Creating spatially-explicit lawn maps without classifying remotely-sensed imagery: The case of suburban Boston, Massachusetts, USA

Residential lawns are a dominant and growing feature of US residential landscapes, and the resource-intensive management of this landscape feature presents major potential risks to both humans and the environment. In recent years, scientists and policymakers have been increasingly calling for large-extent measures of lawns and other similar landscape features. Unfortunately, the production of such datasets using traditional, remotely sensed measurement approaches can be prohibitively expensive and time consuming. This study uses two statistical prediction methods to extrapolate the quantity and spatial distribution of residential lawns from a sample of mapped lawns in a large study area in suburban Boston, Massachusetts. The goal is to find an inexpensive, broad-coverage dataset that will provide useable estimates of landscape features in places where we do not have direct measurements of those landscape features. The first estimation method uses OLS regression in conjunction with the sample of mapped lawns and freely available US Census data representing theoretically informed social driver variables. The second, simpler, and less computationally intensive estimation method allocates the mean of the sample of mapped lawns uniformly across the study area. Both estimation methods are performed 1000 times in a Monte Carlo framework where the sample is drawn randomly each realization, to assess the sensitivity of the prediction results to the selection of CBGs in each simple random sample. The outputs of each estimation method are then compared to a reference map where the quantity and spatial allocation of lawns is known for each spatial unit of analysis. Results indicate that the OLS prediction method specified with the independent social driver variables performs better than a uniform prediction method when both are compared to the full-study area reference map

Every Picture Tells a Story: The 2010 Round of Congressional Redistricting in New England

The United States Constitution requires that the number of representatives in Congress be reapportioned among the states based on a decennial census, and the U.S. Supreme Court ruled half a century ago that congressional districts within each state must be, as nearly as practicable, equal in population. However, the actual drawing of district lines for our national lower house and the methods employed for doing so are largely left to the individual states. Redistricting thus presents a fertile field for the comparative examination of state politics and political institutions

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.We thank the DKFZ Genomics and Proteomics Core Facility and the OICR Genome Technologies Platform for provision of sequencing services. Financial support was provided by the consortium projects READNA under grant agreement FP7 Health-F4-2008-201418, ESGI under grant agreement 262055, GEUVADIS under grant agreement 261123 of the European Commission Framework Programme 7, ICGC-CLL through the Spanish Ministry of Science and Innovation (MICINN), the Instituto de Salud Carlos III (ISCIII) and the Generalitat de Catalunya. Additional financial support was provided by the PedBrain Tumor Project contributing to the International Cancer Genome Consortium, funded by German Cancer Aid (109252) and by the German Federal Ministry of Education and Research (BMBF, grants #01KU1201A, MedSys #0315416C and NGFNplus #01GS0883; the Ontario Institute for Cancer Research to PCB and JDM through funding provided by the Government of Ontario, Ministry of Research and Innovation; Genome Canada; the Canada Foundation for Innovation and Prostate Cancer Canada with funding from the Movember Foundation (PCB). PCB was also supported by a Terry Fox Research Institute New Investigator Award, a CIHR New Investigator Award and a Genome Canada Large-Scale Applied Project Contract. The Synergie Lyon Cancer platform has received support from the French National Institute of Cancer (INCa) and from the ABS4NGS ANR project (ANR-11-BINF-0001-06). The ICGC RIKEN study was supported partially by RIKEN President’s Fund 2011, and the supercomputing resource for the RIKEN study was provided by the Human Genome Center, University of Tokyo. MDE, LB, AGL and CLA were supported by Cancer Research UK, the University of Cambridge and Hutchison-Whampoa Limited. SD is supported by the Torres Quevedo subprogram (MI CINN) under grant agreement PTQ-12-05391. EH is supported by the Research Council of Norway under grant agreements 221580 and 218241 and by the Norwegian Cancer Society under grant agreement 71220-PR-2006-0433. Very special thanks go to Jennifer Jennings for administrating the activity of the ICGC Verification Working Group and Anna Borrell for administrative support.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms1000

Polymorphisms near TBX5 and GDF7 are associated with increased risk for Barrett's esophagus.

BACKGROUND & AIMS: Barrett's esophagus (BE) increases the risk of esophageal adenocarcinoma (EAC). We found the risk to be BE has been associated with single nucleotide polymorphisms (SNPs) on chromosome 6p21 (within the HLA region) and on 16q23, where the closest protein-coding gene is FOXF1. Subsequently, the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON) identified risk loci for BE and esophageal adenocarcinoma near CRTC1 and BARX1, and within 100 kb of FOXP1. We aimed to identify further SNPs that increased BE risk and to validate previously reported associations. METHODS: We performed a genome-wide association study (GWAS) to identify variants associated with BE and further analyzed promising variants identified by BEACON by genotyping 10,158 patients with BE and 21,062 controls. RESULTS: We identified 2 SNPs not previously associated with BE: rs3072 (2p24.1; odds ratio [OR] = 1.14; 95% CI: 1.09-1.18; P = 1.8 × 10(-11)) and rs2701108 (12q24.21; OR = 0.90; 95% CI: 0.86-0.93; P = 7.5 × 10(-9)). The closest protein-coding genes were respectively GDF7 (rs3072), which encodes a ligand in the bone morphogenetic protein pathway, and TBX5 (rs2701108), which encodes a transcription factor that regulates esophageal and cardiac development. Our data also supported in BE cases 3 risk SNPs identified by BEACON (rs2687201, rs11789015, and rs10423674). Meta-analysis of all data identified another SNP associated with BE and esophageal adenocarcinoma: rs3784262, within ALDH1A2 (OR = 0.90; 95% CI: 0.87-0.93; P = 3.72 × 10(-9)). CONCLUSIONS: We identified 2 loci associated with risk of BE and provided data to support a further locus. The genes we found to be associated with risk for BE encode transcription factors involved in thoracic, diaphragmatic, and esophageal development or proteins involved in the inflammatory response

