The genome sequence and structure of rice chromosome 1

The rice species Oryza sativa is considered to be a model plant because of its small genome size, extensive genetic map, relative ease of transformation and synteny with other cereal crops. Here we report the essentially complete sequence of chromosome 1, the longest chromosome in the rice genome. We summarize characteristics of the chromosome structure and the biological insight gained from the sequence. The analysis of 43.3 megabases (Mb) of non-overlapping sequence reveals 6,756 protein coding genes, of which 3,161 show homology to proteins of Arabidopsis thaliana, another model plant. About 30% (2,073) of the genes have been functionally categorized. Rice chromosome 1 is (G + C)-rich, especially in its coding regions, and is characterized by several gene families that are dispersed or arranged in tandem repeats. Comparison with a draft sequence indicates the importance of a high-quality finished sequence.     

Mutations of the BRAF gene in human cancer

Cancers arise owing to the accumulation of mutations in critical genes that alter normal programmes of cell proliferation, differentiation and death. As the first stage of a systematic genome-wide screen for these genes, we have prioritized for analysis signalling pathways in which at least one gene is mutated in human cancer. The RAS RAF MEK ERK MAP kinase pathway mediates cellular responses to growth signals. RAS is mutated to an oncogenic form in about 15% of human cancer. The three RAF genes code for cytoplasmic serine/threonine kinases that are regulated by binding RAS. Here we report BRAF somatic missense mutations in 66% of malignant melanomas and at lower frequency in a wide range of human cancers. All mutations are within the kinase domain, with a single substitution (V599E) accounting for 80%. Mutated BRAF proteins have elevated kinase activity and are transforming in NIH3T3 cells. Furthermore, RAS function is not required for the growth of cancer cell lines with the V599E mutation. As BRAF is a serine/threonine kinase that is commonly activated by somatic point mutation in human cancer, it may provide new therapeutic opportunities in malignant melanoma.     

The impact of surface-adsorbed phosphorus on phytoplankton Redfield stoichiometry

The Redfield ratio of 106 carbon:16 nitrogen:1 phosphorus in marine phytoplankton is one of the foundations of ocean biogeochemistry, with applications in algal physiology, palaeoclimatology and global climate change. However, this ratio varies substantially in response to changes in algal nutrient status and taxonomic affiliation. Here we report that Redfield ratios are also strongly affected by partitioning into surface-adsorbed and intracellular phosphorus pools. The C:N:surface-adsorbed P (80-105 C:15-18 N:1 P) and total (71-80 C:13-14 N:1 P) ratios in natural populations and cultures of Trichodesmium were close to Redfield values and not significantly different from each other. In contrast, intracellular ratios consistently exceeded the Redfield ratio (316-434 C:59-83 N:1 intracellular P). These high intracellular ratios were associated with reduced N2 fixation rates, suggestive of phosphorus deficiency. Other algal species also have substantial surface-adsorbed phosphorus pools, suggesting that our Trichodesmium results are generally applicable to all phytoplankton. Measurements of the distinct phytoplankton phosphorus pools may be required to assess nutrient limitation accurately from elemental composition. Deviations from Redfield stoichiometry may be attributable to surface adsorption of phosphorus rather than to biological processes, and this scavenging could affect the interpretation of marine nutrient inventories and ecosystem models.     

A New Dimension Reduction Method: Factor Discriminant K-means

Reduced K-means (RKM) and Factorial K-means (FKM) are two data reduction techniques incorporating principal component analysis and K-means into a unified methodology to obtain a reduced set of components for variables and an optimal partition for objects. RKM finds clusters in a reduced space by maximizing the between-clusters deviance without imposing any condition on the within-clusters deviance, so that clusters are isolated but they might be heterogeneous. On the other hand, FKM identifies clusters in a reduced space by minimizing the within-clusters deviance without imposing any condition on the between-clusters deviance. Thus, clusters are homogeneous, but they might not be isolated. The two techniques give different results because the total deviance in the reduced space for the two methodologies is not constant; hence the minimization of the within-clusters deviance is not equivalent to the maximization of the between-clusters deviance. In this paper a modification of the two techniques is introduced to avoid the afore mentioned weaknesses. It is shown that the two modified methods give the same results, thus merging RKM and FKM into a new methodology. It is called Factor Discriminant K-means (FDKM), because it combines Linear Discriminant Analysis and K-means. The paper examines several theoretical properties of FDKM and its performances with a simulation study. An application on real-world data is presented to show the features of FDKM.     

