Constraints and Negotiations to Student Recreational Sport Center Usage

Studies have shown that student recreational sports centers offer a variety of benefits to emerging adult students. Previous research has identified the presence of constraints to physical activity and student recreational sports center (SRSC) usage (Flood & Parker, 2014; Stankowski, Trauntvein, & Hall, 2017; Young, Ross, & Barcelona, 2003). However, little research has examined the negotiation strategies which students use to increase their physical activity levels through use of the SRSC. This study focused on the constraints and negotiation strategies which affected both users and infrequent users of the SRSC at a mid-size, public university in the northeastern United States. Results suggested that constraints and negotiation strategies differed significantly between user groups and that several constraints and negotiations predict frequency of visitation to the SRSC. Findings suggest the importance of management actions which help students to create social networks, improve their planning and prioritization, and develop self-efficacy with regard to physical activity at the SRSC

Winds of Change – Predicting Water-Based Recreationists\u27 Support and Opposition for Offshore Wind Energy Development in the Great Lakes

This study examined the factors influencing water-based recreationists\u27 perceptions of support and opposition towards off-shore wind energy development (OWD) on Lake Erie. Much of the proposed or future Lake Erie OWD infrastructure may either be within or adjacent to public lands, waters, and protected areas, raising concerns about the potential environmental and social impacts upon recreation stakeholders. The limited body of OWD research within the United States has suggested there are numerous factors that may influence overall perceptions of support and opposition such as political orientation and beliefs in climate change. Moreover, recent research has proposed that the perceived recreation impact of OWD may be the most important predictor of support and opposition. This study confirmed this premise and found the perceived recreation impact of OWD to be the strongest predictor of support. Results of a multiple linear regression suggested that political orientation (β = 0.135), beliefs in the anthropogenic causation of climate change (β = 0.207), beliefs in the occurrence of climate change (β = 0.213), and the perceived recreation impact of OWD among water-based recreationists (β = 0.439) were significant predictors of support for OWD on Lake Erie (R2 = 0.46). Study findings corroborated previous research which suggested that regional climate change beliefs and political attitudes may influence support for OWD. From a policy and management standpoint, study results highlight the importance of assessing and communicating recreation experience and use impacts when planning, developing, and managing OWD and related decisions in the United States

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

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Multiple mechanisms disrupt the let-7 microRNA family in neuroblastoma

Poor prognosis in neuroblastoma is associated with genetic amplification of MYCN. MYCN is itself a target of let-7, a tumour suppressor family of microRNAs implicated in numerous cancers. LIN28B, an inhibitor of let-7 biogenesis, is overexpressed in neuroblastoma and has been reported to regulate MYCN. Here we show, however, that LIN28B is dispensable in MYCN-amplified neuroblastoma cell lines, despite de-repression of let-7. We further demonstrate that MYCN messenger RNA levels in amplified disease are exceptionally high and sufficient to sponge let-7, which reconciles the dispensability of LIN28B. We found that genetic loss of let-7 is common in neuroblastoma, inversely associated with MYCN amplification, and independently associated with poor outcomes, providing a rationale for chromosomal loss patterns in neuroblastoma. We propose that let-7 disruption by LIN28B, MYCN sponging, or genetic loss is a unifying mechanism of neuroblastoma development with broad implications for cancer pathogenesis.United States. National Institutes of Health (R01GM107536)Alex's Lemonade Stand FoundationHoward Hughes Medical InstituteBoston Children's Hospital. Manton Center for Orphan Disease ResearchNational Institute of General Medical Sciences (U.S.) (T32GM007753

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies