62 research outputs found
BIOFRAG: A new database for analysing BIOdiversity responses to forest FRAGmentation
Habitat fragmentation studies are producing inconsistent and complex results across which it is nearly impossible to synthesise. Consistent analytical techniques can be applied to primary datasets, if stored in a flexible database that allows simple data retrieval for subsequent analyses. Method: We developed a relational database linking data collected in the field to taxonomic nomenclature, spatial and temporal plot attributes and further environmental variables (e.g. information on biogeographic region. Typical field assessments include measures of biological variables (e.g. presence, abundance, ground cover) of one species or a set of species linked to a set of plots in fragments of a forested landscape. Conclusion: The database currently holds records of 5792 unique species sampled in 52 landscapes in six of eight biogeographic regions: mammals 173, birds 1101, herpetofauna 284, insects 2317, other arthropods: 48, plants 1804, snails 65. Most species are found in one or two landscapes, but some are found in four. Using the huge amount of primary data on biodiversity response to fragmentation becomes increasingly important as anthropogenic pressures from high population growth and land demands are increasing. This database can be queried to extract data for subsequent analyses of the biological response to forest fragmentation with new metrics that can integrate across the components of fragmented landscapes. Meta-analyses of findings based on consistent methods and metrics will be able to generalise over studies allowing inter-comparisons for unified answers. The database can thus help researchers in providing findings for analyses of trade-offs between land use benefits and impacts on biodiversity and to track performance of management for biodiversity conservation in human-modified landscapes.Fil: Pfeifer, Marion. Imperial College London; Reino UnidoFil: Lefebvre, Veronique. Imperial College London; Reino UnidoFil: Gardner, Toby A.. Stockholm Environment Institute; SueciaFil: Arroyo RodrĂguez, VĂctor. Universidad Nacional AutĂłnoma de MĂ©xico; MĂ©xicoFil: Baeten, Lander. University of Ghent; BĂ©lgicaFil: Banks Leite, Cristina. Imperial College London; Reino UnidoFil: Barlow, Jos. Lancaster University; Reino UnidoFil: Betts, Matthew G.. State University of Oregon; Estados UnidosFil: Brunet, Joerg. Swedish University of Agricultural Sciences; SueciaFil: Cerezo BlandĂłn, Alexis Mauricio. Universidad de Buenos Aires. Facultad de AgronomĂa. Departamento de MĂ©todos Cuantitativos y Sistemas de InformaciĂłn; ArgentinaFil: Cisneros, Laura M.. University of Connecticut; Estados UnidosFil: Collard, Stuart. Nature Conservation Society of South Australia; AustraliaFil: DÂŽCruze, Neil. The World Society for the Protection of Animals; Reino UnidoFil: Da Silva Motta, Catarina. MinistĂ©rio da CiĂȘncia, Tecnologia, InovaçÔes. Instituto Nacional de Pesquisas da AmazĂŽnia; BrasilFil: Duguay, Stephanie. Carleton University; CanadĂĄFil: Eggermont, Hilde. University of Ghent; BĂ©lgicaFil: Eigenbrod, FĂ©lix. University of Southampton; Reino UnidoFil: Hadley, Adam S.. State University of Oregon; Estados UnidosFil: Hanson, Thor R.. No especifĂca;Fil: Hawes, Joseph E.. University of East Anglia; Reino UnidoFil: Heartsill Scalley, Tamara. United State Department of Agriculture. Forestry Service; Puerto RicoFil: Klingbeil, Brian T.. University of Connecticut; Estados UnidosFil: Kolb, Annette. Universitat Bremen; AlemaniaFil: Kormann, Urs. UniversitĂ€t Göttingen; AlemaniaFil: Kumar, Sunil. State University of Colorado - Fort Collins; Estados UnidosFil: Lachat, Thibault. Swiss Federal Institute for Forest; SuizaFil: Lakeman Fraser, Poppy. Imperial College London; Reino UnidoFil: Lantschner, MarĂa Victoria. