An intervention study to prevent relapse in patients with schizophrenia

Purpose: To determine whether the use of relapse prevention plans (RPPs) in nursing practice is an effective intervention in reducing relapse rates among patients with schizophrenia. Design and Methods: Experimental design. Patients with schizophrenia (or a related psychotic disorder) and nurses from three mental health organizations were randomly assigned to either an experimental (RPP) or control condition (care as usual). The primary outcome measure was the psychotic relapses in the research groups. Results: The relapse rates in the experimental and control groups after 1-year follow-up were 12.5% and 26.2%, respectively (p=.12, ns). The relative risk of a relapse in the experimental versus the control group was 0.48(ns). Conclusions: In this study no statistically significant effects of the intervention were found. Effectiveness research in this area should be continued with larger sample sizes and longer follow-up periods

Mental Health of Parents and Life Satisfaction of Children: A Within-Family Analysis of Intergenerational Transmission of Well-Being

This paper addresses the extent to which there is an intergenerational transmission of mental health and subjective well-being within families. Specifically it asks whether parents’ own mental distress influences their child’s life satisfaction, and vice versa. Whilst the evidence on daily contagion of stress and strain between members of the same family is substantial, the evidence on the transmission between parental distress and children’s well-being over a longer period of time is sparse. We tested this idea by examining the within-family transmission of mental distress from parent to child’s life satisfaction, and vice versa, using rich longitudinal data on 1,175 British youths. Results show that parental distress at year t-1 is an important determinant of child’s life satisfaction in the current year. This is true for boys and girls, although boys do not appear to be affected by maternal distress levels. The results also indicated that the child’s own life satisfaction is related with their father’s distress levels in the following year, regardless of the gender of the child. Finally, we examined whether the underlying transmission correlation is due to shared social environment, empathic reactions, or transmission via parent-child interaction

The Coupled Model Intercomparison Project (CMIP)

The Coupled Model Intercomparison Project (CMIP) was established to study and intercompare climate simulations made with coupled ocean-atmosphere-cryosphere-land GCMs. There are two main phases (CMIP1 and CMIP2), which study, respectively, 1) the ability of models to simulate current climate, and 2) model simulations of climate change due to an idealized change in forcing (a 1% per year CO2 increase). Results from a number of CMIP projects were reported at the first CMIP Workshop held in Melbourne, Australia, in October 1998. Some recent advances in global coupled modeling related to CMIP were also reported. Presentations were based on preliminary unpublished results. Key outcomes from the workshop were that 1) many observed aspects of climate variability are simulated in global coupled models including the North Atlantic oscillation and its linkages to North Atlantic SSTs, El Niño-like events, and monsoon interannual variability; 2) the amplitude of both high- and low-frequency global mean surface temperature variability in many global coupled models is less than that observed, with the former due in part to simulated ENSO in the models being generally weaker than observed, and the latter likely to be at least partially due to the uncertainty in the estimates of past radiative forcing; 3) an El Niño-like pattern in the mean SST response with greater surface warming in the eastern equatorial Pacific than the western equatorial Pacific is found by a number of models in global warming climate change experiments, but other models have a more spatially uniform or even a La Niña-like, response; 4) flux adjustment, by definition, improves the simulation of mean present-day climate over oceans, does not guarantee a drift-free climate, but can produce a stable base state in some models to enable very long term (1000 yr and longer) integrations-in these models it does not appear to have a major effect on model processes or model responses to increasing CO2; and 5) recent multicentury integrations show that a stable surface climate can be attained without flux adjustment (though still with some systematic simulation errors)

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

pubmed2ensembl: A Resource for Mining the Biological Literature on Genes

The last two decades have witnessed a dramatic acceleration in the production of genomic sequence information and publication of biomedical articles. Despite the fact that genome sequence data and publications are two of the most heavily relied-upon sources of information for many biologists, very little effort has been made to systematically integrate data from genomic sequences directly with the biological literature. For a limited number of model organisms dedicated teams manually curate publications about genes; however for species with no such dedicated staff many thousands of articles are never mapped to genes or genomic regions.To overcome the lack of integration between genomic data and biological literature, we have developed pubmed2ensembl (http://www.pubmed2ensembl.org), an extension to the BioMart system that links over 2,000,000 articles in PubMed to nearly 150,000 genes in Ensembl from 50 species. We use several sources of curated (e.g., Entrez Gene) and automatically generated (e.g., gene names extracted through text-mining on MEDLINE records) sources of gene-publication links, allowing users to filter and combine different data sources to suit their individual needs for information extraction and biological discovery. In addition to extending the Ensembl BioMart database to include published information on genes, we also implemented a scripting language for automated BioMart construction and a novel BioMart interface that allows text-based queries to be performed against PubMed and PubMed Central documents in conjunction with constraints on genomic features. Finally, we illustrate the potential of pubmed2ensembl through typical use cases that involve integrated queries across the biomedical literature and genomic data.By allowing biologists to find the relevant literature on specific genomic regions or sets of functionally related genes more easily, pubmed2ensembl offers a much-needed genome informatics inspired solution to accessing the ever-increasing biomedical literature

Non-Linear Interactions between Consumers and Flow Determine the Probability of Plant Community Dominance on Maine Rocky Shores

Although consumers can strongly influence community recovery from disturbance, few studies have explored the effects of consumer identity and density and how they may vary across abiotic gradients. On rocky shores in Maine, recent experiments suggest that recovery of plant- or animal- dominated community states is governed by rates of water movement and consumer pressure. To further elucidate the mechanisms of consumer control, we examined the species-specific and density-dependent effects of rocky shore consumers (crabs and snails) on community recovery under both high (mussel dominated) and low flow (plant dominated) conditions. By partitioning the direct impacts of predators (crabs) and grazers (snails) on community recovery across a flow gradient, we found that grazers, but not predators, are likely the primary agent of consumer control and that their impact is highly non-linear. Manipulating snail densities revealed that herbivorous and bull-dozing snails (Littorina littorea) alone can control recovery of high and low flow communities. After ∼1.5 years of recovery, snail density explained a significant amount of the variation in macroalgal coverage at low flow sites and also mussel recovery at high flow sites. These density-dependent grazer effects were were both non-linear and flow-dependent, with low abundance thresholds needed to suppress plant community recovery, and much higher levels needed to control mussel bed development. Our study suggests that consumer density and identity are key in regulating both plant and animal community recovery and that physical conditions can determine the functional forms of these consumer effects