Laser Ultrasonics as an Alternative Inspection Method to Detect Microstructural Flaws in Aerospace Structures and Engines Manufactured by Advanced Metallic Material Processes

Peer reviewed: YesNRC publication: Ye

Do adults with high functioning autism or Asperger Syndrome differ in empathy and emotion recognition?

The present study examined whether adults with high functioning autism (HFA) showed greater difficulties in (i) their self-reported ability to empathise with others and/or (ii) their ability to read mental states in others’ eyes than adults with Asperger syndrome (AS). The Empathy Quotient (EQ) and ‘Reading the Mind in the Eyes’ Test (Eyes Test) were compared in 43 adults with AS and 43 adults with HFA. No significant difference was observed on EQ score between groups, while adults with AS performed significantly better on the Eyes Test than those with HFA. This suggests that adults with HFA may need more support, particularly in mentalizing and complex emotion recognition, and raises questions about the existence of subgroups within autism spectrum conditions

Learning pair-wise gene functional similarity by multiplex gene expression maps

Abstract Background The relationships between the gene functional similarity and gene expression profile, and between gene function annotation and gene sequence have been studied extensively. However, not much work has considered the connection between gene functions and location of a gene's expression in the mammalian tissues. On the other hand, although unsupervised learning methods have been commonly used in functional genomics, supervised learning cannot be directly applied to a set of normal genes without having a target (class) attribute. Results Here, we propose a supervised learning methodology to predict pair-wise gene functional similarity from multiplex gene expression maps that provide information about the location of gene expression. The features are extracted from expression maps and the labels denote the functional similarities of pairs of genes. We make use of wavelet features, original expression values, difference and average values of neighboring voxels and other features to perform boosting analysis. The experimental results show that with increasing similarities of gene expression maps, the functional similarities are increased too. The model predicts the functional similarities between genes to a certain degree. The weights of the features in the model indicate the features that are more significant for this prediction. Conclusions By considering pairs of genes, we propose a supervised learning methodology to predict pair-wise gene functional similarity from multiplex gene expression maps. We also explore the relationship between similarities of gene maps and gene functions. By using AdaBoost coupled with our proposed weak classifier we analyze a large-scale gene expression dataset and predict gene functional similarities. We also detect the most significant single voxels and pairs of neighboring voxels and visualize them in the expression map image of a mouse brain. This work is very important for predicting functions of unknown genes. It also has broader applicability since the methodology can be applied to analyze any large-scale dataset without a target attribute and is not restricted to gene expressions

Autism Symptoms and Internalizing Psychopathology in Girls and Boys with Autism Spectrum Disorders

Findings regarding phenotypic differences between boys and girls with ASD are mixed. We compared autism and internalizing symptoms in a sample of 8-18 year-old girls (n = 20) and boys (n = 20) with ASD and typically developing (TYP) girls (n = 19) and boys (n = 17). Girls with ASD were more impaired than TYP girls but did not differ from boys with ASD in autism symptoms. In adolescence, girls with ASD had higher internalizing symptoms than boys with ASD and TYP girls, and higher symptoms of depression than TYP girls. Girls ages 8-18 with ASD resemble boys with ASD and not TYP girls, and appear to be at increased risk for affective symptoms in the teen years