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - BahĂa Blanca; Argentina. Instituto Nacional de TecnologĂa Agropecuaria. Centro Regional Patagonia Norte. EstaciĂłn Experimental Agropecuaria San Carlos de Bariloche; ArgentinaFil: Laurance, William F.. James Cook University; AustraliaFil: Leal, Inara R.. Universidade Federal de Pernambuco; BrasilFil: Lens, Luc. University of Ghent; BĂ©lgicaFil: Marsh, Charles J.. University of Leeds; Reino UnidoFil: Medina Rangel, Guido F.. Universidad Nacional de Colombia; ColombiaFil: Melles, Stephanie. University of Toronto; CanadĂĄFil: Mezger, Dirk. Field Museum of Natural History; Estados UnidosFil: Oldekop, Johan A.. University of Sheffield; Reino UnidoFil: Overal , Williams L.. Museu Paraense EmĂlio Goeldi. Departamento de Entomologia; BrasilFil: Owen, Charlotte. Imperial College London; Reino UnidoFil: Peres, Carlos A.. University of East Anglia; Reino UnidoFil: Phalan, Ben. University of Southampton; Reino UnidoFil: Pidgeon, Anna Michle. University of Wisconsin; Estados UnidosFil: Pilia, Oriana. Imperial College London; Reino UnidoFil: Possingham, Hugh P.. Imperial College London; Reino Unido. The University Of Queensland; AustraliaFil: Possingham, Max L.. No especifĂca;Fil: Raheem, Dinarzarde C.. Royal Belgian Institute of Natural Sciences; BĂ©lgica. Natural History Museum; Reino UnidoFil: Ribeiro, Danilo B.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Ribeiro Neto, Jose D.. Universidade Federal de Pernambuco; BrasilFil: Robinson, Douglas W.. State University of Oregon; Estados UnidosFil: Robinson, Richard. Manjimup Research Centre; AustraliaFil: Rytwinski, Trina. Carleton University; CanadĂĄFil: Scherber, Christoph. UniversitĂ€t Göttingen; AlemaniaFil: Slade, Eleanor M.. University of Oxford; Reino UnidoFil: Somarriba, Eduardo. Centro AgronĂłmico Tropical de InvestigaciĂłn y Enseñanza; Costa RicaFil: Stouffer, Philip C.. State University of Louisiana; Estados UnidosFil: Struebig, Matthew J.. University of Kent; Reino UnidoFil: Tylianakis, Jason M.. University College London; Estados Unidos. Imperial College London; Reino UnidoFil: Teja, Tscharntke. UniversitĂ€t Göttingen; AlemaniaFil: Tyre, Andrew J.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Urbina Cardona, Jose N.. Pontificia Universidad Javeriana; ColombiaFil: Vasconcelos, Heraldo L.. Universidade Federal de Uberlandia; BrasilFil: Wearn, Oliver. Imperial College London; Reino Unido. The Zoological Society of London; Reino UnidoFil: Wells, Konstans. University of Adelaide; AustraliaFil: Willig, Michael R.. University of Connecticut; Estados UnidosFil: Wood, Eric. University of Wisconsin; Estados UnidosFil: Young, Richard P.. Durrell Wildlife Conservation Trust; Reino UnidoFil: Bradley, Andrew V.. Imperial College London; Reino UnidoFil: Ewers, Robert M.. Imperial College London; Reino Unid
BIOFRAG - a new database for analyzing BIOdiversity responses to forest FRAGmentation
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BIOFRAG â a new database for analyzing BIOdiversity responses to forest FRAGmentation
Habitat fragmentation studies have produced complex results that are challenging
to synthesize. Inconsistencies among studies may result from variation in
the choice of landscape metrics and response variables, which is often compounded
by a lack of key statistical or methodological information. Collating
primary datasets on biodiversity responses to fragmentation in a consistent and
flexible database permits simple data retrieval for subsequent analyses. We present
a relational database that links such field data to taxonomic nomenclature,
spatial and temporal plot attributes, and environmental characteristics. Field
assessments include measurements of the response(s) (e.g., presence, abundance,
ground cover) of one or more species linked to plots in fragments
within a partially forested landscape. The database currently holds 9830 unique
species recorded in plots of 58 unique landscapes in six of eight realms: mammals
315, birds 1286, herptiles 460, insects 4521, spiders 204, other arthropods
85, gastropods 70, annelids 8, platyhelminthes 4, Onychophora 2, vascular
plants 2112, nonvascular plants and lichens 320, and fungi 449. Three landscapes
were sampled as long-term time series (>10 years). Seven hundred and
eleven species are found in two or more landscapes. Consolidating the substantial
amount of primary data available on biodiversity responses to fragmentation
in the context of land-use change and natural disturbances is an essential
part of understanding the effects of increasing anthropogenic pressures on land.
