On the bioeconomics of marine reserves when dispersal evolves

Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Natural Resource Modeling 28 (2015): 456-474, doi:10.1111/nrm.12075.Marine reserves are an increasingly used and potentially contentious tool in fisheries management. Depending upon the way that individuals move, no-take marine reserves can be necessary for maximizing equilibrium rent in some simple mathematical models. The implementation of no-take marine reserves often generates a redistribution of fishing effort in space. This redistribution of effort, in turn, produces sharp spatial gradients in mortality rates for the targeted stock. Using a two-patch model, we show that the existence of such gradients is a sufficient condition for the evolution of an evolutionarily stable conditional dispersal strategy. Thus, the dispersal strategy of the fish depends upon the harvesting strategy of the manager and vice versa. We find that an evolutionarily stable optimal harvesting strategy (ESOHS)—one which maximizes equilibrium rent given that fish disperse in an evolutionarily stable manner– - never includes a no-take marine reserve. This strategy is economically unstable in the short run because a manager can generate more rent by disregarding the possibility of dispersal evolution. Simulations of a stochastic evolutionary process suggest that such a short-run, myopic strategy performs poorly compared to the ESOHS over the long run, however, as it generates rent that is lower on average and higher in variability.This material is based upon work supported by funding from: The Woods Hole Oceanographic Institution's Investment in Science Fund to MGN; The Recruitment Program of Global Experts to YL; The University of Tennessee Center for Business and Economics Research to SL; and the U.S. National Science Foundation (NSF) through grants OCE-1031256, DEB-1257545, and DEB-1145017 to MGN, CNH-0707961 to GEH, DMS-1411476 to YL; and NSF Graduate Research Fellowships under Grant No. 1122374 to EAM and ES

Screening and Treatment Outcomes in Adults and Children With Type 1 Diabetes and Asymptomatic Celiac Disease: The CD-DIET Study.

OBJECTIVE: To describe celiac disease (CD) screening rates and glycemic outcomes of a gluten-free diet (GFD) in patients with type 1 diabetes who are asymptomatic for CD. RESEARCH DESIGN AND METHODS: Asymptomatic patients (8-45 years) were screened for CD. Biopsy-confirmed CD participants were randomized to GFD or gluten-containing diet (GCD) to assess changes in HbA RESULTS: Adults had higher CD-seropositivity rates than children (6.8% [95% CI 4.9-8.2%, CONCLUSIONS: CD is frequently observed in asymptomatic patients with type 1 diabetes, and clinical vigilance is warranted with initiation of a GFD

The Bacterial Fimbrial Tip Acts as a Mechanical Force Sensor

The subunits that constitute the bacterial adhesive complex located at the tip of the fimbria form a hook-chain that acts as a rapid force-sensitive anchor at high flow

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis.

Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Snapshot ARG Removal Rates across Wastewater Treatment Plants Are Not Representative Due to Diurnal Variations

To evaluate the threat of the environmental dissemination of antibiotic resistance associated with wastewater treatment plants (WWTPs), the removal efficiency of antibiotic resistance genes (ARGs) during wastewater treatment needs to be assessed. The sample collection strategy is one factor that is often overlooked in study design and most studies on ARGs in wastewater perform grab sampling. Here, we hypothesized that wastewater sampling (i.e., grab and composite sampling) influences the observed ARG concentrations and calculated removal rates across WWTPs. We compared the removal rates calculated based on the two different sampling methods for several genes, including some clinically relevant ARGs (blaNDM-1, blaOXA-1, MCR-1, MCR-5, MCR-10, and qnrA). We conducted summer and winter 24 h sampling campaigns where grab samples were collected every 2 h from the influent, secondary effluent, and final effluent. The snapshot removal rate of each target gene calculated based on the 12 grab samples fluctuated by 0.5–1.6 log in the winter and 0.9–2.7 log in the summer, indicating diurnal variation. Overall, for each target gene, the removal rates calculated based on 24 h composite samples were approximately equal to the median of the 12 snapshot removal rates. Our study confirms the importance of using composite samples to monitor ARGs in wastewater