MERAV: a tool for comparing gene expression across human tissues and cell types

The oncogenic transformation of normal cells into malignant, rapidly proliferating cells requires major alterations in cell physiology. For example, the transformed cells remodel their metabolic processes to supply the additional demand for cellular building blocks. We have recently demonstrated essential metabolic processes in tumor progression through the development of a methodological analysis of gene expression. Here, we present the Metabolic gEne RApid Visualizer (MERAV, http://merav.wi.mit.edu), a web-based tool that can query a database comprising ∼4300 microarrays, representing human gene expression in normal tissues, cancer cell lines and primary tumors. MERAV has been designed as a powerful tool for whole genome analysis which offers multiple advantages: one can search many genes in parallel; compare gene expression among different tissue types as well as between normal and cancer cells; download raw data; and generate heatmaps; and finally, use its internal statistical tool. Most importantly, MERAV has been designed as a unique tool for analyzing metabolic processes as it includes matrixes specifically focused on metabolic genes and is linked to the Kyoto Encyclopedia of Genes and Genomes pathway search.United States. National Institutes of Health (CA103866)United States. National Institutes of Health (AI47389)Life Sciences Research FoundationMassachusetts Institute of Technology. Ludwig Center for Molecular OncologyHoward Hughes Medical Institut

Quantifying the impact of an extreme climate event on species diversity in fragmented temperate forests: the effect of the October 1987 storm on British broadleaved woodlands

1. We report the impact of an extreme weather event, the October 1987 severe storm, on fragmented woodlands in southern Britain. We analysed ecological changes between 1971 and 2002 in 143 200-m2 plots in 10 woodland sites exposed to the storm with an ecologically equivalent sample of 150 plots in 16 non-exposed sites. In both years, understorey species-richness, species composition, soil pH and woody basal area of the tree and shrub canopy were measured. 2. We tested the hypothesis that the storm had deflected sites from the wider national trajectory of an increase in woody basal area and reduced understorey species-richness associated with ageing canopies and declining woodland management. We also expected storm disturbance to amplify the background trend of increasing soil pH, a UK-wide response to reduced atmospheric sulphur deposition. Path analysis was used to quantify indirect effects of storm exposure on understorey species richness via changes in woody basal area and soil pH. 3. By 2002, storm exposure was estimated to have increased mean species richness per 200 m2 by 32%. Woody basal area changes were highly variable and did not significantly differ with storm exposure. 4. Increasing soil pH was associated with a 7% increase in richness. There was no evidence that soil pH increased more as a function of storm exposure. Changes in species richness and basal area were negatively correlated: a 3.4% decrease in richness occurred for every 0.1-m2 increase in woody basal area per plot. 5. Despite all sites substantially exceeding the empirical critical load for nitrogen deposition, there was no evidence that in the 15 years since the storm, disturbance had triggered a eutrophication effect associated with dominance of gaps by nitrophilous species. 6. Synthesis: Although the impacts of the 1987 storm were spatially variable in terms of impacts on woody basal area, the storm had a positive effect on understorey species richness. There was no evidence that disturbance had increased dominance of gaps by invasive species. This could change if recovery from acidification results in a soil pH regime associated with greater macronutrient availability

The SAMI Galaxy Survey: Shocks and Outflows in a normal star-forming galaxy

We demonstrate the feasibility and potential of using large integral field spectroscopic surveys to investigate the prevalence of galactic-scale outflows in the local Universe. Using integral field data from SAMI and the Wide Field Spectrograph, we study the nature of an isolated disk galaxy, SDSS J090005.05+000446.7 (z = 0.05386). In the integral field datasets, the galaxy presents skewed line profiles changing with position in the galaxy. The skewed line profiles are caused by different kinematic components overlapping in the line-of-sight direction. We perform spectral decomposition to separate the line profiles in each spatial pixel as combinations of (1) a narrow kinematic component consistent with HII regions, (2) a broad kinematic component consistent with shock excitation, and (3) an intermediate component consistent with shock excitation and photoionisation mixing. The three kinematic components have distinctly different velocity fields, velocity dispersions, line ratios, and electron densities. We model the line ratios, velocity dispersions, and electron densities with our MAPPINGS IV shock and photoionisation models, and we reach remarkable agreement between the data and the models. The models demonstrate that the different emission line properties are caused by major galactic outflows that introduce shock excitation in addition to photoionisation by star-forming activities. Interstellar shocks embedded in the outflows shock-excite and compress the gas, causing the elevated line ratios, velocity dispersions, and electron densities observed in the broad kinematic component. We argue from energy considerations that, with the lack of a powerful active galactic nucleus, the outflows are likely to be driven by starburst activities. Our results set a benchmark of the type of analysis that can be achieved by the SAMI Galaxy Survey on large numbers of galaxies.Comment: 17 pages, 15 figures. Accepted to MNRAS. References update

