GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database.</p> <p>Results</p> <p>GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories.</p> <p>Conclusion</p> <p>GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at <url>http://cgs.pharm.kyoto-u.ac.jp/services/network</url>.</p

One-step synthesis of single-walled carbon nanohorns dispersed with Pd-Ni alloy nanoparticles by gas-injected arc-in-water method and effects of synthesis factors on their hydrogen sensor sensitivity

Single-walled carbon nanohorns (SWCNHs) dispersed with Pd-Ni alloy nanoparticles were synthesized in a technique requiring a single step by a gas-injected arc-in-water method using Pd-Ni-C mixed powders charged in an anode hole. It was found that the Ni/Pd weight ratio in the alloy nanoparticles dispersed in the products uniquely depended on the initial Ni/Pd weight ratio; Pd in the products was enriched by a factor of two when the Ni/Pd weight ratio in the initial mixture was higher than 0.1, while Ni was enriched at a Ni/Pd weight ratio below this threshold. The average diameter of alloy nanoparticles increased with the initial weight of the metallic components, while the average diameter of the discrete forms of the SWCNH aggregates exhibited the opposite tendency. Increasing the amount of the metallic compounds in the initial mixed powders caused the enrichment of Pd. The effect of adding Pd-Ni alloy nanoparticles into the products on the carbonaceous structures of SWCNHs was not detected by Raman analysis. The sensitivities of H2 sensors using the SWCNHs dispersed with Ni, Pd, and Pd-Ni alloy nanoparticles were compared, and the sensitivity of the sensor using the Pd-Ni alloy was the highest

Applicability of composite materials for space radiation shielding of spacecraft

Energetic ion beam experiments with major space radiation elements, 1H, 4He, 16O, 28Si and 56Fe, have been conducted to investigate the radiation shielding properties of composite materials. These materials are expected to be used for parts and fixtures of space vehicles due to both their mechanical strength and their space radiation shielding capabilities. Low Z materials containing hydrogen are effective for shielding protons and heavy ions due to their high stopping power and large fragmentation cross section per unit mass. The stopping power of the composite materials used in this work is intermediate between that of aluminum and polyethylene, which are typical structural and shielding materials used in space. The total charge-changing cross sections per unit mass, σUM, of the composite materials are 1.3–1.8 times larger than that of aluminum. By replacing conventional aluminum used for spacecraft with commercially available composite (carbon fiber / polyether ether ketone), it is expected that the shielding effect is increased by ~17%. The utilization of composite materials will help mitigate the space radiation hazard on future deep space missions

Investigation of shielding material properties for effective space radiation protection

Geant4 Monte Carlo simulations were carried out to investigate the possible shielding materials of aluminum, polyethylene, hydrides, complex hydrides and composite materials for radiation protection in spacecraft by considering two physical parameters, stopping power and fragmentation cross section. The dose reduction with shielding materials was investigated for Fe ions with energies of 500 MeV/n, 1 GeV/n and 2 GeV/n which are around the peak of the GCR energy spectrum. Fe ions easily stop in materials such as polyethylene and hydrides as opposed to materials such as aluminum and complex hydrides including high Z metals with contain little or no hydrogen. Attenuation of the primary particles in the shielding and fragmentation into more lightly charged and therefore more penetrating secondary particles are competing factors: attenuation acts to reduce the dose behind shielding while fragmentation increases it. Among hydrogenous materials, 6Li10BH4 was one of the more effective shielding materials as a function of mass providing a 20% greater dose reduction compared to polyethylene. Composite materials such as carbon fiber reinforced plastic and SiC composite plastic offer 1.9 times the dose reduction compared to aluminum as well as high mechanical strength. Composite materials have been found to be promising for spacecraft shielding, where both mass and volume are constrained

CRISIS AFAR: an international collaborative study of the impact of the COVID-19 pandemic on mental health and service access in youth with autism and neurodevelopmental conditions

BackgroundHeterogeneous mental health outcomes during the COVID-19 pandemic are documented in the general population. Such heterogeneity has not been systematically assessed in youth with autism spectrum disorder (ASD) and related neurodevelopmental disorders (NDD). To identify distinct patterns of the pandemic impact and their predictors in ASD/NDD youth, we focused on pandemic-related changes in symptoms and access to services.MethodsUsing a naturalistic observational design, we assessed parent responses on the Coronavirus Health and Impact Survey Initiative (CRISIS) Adapted For Autism and Related neurodevelopmental conditions (AFAR). Cross-sectional AFAR data were aggregated across 14 European and North American sites yielding a clinically well-characterized sample of N = 1275 individuals with ASD/NDD (age = 11.0 ± 3.6&nbsp;years; n females = 277). To identify subgroups with differential outcomes, we applied hierarchical clustering across eleven variables measuring changes in symptoms and access to services. Then, random forest classification assessed the importance of socio-demographics, pre-pandemic service rates, clinical severity of ASD-associated symptoms, and COVID-19 pandemic experiences/environments in predicting the outcome subgroups.ResultsClustering revealed four subgroups. One subgroup-broad symptom worsening only (20%)-included youth with worsening across a range of symptoms but with service disruptions similar to the average of the aggregate sample. The other three subgroups were, relatively, clinically stable but differed in service access: primarily modified services (23%), primarily lost services (6%), and average services/symptom changes (53%). Distinct combinations of a set of pre-pandemic services, pandemic environment (e.g., COVID-19 new cases, restrictions), experiences (e.g., COVID-19 Worries), and age predicted each outcome subgroup.LimitationsNotable limitations of the study are its cross-sectional nature and focus on the first six months of the pandemic.ConclusionsConcomitantly assessing variation in changes of symptoms and service access during the first phase of the pandemic revealed differential outcome profiles in ASD/NDD youth. Subgroups were characterized by distinct prediction patterns across a set of pre- and pandemic-related experiences/contexts. Results may inform recovery efforts and preparedness in future crises; they also underscore the critical value of international data-sharing and collaborations to address the needs of those most vulnerable in times of crisis