Genomic and epigenetic evidence for oxytocin receptor deficiency in autism

<p>Abstract</p> <p>Background</p> <p>Autism comprises a spectrum of behavioral and cognitive disturbances of childhood development and is known to be highly heritable. Although numerous approaches have been used to identify genes implicated in the development of autism, less than 10% of autism cases have been attributed to single gene disorders.</p> <p>Methods</p> <p>We describe the use of high-resolution genome-wide tilepath microarrays and comparative genomic hybridization to identify copy number variants within 119 probands from multiplex autism families. We next carried out DNA methylation analysis by bisulfite sequencing in a proband and his family, expanding this analysis to methylation analysis of peripheral blood and temporal cortex DNA of autism cases and matched controls from independent datasets. We also assessed oxytocin receptor (OXTR) gene expression within the temporal cortex tissue by quantitative real-time polymerase chain reaction (PCR).</p> <p>Results</p> <p>Our analysis revealed a genomic deletion containing the oxytocin receptor gene, <it>OXTR </it>(MIM accession no.: 167055), previously implicated in autism, was present in an autism proband and his mother who exhibits symptoms of obsessive-compulsive disorder. The proband's affected sibling did not harbor this deletion but instead may exhibit epigenetic misregulation of this gene through aberrant gene silencing by DNA methylation. Further DNA methylation analysis of the CpG island known to regulate <it>OXTR </it>expression identified several CpG dinucleotides that show independent statistically significant increases in the DNA methylation status in the peripheral blood cells and temporal cortex in independent datasets of individuals with autism as compared to control samples. Associated with the increase in methylation of these CpG dinucleotides is our finding that <it>OXTR </it>mRNA showed decreased expression in the temporal cortex tissue of autism cases matched for age and sex compared to controls.</p> <p>Conclusion</p> <p>Together, these data provide further evidence for the role of OXTR and the oxytocin signaling pathway in the etiology of autism and, for the first time, implicate the epigenetic regulation of <it>OXTR </it>in the development of the disorder.</p> <p>See the related commentary by Gurrieri and Neri: <url>http://www.biomedcentral.com/1741-7015/7/63</url></p

Effectiveness of dual-task functional power training for preventing falls in older people: Study protocol for a cluster randomised controlled trial

Background: Falls are a major public health concern with at least one third of people aged 65 years and over falling at least once per year, and half of these will fall repeatedly, which can lead to injury, pain, loss of function and independence, reduced quality of life and even death. Although the causes of falls are varied and complex, the age-related loss in muscle power has emerged as a useful predictor of disability and falls in older people. In this population, the requirements to produce explosive and rapid movements often occurs whilst simultaneously performing other attention-demanding cognitive or motor tasks, such as walking while talking or carrying an object. The primary aim of this study is to determine whether dual-task functional power training (DT-FPT) can reduce the rate of falls in community-dwelling older people. Methods/Design: The study design is an 18-month cluster randomised controlled trial in which 280 adults aged =65 years residing in retirement villages, who are at increased risk of falling, will be randomly allocated to: 1) an exercise programme involving DT-FPT, or 2) a usual care control group. The intervention is divided into 3 distinct phases: 6 months of supervised DT-FPT, a 6-month 'step down' maintenance programme, and a 6-month follow-up. The primary outcome will be the number of falls after 6, 12 and 18 months. Secondary outcomes will include: lower extremity muscle power and strength, grip strength, functional assessments of gait, reaction time and dynamic balance under single- and dual-task conditions, activities of daily living, quality of life, cognitive function and falls-related self-efficacy. We will also evaluate the cost-effectiveness of the programme for preventing falls. Discussion: The study offers a novel approach that may guide the development and implementation of future community-based falls prevention programmes that specifically focus on optimising muscle power and dual-task performance to reduce falls risk under 'real life' conditions in older adults. In addition, the 'step down' programme will provide new information about the efficacy of a less intensive maintenance programme for reducing the risk of falls over an extended period. Trial registration: Australian New Zealand Clinical Trials Registry: ACTRN12613001161718. Date registered 23 October 2013

Methodological approaches in application of synthetic lethality screening towards anticancer therapy

A promising direction in the development of selective less toxic cancer drugs is the usage of synthetic lethality concept. The availability of large-scale synthetic low-molecular-weight chemical libraries has allowed HTS for compounds synergistic lethal with defined human cancer aberrations in activated oncogenes or tumour suppressor genes. The search for synthetic lethal chemicals in human/mouse tumour cells is greatly aided by a prior knowledge of relevant signalling and DNA repair pathways, allowing for educated guesses on the preferred potential therapeutic targets. The recent generation of human/rodents genome-wide siRNAs, and shRNA-expressing libraries, should further advance this more focused approach to cancer drug discovery