Fibulin-1 is required for morphogenesis of neural crest-derived structures

AbstractHere we report that mouse embryos homozygous for a gene trap insertion in the fibulin-1 (Fbln1) gene are deficient in Fbln1 and exhibit cardiac ventricular wall thinning and ventricular septal defects with double outlet right ventricle or overriding aorta. Fbln1 nulls also display anomalies of aortic arch arteries, hypoplasia of the thymus and thyroid, underdeveloped skull bones, malformations of cranial nerves and hemorrhagic blood vessels in the head and neck. The spectrum of malformations is consistent with Fbln1 influencing neural crest cell (NCC)-dependent development of these tissues. This is supported by evidence that Fbln1 expression is associated with streams of cranial NCCs migrating adjacent to rhombomeres 2–7 and that Fbln1-deficient embryos display patterning anomalies of NCCs forming cranial nerves IX and X, which derive from rhombomeres 6 and 7. Additionally, Fbln1-deficient embryos show increased apoptosis in areas populated by NCCs derived from rhombomeres 4, 6 and 7. Based on these findings, it is concluded that Fbln1 is required for the directed migration and survival of cranial NCCs contributing to the development of pharyngeal glands, craniofacial skeleton, cranial nerves, aortic arch arteries, cardiac outflow tract and cephalic blood vessels

Joint analysis of stressors and ecosystem services to enhance restoration effectiveness

With increasing pressure placed on natural systems by growing human populations, both scientists and resource managers need a better understanding of the relationships between cumulative stress from human activities and valued ecosystem services. Societies often seek to mitigate threats to these services through large-scale, costly restoration projects, such as the over one billion dollar Great Lakes Restoration Initiative currently underway. To help inform these efforts, we merged high-resolution spatial analyses of environmental stressors with mapping of ecosystem services for all five Great Lakes. Cumulative ecosystem stress is highest in near-shore habitats, but also extends offshore in Lakes Erie, Ontario, and Michigan. Variation in cumulative stress is driven largely by spatial concordance among multiple stressors, indicating the importance of considering all stressors when planning restoration activities. In addition, highly stressed areas reflect numerous different combinations of stressors rather than a single suite of problems, suggesting that a detailed understanding of the stressors needing alleviation could improve restoration planning. We also find that many important areas for fisheries and recreation are subject to high stress, indicating that ecosystem degradation could be threatening key services. Current restoration efforts have targeted high-stress sites almost exclusively, but generally without knowledge of the full range of stressors affecting these locations or differences among sites in service provisioning. Our results demonstrate that joint spatial analysis of stressors and ecosystem services can provide a critical foundation for maximizing social and ecological benefits from restoration investments. www.pnas.org/lookup/suppl/doi:10.1073/pnas.1213841110/-/DCSupplementa

Risk algorithm using serial biomarker measurements doubles the number of screen-detected cancers compared with a single-threshold rule in the United Kingdom collaborative trial of ovarian cancer screening