Long-term effects of medical management on growth and weight in individuals with urea cycle disorders

Low protein diet and sodium or glycerol phenylbutyrate, two pillars of recommended long-term therapy of individuals with urea cycle disorders (UCDs), involve the risk of iatrogenic growth failure. Limited evidence-based studies hamper our knowledge on the long-term effects of the proposed medical management in individuals with UCDs. We studied the impact of medical management on growth and weight development in 307 individuals longitudinally followed by the Urea Cycle Disorders Consortium (UCDC) and the European registry and network for Intoxication type Metabolic Diseases (E-IMD). Intrauterine growth of all investigated UCDs and postnatal linear growth of asymptomatic individuals remained unaffected. Symptomatic individuals were at risk of progressive growth retardation independent from the underlying disease and the degree of natural protein restriction. Growth impairment was determined by disease severity and associated with reduced or borderline plasma branched-chain amino acid (BCAA) concentrations. Liver transplantation appeared to have a beneficial effect on growth. Weight development remained unaffected both in asymptomatic and symptomatic individuals. Progressive growth impairment depends on disease severity and plasma BCAA concentrations, but cannot be predicted by the amount of natural protein intake alone. Future clinical trials are necessary to evaluate whether supplementation with BCAAs might improve growth in UCDs

A comparison of Landsat ETM+ and high-resolution aerial orthophotos to map urban/suburban forest cover in Massachusetts, USA

This article examines the extent to which L(ow)-spatial resolution Landsat Enhanced Thematic Mapper Plus (ETM+) imagery can be used to map urban/suburban forest cover in comparison with H(igh)-spatial resolution (less than 1 m) digital aerial orthophotos from the same study area and time period. This research has practical implications for resource managers, government agencies and forestry researchers interested in mapping large-area urban/suburban forests because Landsat imagery is more accessible, has an extensive historical archive, has broader spatial and temporal coverage and is more cost efficient than H-resolution aerial orthophotos. Classification tree results suggest that Landsat ETM+ imagery is adequate for mapping larger, contiguous patches of forest (i.e. small forest patches greater than 2 acres) in urban/suburban settings, but its spatial resolution is too coarse to accurately map spatially complex residential areas in urban/suburban landscapes. © 2012 Taylor & Francis

Understanding the social determinants of lawn landscapes: A fine-resolution spatial statistical analysis in suburban Boston, Massachusetts, USA

This study examines the influence of social processes on the spatial distribution of residential lawns, one of the most prominent anthropogenic environmental challenges in US urban/suburban areas today. Specifically, we examine how three theoretically informed social drivers of urban vegetation patterns-population density, social stratification, and lifestyle behavior-explain two measures of residential lawns at the US Census block group (CBG) scale in suburban Boston, MA, USA. Using fine-spatial resolution (0.5. m) remotely sensed data, we map land cover from which we generate two lawn measures: (1) percent lawn cover, which is the overall percentage of land in a CBG containing lawn, and (2) percent lawn realized stewardship, which is the percentage of non-developed land in a CBG containing lawn. We use spatial regression to find that population density and lifestyle behavior, proxied by percentage of single-family detached homes, average household size, and percentage of protected land in the CBG-are the key social processes driving the spatial distribution of both lawn measures in our study area. Results also show that spatial regression provides theoretical insight into additional, unspecified processes influencing the spatial distribution of lawns, net of the effects of the independent variables. These findings contribute to the existing understanding of the social processes influencing the residential lawn landscape, and are therefore useful for scientists, decision-makers, and stakeholders who are interested in moderating the potential social and ecological impacts of this landscape. © 2012 Elsevier B.V

A 35-bp Conserved Region Is Crucial for <i>Insl3</i> Promoter Activity in Mouse MA-10 Leydig Cells

The peptide hormone insulin-like 3 (INSL3) is produced almost exclusively by Leydig cells of the male gonad. INSL3 has several functions such as fetal testis descent and bone metabolism in adults. Insl3 gene expression in Leydig cells is not hormonally regulated but rather is constitutively expressed. The regulatory region of the Insl3 gene has been described in various species; moreover, functional studies have revealed that the Insl3 promoter is regulated by various transcription factors that include the nuclear receptors AR, NUR77, COUP-TFII, LRH1, and SF1, as well as the Krüppel-like factor KLF6. However, these transcription factors are also found in several tissues that do not express Insl3, indicating that other, yet unidentified factors, must be involved to drive Insl3 expression specifically in Leydig cells. Through a fine functional promoter analysis, we have identified a 35-bp region that is responsible for conferring 70% of the activity of the mouse Insl3 promoter in Leydig cells. All tri- and dinucleotide mutations introduced dramatically reduced Insl3 promoter activity, indicating that the entire 35-bp sequence is required. Nuclear proteins from MA-10 Leydig cells bound specifically to the 35-bp region. The 35-bp sequence contains GC- and GA-rich motifs as well as potential binding elements for members of the CREB, C/EBP, AP1, AP2, and NF-κB families. The Insl3 promoter was indeed activated 2-fold by NF-κB p50 but not by other transcription factors tested. These results help to further define the regulation of Insl3 gene transcription in Leydig cells

Design and Interpretation of Intensity Analysis Illustrated by Land Change in Central Kalimantan, Indonesia

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