Climate Change and invasibility of the Antarctic benthos

Benthic communities living in shallow-shelf habitats in Antarctica (<100-m depth) are archaic in their structure and function. Modern predators, including fast-moving, durophagous (skeleton-crushing) bony fish, sharks, and crabs, are rare or absent; slow-moving invertebrates are the top predators; and epifaunal suspension feeders dominate many soft substratum communities. Cooling temperatures beginning in the late Eocene excluded durophagous predators, ultimately resulting in the endemic living fauna and its unique food-web structure. Although the Southern Ocean is oceanographically isolated, the barriers to biological invasion are primarily physiological rather than geographic. Cold temperatures impose limits to performance that exclude modern predators. Global warming is now removing those physiological barriers, and crabs are reinvading Antarctica. As sea temperatures continue to rise, the invasion of durophagous predators will modernize the shelf benthos and erode the indigenous character of marine life in Antarctica

Branch&Rank for Efficient Object Detection

Ranking hypothesis sets is a powerful concept for efficient object detection. In this work, we propose a branch&rank scheme that detects objects with often less than 100 ranking operations. This efficiency enables the use of strong and also costly classifiers like non-linear SVMs with RBF-χ2 kernels. We thereby relieve an inherent limitation of branch&bound methods as bounds are often not tight enough to be effective in practice. Our approach features three key components: a ranking function that operates on sets of hypotheses and a grouping of these into different tasks. Detection efficiency results from adaptively sub-dividing the object search space into decreasingly smaller sets. This is inherited from branch&bound, while the ranking function supersedes a tight bound which is often unavailable (except for rather limited function classes). The grouping makes the system effective: it separates image classification from object recognition, yet combines them in a single formulation, phrased as a structured SVM problem. A novel aspect of branch&rank is that a better ranking function is expected to decrease the number of classifier calls during detection. We use the VOC’07 dataset to demonstrate the algorithmic properties of branch&rank.ISSN:0920-5691ISSN:1573-140

Search for intracranial aneurysm susceptibility gene(s) using Finnish families

BACKGROUND: Cerebrovascular disease is the third leading cause of death in the United States, and about one-fourth of cerebrovascular deaths are attributed to ruptured intracranial aneurysms (IA). Epidemiological evidence suggests that IAs cluster in families, and are therefore probably genetic. Identification of individuals at risk for developing IAs by genetic tests will allow concentration of diagnostic imaging on high-risk individuals. We used model-free linkage analysis based on allele sharing with a two-stage design for a genome-wide scan to identify chromosomal regions that may harbor IA loci. METHODS: We previously estimated sibling relative risk in the Finnish population at between 9 and 16, and proceeded with a genome-wide scan for loci predisposing to IA. In 85 Finnish families with two or more affected members, 48 affected sibling pairs (ASPs) were available for our genetic study. Power calculations indicated that 48 ASPs were adequate to identify chromosomal regions likely to harbor predisposing genes and that a liberal stage I lod score threshold of 0.8 provided a reasonable balance between detection of false positive regions and failure to detect real loci with moderate effect. RESULTS: Seven chromosomal regions exceeded the stage I lod score threshold of 0.8 and five exceeded 1.0. The most significant region, on chromosome 19q, had a maximum multipoint lod score (MLS) of 2.6. CONCLUSIONS: Our study provides evidence for the locations of genes predisposing to IA. Further studies are necessary to elucidate the genes and their role in the pathophysiology of IA, and to design genetic tests

Multiplicity: an organizing principle for cancers and somatic mutations

<p>Abstract</p> <p>Background</p> <p>With the advent of whole-genome analysis for profiling tumor tissue, a pressing need has emerged for principled methods of organizing the large amounts of resulting genomic information. We propose the concept of multiplicity measures on cancer and gene networks to organize the information in a clinically meaningful manner. Multiplicity applied in this context extends Fearon and Vogelstein's multi-hit genetic model of colorectal carcinoma across multiple cancers.</p> <p>Methods</p> <p>Using the Catalogue of Somatic Mutations in Cancer (COSMIC), we construct networks of interacting cancers and genes. Multiplicity is calculated by evaluating the number of cancers and genes linked by the measurement of a somatic mutation. The Kamada-Kawai algorithm is used to find a two-dimensional minimum energy solution with multiplicity as an input similarity measure. Cancers and genes are positioned in two dimensions according to this similarity. A third dimension is added to the network by assigning a maximal multiplicity to each cancer or gene. Hierarchical clustering within this three-dimensional network is used to identify similar clusters in somatic mutation patterns across cancer types.</p> <p>Results</p> <p>The clustering of genes in a three-dimensional network reveals a similarity in acquired mutations across different cancer types. Surprisingly, the clusters separate known causal mutations. The multiplicity clustering technique identifies a set of causal genes with an area under the ROC curve of 0.84 versus 0.57 when clustering on gene mutation rate alone. The cluster multiplicity value and number of causal genes are positively correlated via Spearman's Rank Order correlation (<it>r_s</it>(8) = 0.894, Spearman's <it>t </it>= 17.48, <it>p </it>< 0.05). A clustering analysis of cancer types segregates different types of cancer. All blood tumors cluster together, and the cluster multiplicity values differ significantly (Kruskal-Wallis, <it>H </it>= 16.98, <it>df </it>= 2, <it>p </it>< 0.05).</p> <p>Conclusion</p> <p>We demonstrate the principle of multiplicity for organizing somatic mutations and cancers in clinically relevant clusters. These clusters of cancers and mutations provide representations that identify segregations of cancer and genes driving cancer progression.</p