The consistent format of this database facilitates testing of generalizations concerning
biologic responses to fragmentation across diverse systems and taxa. It
also allows the re-examination of existing datasets with alternative landscape
metrics and robust statistical methods, for example, helping to address pseudo-replication
problems. The database can thus help researchers in producing
broad syntheses of the effects of land use. The database is dynamic and inclusive,
and contributions from individual and large-scale data-collection efforts
are welcome.Keywords: Species turnover,
Data sharing,
Database,
Global change,
Landscape metrics,
Edge effects,
Forest fragmentation,
Matrix contrast,
Bioinformatic
Transcriptomic profile of cystic fibrosis patients identifies type I interferon response and ribosomal stalk proteins as potential modifiers of disease severity.
Cystic Fibrosis (CF) is the most common monogenic disease among people of Western European descent and caused by mutations in the CFTR gene. However, the disease severity is immensely variable even among patients with similar CFTR mutations due to the possible effect of 'modifier genes'. To identify genetic modifiers, we applied RNA-seq based transcriptomic analyses in CF patients with a mild and severe lung phenotype. Global gene expression and enrichment analyses revealed that genes of the type I interferon response and ribosomal stalk proteins are potential modifiers of CF related lung dysfunction. The results provide a new set of CF modifier genes with possible implications as new therapeutic targets for the treatment of CF
Published online:
Abstract We describe our development of Cobot, a novel software agent who lives in LambdaMOO, a popular virtual world frequented by hundreds of users. Cobotâs goal was to become an actual part of that community. Here, we present a detailed discussion of the functionality that made him one of the objects most frequently interacted with in LambdaMOO, human or artificial. Cobotâs fundamental power is that he has the ability to collect social statistics summarizing the quantity and quality of interpersonal interactions. Initially, Cobot acted as little more than a reporter of this information; however, as he collected more and more data, he was able to use these statistics as models that allowed him to modify his own behavior. In particular, C. L. Isbell, Jr. (B
Correction: mRNA-Mediated Gene Supplementation of Toll-Like Receptors as Treatment Strategy for Asthma In Vivo.
[This corrects the article DOI: 10.1371/journal.pone.0154001.]
Functional Toll-Like Receptor (TLR)2 polymorphisms in the susceptibility to inflammatory bowel disease.
BACKGROUND:The recent genome-wide association studies (GWAS) in inflammatory bowel disease (IBD) suggest significant genetic overlap with complex mycobacterial diseases like tuberculosis or leprosy. TLR variants have previously been linked to susceptibility for mycobacterial diseases. Here we investigated the contribution to IBD risk of two TLR2 polymorphisms, the low-prevalence variant Arg753Gln and the GTn microsatellite repeat polymorphism in intron 2. We studied association with disease, possible correlations with phenotype and gene-gene interactions. METHODOLOGY/PRINCIPAL FINDINGS:We conducted a large study in 843 patients with Crohn's disease, 426 patients with ulcerative colitis and 805 healthy, unrelated controls, all of European origin. Overall, the frequency for carriers of shorter GTn repeats in intron 2 of the TLR2 gene, which have previously been associated with low TLR2 expression and high IL-10 production, was slightly elevated in Crohn's disease and ulcerative colitis compared to healthy controls (16.0% resp. 16.7% vs. 12.8%). The highest frequency of short GTn carriers was noted among IBD patients on anti TNF-alpha therapy. However, none of these differences was significant in the multivariate analysis. The Arg753Gln polymorphism showed no association with any clinical subtype of IBD, including extensive colitis, for which such an association was previously described. We found no association with specific phenotypic disease subgroups. Also, epistasis analysis revealed no significant interactions between the two TLR2 variants and confirmed IBD susceptibility genes. CONCLUSIONS:The two functional relevant polymorphisms in TLR2, the GTn microsatellite repeat polymorphism in intron 2 and the Arg753Gln variant do not seem to play a role in the susceptibility to Crohn's disease or ulcerative colitis
Clinical characteristics of the mild CF and severe CF samples.
<p>Clinical characteristics of the mild CF and severe CF samples.</p
RNA-seq analyses of Mild CF and severe CF patients.
<p><b>A)</b> Heat-map of differentially expressed genes. Each column represents a separate patient, and each horizontal line represents a separate gene. Dendrogram of clustered samples and genes, in which mild CF and severe CF samples cluster with respect to their expression similarity. Expression profiles are measured by counts per million reads (CPM- model). <b>B)</b> Volcano plot of RNA-seq data, in which the -Log<sub>10</sub> of the false discovery rate is plotted against Log<sub>2</sub> fold change.</p
Primer details and PCR cycling conditions for the qPCR validation.
<p>Primer details and PCR cycling conditions for the qPCR validation.</p
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