A network analysis of the 2010 FIFA world cup champion team play

This paper analyzes the network of passes among the players of the Spanish team during the last FIFA World Cup 2010, where they emerged as the champion, with the objective of explaining the results obtained from the behavior at the complex network level. The team is considered a network with players as nodes and passes as (directed) edges. A temporal analysis of the resulting passes network is also done, looking at the number of passes, length of the chain of passes, and to network measures such as player centrality and clustering coefficient. Results of the last three matches (the decisive ones) indicate that the clustering coefficient of the pass network remains high, indicating the elaborate style of the Spanish team. The effectiveness of the opposing team in negating the Spanish game is reflected in the change of several network measures over time, most importantly in drops of the clustering coefficient and passing length/speed, as well as in their being able in removing the most talented players from the central positions of the network. Spain’s ability to restore their combinative game and move the focus of the game to offensive positions and talented players is shown to tilt the balance in favor of the Spanish team.     

Accurate Tree-based Missing Data Imputation and Data Fusion within the Statistical Learning Paradigm

Framework of this paper is statistical data editing, specifically how to edit or impute missing or contradictory data and how to merge two independent data sets presenting some lack of information. Assuming a missing at random mechanism, this paper provides an accurate tree-based methodology for both missing data imputation and data fusion that is justified within the Statistical Learning Theory of Vapnik. It considers both an incremental variable imputation method to improve computational efficiency as well as boosted trees to gain in prediction accuracy with respect to other methods. As a result, the best approximation of the structural risk (also known as irreducible error) is reached, thus reducing at minimum the generalization (or prediction) error of imputation. Moreover, it is distribution free, it holds independently of the underlying probability law generating missing data values. Performance analysis is discussed considering simulation case studies and real world applications.     

Predictability of Plastic Parts Behaviour Made from Rapid Manufacturing

One of the most important issues to resolve in parts manufactured from rapid manufacturing (RM) technologies is to know their behavior working under real conditions. Total quality manufacturing (TQM) is only possible if mechanical properties are well known in the design stage depending on the processing parameters. This work is mainly focused on testing of several samples made with different selective laser sintering (SLS) parameters and technologies. This procedure is the starting point to establish a basis for designing for RM and the standardization of RM testing. The experiments and the analysis of variance (ANOVA) analyzed the effects of several factors on mechanical properties. The SLS technologies were 3DSystem and EOS. The results show which factor has a large effect on the variables and the interaction between them. The conclusions are very useful for developing rules for designing (designing for RM) and creating new standard rules (ISO, AISI, and DIN) for RM materials and parts testing. The ANOVA gives a better knowledge of the effects of these factors and eliminates unimportant parameters.     

Identification of a new gene mutated in Fraser syndrome and mouse myelencephalic blebs

Fraser syndrome is a recessive, multisystem disorder presenting with cryptophthalmos, syndactyly and renal defects and associated with loss-of-function mutations of the extracellular matrix protein FRAS1. Fras1 mutant mice have a blebbed phenotype characterized by intrauterine epithelial fragility generating serous and, later, hemorrhagic blisters. The myelencephalic blebs (my) strain has a similar phenotype. We mapped my to Frem2, a gene related to Fras1 and Frem1, and showed that a Frem2 gene-trap mutation was allelic to my. Expression of Frem2 in adult kidneys correlated with cyst formation in my homozygotes, indicating that the gene is required for maintaining the differentiated state of renal epithelia. Two individuals with Fraser syndrome were homozygous with respect to the same missense mutation of FREM2, confirming genetic heterogeneity. This is the only missense mutation reported in any blebbing mutant or individual with Fraser syndrome, suggesting that calcium binding in the CALXbeta-cadherin motif is important for normal functioning of FREM2.