GOLIAH (Gaming Open Library for Intervention in Autism at Home): a 6-month single blind matched controlled exploratory study

BackgroundTo meet the required hours of intensive intervention for treating children with autism spectrum disorder (ASD), we developed an automated serious gaming platform (11 games) to deliver intervention at home (GOLIAH) by mapping the imitation and joint attention (JA) subset of age-adapted stimuli from the Early Start Denver Model (ESDM) intervention. Here, we report the results of a 6-month matched controlled exploratory study.MethodsFrom two specialized clinics, we included 14 children (age range 5–8 years) with ASD and 10 controls matched for gender, age, sites, and treatment as usual (TAU). Participants from the experimental group received in addition to TAU four 30-min sessions with GOLIAH per week at home and one at hospital for 6 months. Statistics were performed using Linear Mixed Models.ResultsChildren and parents participated in 40% of the planned sessions. They were able to use the 11 games, and participants trained with GOLIAH improved time to perform the task in most JA games and imitation scores in most imitation games. GOLIAH intervention did not affect Parental Stress Index scores. At end-point, we found in both groups a significant improvement for Autism Diagnostic Observation Schedule scores, Vineland socialization score, Parental Stress Index total score, and Child Behavior Checklist internalizing, externalizing and total problems. However, we found no significant change for by time × group interaction.ConclusionsDespite the lack of superiority of TAU + GOLIAH versus TAU, the results are interesting both in terms of changes by using the gaming platform and lack of parental stress increase. A large randomized controlled trial with younger participants (who are the core target of ESDM model) is now discussed. This should be facilitated by computing GOLIAH for a web platform.Trial registration Clinicaltrials.gov NCT0256041

Incorporating functional inter-relationships into protein function prediction algorithms

<p>Abstract</p> <p>Background</p> <p>Functional classification schemes (e.g. the Gene Ontology) that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction algorithms have been developed, few previous efforts have utilized more than the protein-to-functional class label information provided by such knowledge bases. For instance, the Gene Ontology not only captures protein annotations to a set of functional classes, but it also arranges these classes in a DAG-based hierarchy that captures rich inter-relationships between different classes. These inter-relationships present both opportunities, such as the potential for additional training examples for small classes from larger related classes, and challenges, such as a harder to learn distinction between similar GO terms, for standard classification-based approaches.</p> <p>Results</p> <p>We propose a method to enhance the performance of classification-based protein function prediction algorithms by addressing the issue of using these interrelationships between functional classes constituting functional classification schemes. Using a standard measure for evaluating the semantic similarity between nodes in an ontology, we quantify and incorporate these inter-relationships into the <it>k</it>-nearest neighbor classifier. We present experiments on several large genomic data sets, each of which is used for the modeling and prediction of over hundred classes from the GO Biological Process ontology. The results show that this incorporation produces more accurate predictions for a large number of the functional classes considered, and also that the classes benefitted most by this approach are those containing the fewest members. In addition, we show how our proposed framework can be used for integrating information from the entire GO hierarchy for improving the accuracy of predictions made over a set of base classes. Finally, we provide qualitative and quantitative evidence that this incorporation of functional inter-relationships enables the discovery of interesting biology in the form of novel functional annotations for several yeast proteins, such as Sna4, Rtn1 and Lin1.</p> <p>Conclusion</p> <p>We implemented and evaluated a methodology for incorporating interrelationships between functional classes into a standard classification-based protein function prediction algorithm. Our results show that this incorporation can help improve the accuracy of such algorithms, and help uncover novel biology in the form of previously unknown functional annotations. The complete source code, a sample data set and the additional files for this paper are available free of charge for non-commercial use at <url>http://www.cs.umn.edu/vk/gaurav/functionalsimilarity/</url>.</p