We present a novel strategy for classification of DNA molecules using measurements from an alpha-Hemolysin channel detector. The proposed approach provides excellent classification performance for five different DNA hairpins that differ in only one base-pair. For multi-class DNA classification problems, practitioners usually adopt approaches that use decision trees consisting of binary classifiers. Finding the best tree topology requires exploring all possible tree topologies and is computationally prohibitive. We propose a computational framework based on feature primitives that eliminates the need of a decision tree of binary classifiers. In the first phase, we generate a pool of weak features from nanopore blockade current measurements by using HMM analysis, principal component analysis and various wavelet filters. In the next phase, feature selection is performed using AdaBoost. AdaBoost provides an ensemble of weak learners of various types learned from feature primitives. RESULTS AND CONCLUSION: We show that our technique, despite its inherent simplicity, provides a performance comparable to recent multi-class DNA molecule classification results. Unlike the approach presented by Winters-Hilt et al., where weaker data is dropped to obtain better classification, the proposed approach provides comparable classification accuracy without any need for rejection of weak data. A weakness of this approach, on the other hand, is the very "hands-on" tuning and feature selection that is required to obtain good generalization. Simply put, this method obtains a more informed set of features and provides better results for that reason. The strength of this approach appears to be in its ability to identify strong features, an area where further results are actively being sought

The Effects of Time Varying Curvature on Species Transport in Coronary Arteries

Alterations in mass transport patterns of low-density lipoproteins (LDL) and oxygen are known to cause atherosclerosis in larger arteries. We hypothesise that the species transport processes in coronary arteries may be affected by their physiological motion, a factor which has not been considered widely in mass transfer studies. Hence, we numerically simulated the mass transport of LDL and oxygen in an idealized moving coronary artery model under both steady and pulsatile flow conditions. A physiological inlet velocity and a sinusoidal curvature waveform were specified as velocity and wall motion boundary conditions. The results predicted elevation of LDL flux, impaired oxygen flux and low wall shear stress (WSS) along the inner wall of curvature, a predilection site for atherosclerosis. The wall motion induced changes in the velocity and WSS patterns were only secondary to the pulsatile flow effects. The temporal variations in flow and WSS due to the flow pulsation and wall motion did not affect temporal changes in the species wall flux. However, the wall motion did alter the time-averaged oxygen and LDL flux in the order of 26% and 12% respectively. Taken together, these results suggest that the wall motion may play an important role in coronary arterial transport processes and emphasise the need for further investigation

Decoding accuracy in supplementary motor cortex correlates with perceptual sensitivity to tactile roughness

Perceptual sensitivity to tactile roughness varies across individuals for the same degree of roughness. A number of neurophysiological studies have investigated the neural substrates of tactile roughness perception, but the neural processing underlying the strong individual differences in perceptual roughness sensitivity remains unknown. In this study, we explored the human brain activation patterns associated with the behavioral discriminability of surface texture roughness using functional magnetic resonance imaging (fMRI). First, a wholebrain searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions from which we could decode roughness information. The searchlight MVPA revealed four brain regions showing significant decoding results: the supplementary motor area (SMA), contralateral postcentral gyrus (S1), and superior portion of the bilateral temporal pole (STP). Next, we evaluated the behavioral roughness discrimination sensitivity of each individual using the just-noticeable difference (JND) and correlated this with the decoding accuracy in each of the four regions. We found that only the SMA showed a significant correlation between neuronal decoding accuracy and JND across individuals; Participants with a smaller JND (i.e., better discrimination ability) exhibited higher decoding accuracy from their voxel response patterns in the SMA. Our findings suggest that multivariate voxel response patterns presented in the SMA represent individual perceptual sensitivity to tactile roughness and people with greater perceptual sensitivity to tactile roughness are likely to have more distinct neural representations of different roughness levels in their SMA. © 2015 Kim et al.close0

Dental Abnormalities in Schimke Immuno-osseous Dysplasia

Described for the first time in 1971, Schimke immuno-osseous dysplasia (SIOD) is an autosomal-recessive multisystem disorder that is caused by bi-allelic mutations of SMARCAL1, which encodes a DNA annealing helicase. To define better the dental anomalies of SIOD, we reviewed the records from SIOD patients with identified bi-allelic SMARCAL1 mutations, and we found that 66.0% had microdontia, hypodontia, or malformed deciduous and permanent molars. Immunohistochemical analyses showed expression of SMARCAL1 in all developing teeth, raising the possibility that the malformations are cell-autonomous consequences of SMARCAL1 deficiency. We also found that stimulation of cultured skin fibroblasts from SIOD patients with the tooth morphogens WNT3A, BMP4, and TGF beta 1 identified altered transcriptional responses, raising the hypothesis that the dental malformations arise in part from altered responses to developmental morphogens. To the best of our knowledge, this is the first systematic study of the dental anomalies associated with SIOD