Regional perturbation of gene transcription is associated with intrachromosomal rearrangements and gene fusion transcripts in high grade ovarian cancer.

Genomic rearrangements are a hallmark of cancer biology and progression, allowing cells to rapidly transform through alterations in regulatory structures, changes in expression patterns, reprogramming of signaling pathways, and creation of novel transcripts via gene fusion events. Though functional gene fusions encoding oncogenic proteins are the most dramatic outcomes of genomic rearrangements, we investigated the relationship between rearrangements evidenced by fusion transcripts and local expression changes in cancer using transcriptome data alone. 9,953 gene fusion predictions from 418 primary serious ovarian cancer tumors were analyzed, identifying depletions of gene fusion breakpoints within coding regions of fused genes as well as an N-terminal enrichment of breakpoints within fused genes. We identified 48 genes with significant fusion-associated upregulation and furthermore demonstrate that significant regional overexpression of intact genes in patient transcriptomes occurs within 1 megabase of 78 novel gene fusions that function as central markers of these regions. We reveal that cancer transcriptomes select for gene fusions that preserve protein and protein domain coding potential. The association of gene fusion transcripts with neighboring gene overexpression supports rearrangements as mechanism through which cancer cells remodel their transcriptomes and identifies a new way to utilize gene fusions as indicators of regional expression changes in diseased cells with only transcriptomic data

The "Unfriending" Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence

An increasing number of scholars are using longitudinal social network data to try to obtain estimates of peer or social influence effects. These data may provide additional statistical leverage, but they can introduce new inferential problems. In particular, while the confounding effects of homophily in friendship formation are widely appreciated, homophily in friendship retention may also confound causal estimates of social influence in longitudinal network data. We provide evidence for this claim in a Monte Carlo analysis of the statistical model used by Christakis, Fowler, and their colleagues in numerous articles estimating "contagion" effects in social networks. Our results indicate that homophily in friendship retention induces significant upward bias and decreased coverage levels in the Christakis and Fowler model if there is non-negligible friendship attrition over time.Comment: 26 pages, 4 figure

Coastal Tropical Convection in a Stochastic Modeling Framework

Recent research has suggested that the overall dependence of convection near coasts on large-scale atmospheric conditions is weaker than over the open ocean or inland areas. This is due to the fact that in coastal regions convection is often supported by meso-scale land-sea interactions and the topography of coastal areas. As these effects are not resolved and not included in standard cumulus parametrization schemes, coastal convection is among the most poorly simulated phenomena in global models. To outline a possible parametrization framework for coastal convection we develop an idealized modeling approach and test its ability to capture the main characteristics of coastal convection. The new approach first develops a decision algorithm, or trigger function, for the existence of coastal convection. The function is then applied in a stochastic cloud model to increase the occurrence probability of deep convection when land-sea interactions are diagnosed to be important. The results suggest that the combination of the trigger function with a stochastic model is able to capture the occurrence of deep convection in atmospheric conditions often found for coastal convection. When coastal effects are deemed to be present the spatial and temporal organization of clouds that has been documented form observations is well captured by the model. The presented modeling approach has therefore potential to improve the representation of clouds and convection in global numerical weather forecasting and climate models.Comment: Manuscript submitted for publication in Journal of Advances in Modeling Earth System

Popularity versus Similarity in Growing Networks

Popularity is attractive -- this is the formula underlying preferential attachment, a popular explanation for the emergence of scaling in growing networks. If new connections are made preferentially to more popular nodes, then the resulting distribution of the number of connections that nodes have follows power laws observed in many real networks. Preferential attachment has been directly validated for some real networks, including the Internet. Preferential attachment can also be a consequence of different underlying processes based on node fitness, ranking, optimization, random walks, or duplication. Here we show that popularity is just one dimension of attractiveness. Another dimension is similarity. We develop a framework where new connections, instead of preferring popular nodes, optimize certain trade-offs between popularity and similarity. The framework admits a geometric interpretation, in which popularity preference emerges from local optimization. As opposed to preferential attachment, the optimization framework accurately describes large-scale evolution of technological (Internet), social (web of trust), and biological (E.coli metabolic) networks, predicting the probability of new links in them with a remarkable precision. The developed framework can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon

Breast cancer risk among first-generation migrants in the Netherlands

We investigated breast cancer incidence in migrants in the Netherlands in 1988-1998. The standardised incidence ratio for breast cancer in Northwest-Netherlands was statistically significantly reduced for women born in Surinam (0.56), Turkey (0.29) and Morocco (0.22). The proportion of women with advanced stages (III and IV) did not differ significantly between migrants and women born in the Netherlands

Genetic parameters and selection strategies for soybean genotypes resistant to the stink bug-complex

Soybean genotypes resistant to stink bugs are derived from complex breeding processes obtained through indirect selection. The aim of the present work was to estimate genetic parameters for guiding selection strategies towards resistant genotypes, based on those traits associated with responses to pod-attacking stink bugs, such as the grain filling period (GFP), leaf retention (LR), percentage index of pod damage (PIPD) and percentage of spotted seeds (PSS). We assessed the parental lines IAC-100 (resistant) and FT-Estrela (susceptible), the progenies F2 and F 4 , 30 progenies F 2:3 , 30 progenies BC 1 F 2:3 and 30 progenies BC 2 F 2:3 , besides the cultivars BRS Celeste and MGBR-46 (Conquista). Three field experiments, using randomized complete block design with three replications, were installed in Goiânia-GO, in the 2002/03 season. Each experiment consisted of 36 treatments (6 common and 30 regular). Heritability estimates were: 74.6 and 36.1 (GFP); 51.9 and 19.9 (LR); 49.6 and 49.6 (PIPD) and 55.8 and 20.3 (PSS), in both the broad and narrow senses, respectively. Based on these results, we concluded that the best strategy for obtaining stink bug-resistant genotypes consists of selecting the PIPD trait in early generations (F 3 or F 4 ), followed by selection for the GFP, LR and PSS traits in generations with higher endogamy levels