PURPOSE: Cancer screening strategies have commonly adopted single-biomarker thresholds to identify abnormality. We investigated the impact of serial biomarker change interpreted through a risk algorithm on cancer detection rates. PATIENTS AND METHODS: In the United Kingdom Collaborative Trial of Ovarian Cancer Screening, 46,237 women, age 50 years or older underwent incidence screening by using the multimodal strategy (MMS) in which annual serum cancer antigen 125 (CA-125) was interpreted with the risk of ovarian cancer algorithm (ROCA). Women were triaged by the ROCA: normal risk, returned to annual screening; intermediate risk, repeat CA-125; and elevated risk, repeat CA-125 and transvaginal ultrasound. Women with persistently increased risk were clinically evaluated. All participants were followed through national cancer and/or death registries. Performance characteristics of a single-threshold rule and the ROCA were compared by using receiver operating characteristic curves. RESULTS: After 296,911 women-years of annual incidence screening, 640 women underwent surgery. Of those, 133 had primary invasive epithelial ovarian or tubal cancers (iEOCs). In all, 22 interval iEOCs occurred within 1 year of screening, of which one was detected by ROCA but was managed conservatively after clinical assessment. The sensitivity and specificity of MMS for detection of iEOCs were 85.8% (95% CI, 79.3% to 90.9%) and 99.8% (95% CI, 99.8% to 99.8%), respectively, with 4.8 surgeries per iEOC. ROCA alone detected 87.1% (135 of 155) of the iEOCs. Using fixed CA-125 cutoffs at the last annual screen of more than 35, more than 30, and more than 22 U/mL would have identified 41.3% (64 of 155), 48.4% (75 of 155), and 66.5% (103 of 155), respectively. The area under the curve for ROCA (0.915) was significantly (P = .0027) higher than that for a single-threshold rule (0.869). CONCLUSION: Screening by using ROCA doubled the number of screen-detected iEOCs compared with a fixed cutoff. In the context of cancer screening, reliance on predefined single-threshold rules may result in biomarkers of value being discarded

The Land Suitability Rating System Is a Spatial Planning Tool to Assess Crop Suitability in Canada

The Land Suitability Rating System (LSRS) is a rule-based set of algorithms that integrate soil, climate and landscape factors to calculate a classed suitability rating for a given landscape to support commercial field crop production. The attributes used to define each of the factors are based on their proven ability to affect crop growth, their ability to be measured (or estimated by proxy) and their availability in accessible databases. The LSRS was first published in 1995 by Agriculture and Agri-Food Canada as a site-specific, manual calculator for spring-seeded small grains that incorporated sets of attribute point deduction curves based on expert knowledge. Since that time the system has been expanded to include additional crop modules and all data handling and calculations are automated through a set of web-based applications. The current version of LSRS (version 5) is implemented in Ruby on Rails® software as a suite of web services. The system runs against any soil map with standardized Canadian Soil Information Service soil data tables to process soil attributes and calculate limitations to crop growth. A climate factor rating is based on crop-specific agro-climatic indices and thresholds. Climatic indices have historically been calculated from 30-year climate normal periods using monthly data but LSRS can now also utilize daily data records which facilitate trend analyses within annual historic records. The use of available gridded climate datasets enables direct overlay and extraction of climate attributes to the spatial extent of soil map polygons. Lastly, the system incorporates a landscape factor related to land erodibility and constraints to management. Each of the three suitability factors is assigned a class rating between 1 (no limitations) and 7 (unsuitable) with the final overall rating being the most limiting of the three factors. Recent improvements in the ability of the system to process multiple climate datasets mean outputs from Global Circulation Models may also be useful for the LSRS model in assessing possible impacts of climate change on crop suitability. LSRS is used increasingly as a spatial research tool in assessing potential changes in crop distributions at both national and regional scales

Incorporating New Technologies Into Toxicity Testing and Risk Assessment: Moving From 21st Century Vision to a Data-Driven Framework

Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency

Managing marine disease emergencies in an era of rapid change

Infectious marine diseases can decimate populations and are increasing among some taxa due to global change and our increasing reliance on marine environments. Marine diseases become emergencies when significant ecological, economic or social impacts occur. We can prepare for and manage these emergencies through improved surveillance, and the development and iterative refinement of approaches to mitigate disease and its impacts. Improving surveillance requires fast, accurate diagnoses, forecasting disease risk and real-time monitoring of disease-promoting environmental conditions. Diversifying impact mitigation involves increasing host resilience to disease, reducing pathogen abundance and managing environmental factors that facilitate disease. Disease surveillance and mitigation can be adaptive if informed by research advances and catalysed by communication among observers, researchers and decision-makers using information-sharing platforms. Recent increases in the awareness of the threats posed by marine diseases may lead to policy frameworks that facilitate the responses and management that marine disease emergencies require