Early postzygotic mutations contribute to de novo variation in a healthy monozygotic twin pair

Cataloged from PDF version of article.Background: Human de novo single-nucleotide variation (SNV) rate is estimated to range between 0.82-1.70×10-8 mutations per base per generation. However, contribution of early postzygotic mutations to the overall human de novo SNV rate is unknown. Methods: We performed deep whole-genome sequencing (more than 30-fold coverage per individual) of the whole-blood-derived DNA samples of a healthy monozygotic twin pair and their parents. We examined the genotypes of each individual simultaneously for each of the SNVs and discovered de novo SNVs regarding the timing of mutagenesis. Putative de novo SNVs were validated using Sanger-based capillary sequencing. Results: We conservatively characterised 23 de novo SNVs shared by the twin pair, 8 de novo SNVs specific to twin I and 1 de novo SNV specific to twin II. Based on the number of de novo SNVs validated by Sanger sequencing and the number of callable bases of each twin, we calculated the overall de novo SNV rate of 1.31×10-8 and 1.01×10-8 for twin I and twin II, respectively. Of these, rates of the early postzygotic de novo SNVs were estimated to be 0.34×10-8 for twin I and 0.04×10-8 for twin II. Conclusions: Early postzygotic mutations constitute a substantial proportion of de novo mutations in humans. Therefore, genome mosaicism resulting from early mitotic events during embryogenesis is common and could substantially contribute to the development of diseases

Effect of heat treatment on the wear and corrosion behaviors of a gray cast iron coated with a COLMONOY 88 alloy deposited by high velocity oxygen fuel (HVOF) thermal spray

The present work has been conducted in order to determine the influence of heat treatment on the wear and corrosion behaviours of a gray cast iron substrate coated with a Ni base coating deposited by HVOF thermal spray. The wear resistance of the coatings was obtained using a reciprocating wear tester by rubbing a 10 mm diameter steel ball on the coatings at normal atmospheric conditions. Corrosion tests were performed using potentiodynamic polarization measurements in a 3,5 % NaCl solution. It was observed that the corrosion and wear resistance of the coatings increased along with the reduction of porosity and roughness by the heat treatment

A Survey of Bayesian Statistical Approaches for Big Data

The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A natural question is how these approaches differ from those that were available prior to the advent of Big Data. We present a review of published studies that present Bayesian statistical approaches specifically for Big Data and discuss the reported and perceived benefits of these approaches. We conclude by addressing the question of whether focusing only on improving computational algorithms and infrastructure will be enough to face the challenges of Big Data

The ARID1B spectrum in 143 patients: from nonsyndromic intellectual disability to Coffin–Siris syndrome

Purpose: Pathogenic variants in ARID1B are one of the most frequent causes of intellectual disability (ID) as determined by large-scale exome sequencing studies. Most studies published thus far describe clinically diagnosed Coffin–Siris patients (ARID1B-CSS) and it is unclear whether these data are representative for patients identified through sequencing of unbiased ID cohorts (ARID1B-ID). We therefore sought to determine genotypic and phenotypic differences between ARID1B-ID and ARID1B-CSS. In parallel, we investigated the effect of different methods of phenotype reporting. Methods: Clinicians entered clinical data in an extensive web-based survey. Results: 79 ARID1B-CSS and 64 ARID1B-ID patients were included. CSS-associated dysmorphic features, such as thick eyebrows, long eyelashes, thick alae nasi, long and/or broad philtrum, small nails and small or absent fifth distal phalanx and hypertrichosis, were observed significantly more often (p < 0.001) in ARID1B-CSS patients. No other significant differences were identified. Conclusion: There are only minor differences between ARID1B-ID and ARID1B-CSS patients. ARID1B-related disorders seem to consist of a spectrum, and patients should be managed similarly. We demonstrated that data collection methods without an explicit option to report the absence of a feature (such as most Human Phenotype Ontology-based methods) tended to underestimate gene-related features

A multilayered perceptron neural network for a micro-coplanar strip line

This paper presents a new approach based on multilayered perceptrons (MLPs) to compute the characteristic impedance and the effective permittivity of the microcoplanar strip. Only one neural model is used to calculate the both parameters of the strip. An extended delta-bar-delta algorithm is used to train the MLP. The results obtained by using the MLP model are in very good agreement with the theoretical and experimental results reported elsewhere

Intelligent Face Mask Prediction System

Biometric based person identification systems are used to provide alternative solutions for security. Although many approaches and algorithms for biometric recognition techniques have been developed and proposed in the literature, relationships among biometric features have not been studied in the field so far. In this study, we have analysed the existence of any relationship between biometric features and we have tried to obtain a biometric feature of a person from another biometric feature of the same person. Consequently, we have designed and introduced a new and intelligent system using a novel approach based on artificial neural networks for generating face masks including eyes, nose and mouth from fingerprints with 0.75-3.60 absolute percent errors. Experimental results have demonstrated that it is possible to generate face masks from fingerprints without knowing any information about faces. In addition it is shown that fingerprints and faces are related to each other closely. In spite of the proposed system is initial study and it is still under development, the results are very encouraging and promising. Also proposed work is very important from view of the point that it is a new research area in biometrics

Artificial neural networks for the resonant resistance calculation of electrically thin and thick rectangular microstrip antennas

A new method for calculating the resonant resistance of electrically thin and thick rectangular microstrip path antennas, based on the artificial neural networks, is presented. The four learning algorithms, the backpropagation, the delta-bar-delta, the quick propagation, and the extended-delta-bar-delta, are used to train the networks. The theoretical resonant resistance results obtained by using this method are in very good agreement with the experimental results available in the literature