The utility and predictive value of combinations of low penetrance genes for screening and risk prediction of colorectal cancer

Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., ~140–160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual’s CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci associated with CRC before the question of the potential utility of germline genomic profiling can be definitively answered

Changes in global groundwater organic carbon driven by climate change and urbanization

YesClimate change and urbanization can increase pressures on groundwater resources, but little is known about how groundwater quality will change. Here, we rely on a global synthesis (n = 9,404) to reveal the drivers of dissolved organic carbon (DOC), which is an important component of water chemistry and substrate for microorganisms which control many biogeochemical reactions. Groundwater ions, local climate and land use explained ~ 31% of observed variability in groundwater DOC, whilst aquifer age explained an additional 16%. We identify a 19% increase in DOC associated with urban land cover. We predict major groundwater DOC increases following changes in precipitation and temperature in key areas relying on groundwater. Climate change and conversion of natural or agricultural areas to urban areas will decrease groundwater quality and increase water treatment costs, compounding existing threats to groundwater resources

Joint effect of phosphorus limitation and temperature on alkaline phosphatase activity and somatic growth in Daphnia magna

Alkaline phosphatase (AP) is a potential biomarker for phosphorus (P) limitation in zooplankton. However, knowledge about regulation of AP in this group is limited. In a laboratory acclimation experiment, we investigated changes in body AP concentration for Daphnia magna kept for 6 days at 10, 15, 20 and 25°C and fed algae with 10 different molar C:P ratios (95–660). In the same experiment, we also assessed somatic growth of the animals since phosphorus acquisition is linked to growth processes. Overall, non-linear but significant relationships of AP activity with C:P ratio were observed, but there was a stronger impact of temperature on AP activity than of P limitation. Animals from the lowest temperature treatment had higher normalized AP activity, which suggests the operation of biochemical temperature compensation mechanisms. Body AP activity increased by a factor of 1.67 for every 10°C decrease in temperature. These results demonstrate that temperature strongly influences AP expression. Therefore, using AP as a P limitation marker in zooplankton needs to consider possible confounding effects of temperature. Both temperature and diet affected somatic growth. The temperature effect on somatic growth, expressed as the Q10 value, responded non-linearly with C:P, with Q10 ranging between 1.9 for lowest food C:P ratio and 1.4 for the most P-deficient food. The significant interaction between those two variables highlights the importance of studying temperature-dependent changes of growth responses to food quality

Hydrochemical system analysis of public supply well fields, to reveal water-quality patterns and define groundwater bodies:The Netherlands

Hydrochemical system analysis (HCSA) is used to better understand the individual state of and spatial patterns in groundwater quality, by addressing the spatial distribution of groundwater bodies with specific origins (hydrosomes) and characteristic hydrochemical zones within each hydrosome (facies). The origin is determined by environmental tracers or geomorphological and potentiometric maps, the facies by combining age, redox and alkalinity indices. The HCSA method is applied to all 206 active public supply well fields (PSWFs) in The Netherlands, resulting in the distinction of nine hydrosomes and eleven facies parameters-age (young, intermediate, old), redox ((sub)oxic, anoxic, deep anoxic, mixed) and alkalinity (very low, low, intermediate and high). The resulting classification of PSWFs provides a means to (1) predict their vulnerability; (2) optimize groundwater-quality monitoring programs; and (3) better delineate groundwater bodies, by considering groundwater origin and flow. The HCSA translates complex hydrochemical patterns into easily interpretable maps by showing PSWFs, groundwater bodies and hydrochemical facies. Such maps facilitate communication between researchers, water resources managers and policy makers and can help to solve complex groundwater resources management problems at different scales, ranging from a single well(field) or region to the national or European scale. © 2010 Springer-Verlag