Engaging Communities in Marine Protected Areas: Concepts and Strategies from Current Practice

This study provides information and insights about the community engagement strategies in current practice by Marine Protected Area (MPA) managers and community members throughout the United States. Until now, no synthesis of these efforts has been completed. Recognizing this gap, the National Marine Protected Area Center commissioned an external report on community engagement to be undertaken by Master’s students at the University of Michigan. Through a literature review, interviews with MPA managers and community members, and an online survey, this report addresses the identified need. Common challenges to community engagement identified by MPA managers and community members are communication, involvement, representation, resource limitations, preconceptions, and staff expertise. Principles of community engagement are: to be proactive; to be clear about purposes and terms; understand, validate, and speak to the community’s concerns; start early with clear expectations; be responsive; be inclusive; build on common needs and goals; and recognize that it all begins with relationships. MPA managers described six objectives for community engagement: to increase awareness and raise visibility of the MPA; to enhance understanding and support for the MPA’s purpose and resources; to encourage MPA-beneficial stewardship behaviors within the communities; to enable others to help advance MPA objectives; and to instill community ownership and pride in the MPA. Moving forward, we encourage managers to draw inspiration from the community, celebrate small victories, and share ideas and inspiration.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/106570/1/EngagingCommunitiesOpus.pd

The Epstein-Barr virus encoded LMP1 oncoprotein modulates cell adhesion via regulation of activin A/TGFβ and β1 integrin signalling

Approximately 20% of global cancer incidence is causally linked to an infectious agent. EpsteinBarr virus (EBV) accounts for around 1% of all virus-associated cancers and is associated with nasopharyngeal carcinoma (NPC). Latent membrane protein 1 (LMP1), the major oncoprotein encoded by EBV, behaves as a constitutively active tumour necrosis factor (TNF) receptor activating a variety of signalling pathways, including the three classic MAPKs (ERK-MAPK, p38 MAPK and JNK/SAPK). The present study identifes novel signalling properties for this integral membrane protein via the induction and secretion of activin A and TGFβ1, which are both required for LMP1’s ability to induce the expression of the extracellular matrix protein, fbronectin. However, it is evident that LMP1 is unable to activate the classic Smad-dependent TGFβ signalling pathway, but rather elicits its efects through the non-Smad arm of TGFβ signalling. In addition, there is a requirement for JNK/SAPK signalling in LMP1-mediated fbronectin induction. LMP1 also induces the expression and activation of the major fbronectin receptor, α5β1 integrin, an efect that is accompanied by increased focal adhesion formation and turnover. Taken together, these fndings support the putative role for LMP1 in the pathogenesis of NPC by contributing to the metastatic potential of epithelial cells

Comparing composite likelihood methods based on pairs for spatial Gaussian random fields

In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when we deal with a Gaussian model. However maximum likelihood becomes impractical when the number of observations is very large. In this work we review some solutions and we contrast them in terms of loss of statistical efficiency and computational burden. Specifically we focus on three types of weighted composite likelihood functions based on pairs and we compare them with the method of covariance tapering. Asymptotic properties of the three estimation methods are derived. We illustrate the effectiveness of the methods through theoretical examples, simulation experiments and by analyzing a data set on yearly total precipitation anomalies at weather stations in the United States.In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when we deal with a Gaussian model. However maximum likelihood becomes impractical when the number of observations is very large. In this work we review some solutions and we contrast them in terms of loss of statistical efficiency and computational burden. Specifically we focus on three types of weighted composite likelihood functions based on pairs and we compare them with the method of covariance tapering. Asymptotic properties of the three estimation methods are derived. We illustrate the effectiveness of the methods through theoretical examples, simulation experiments and by analyzing a data set on yearly total precipitation anomalies at weather stations in the United States

Overexpression of Arabidopsis FLOWERING LOCUS T (FT) gene improves floral development in cassava (Manihot esculenta, Crantz)

Cassava is a tropical storage-root crop that serves as a worldwide source of staple food for over 800 million people. Flowering is one of the most important breeding challenges in cassava because in most lines flowering is late and non-synchronized, and flower production is sparse. The FLOWERING LOCUS T (FT) gene is pivotal for floral induction in all examined angiosperms. The objective of the current work was to determine the potential roles of the FT signaling system in cassava. The Arabidopsis thaliana FT gene (atFT) was transformed into the cassava cultivar 60444 through Agrobacterium-mediated transformation and was found to be overexpressed constitutively. FT overexpression hastened flower initiation and associated fork-type branching, indicating that cassava has the necessary signaling factors to interact with and respond to the atFT gene product. In addition, overexpression stimulated lateral branching, increased the prolificacy of flower production and extended the longevity of flower development. While FT homologs in some plant species stimulate development of vegetative storage organs, atFT inhibited storage-root development and decreased root harvest index in cassava. These findings collectively contribute to our understanding of flower development in cassava and have the potential for applications in breeding

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

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

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

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