90 research outputs found

    Caribbean Leucothoidae (Crustacea: Amphipoda) of Panama

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    Leucothoid amphipods were collected from sponge, ascidian, and bivalve mollusk hosts around Bocas del Toro, Panama. New host and locality records are reported for 10 species. Morphological variation is noted in some species originally described from Belize and South Florida. Future molecular research will help to clarify the importance of this variation. A key to the Caribbean species of the Leucothoidae collected around Bocas del Toro, Panama is provided based on morphological characters

    Leucothoidae

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    Four genera and 17 species of leucothoids, the majority of these belonging to the genus Leucothoe, are herein reported from the Great Barrier Reef. Fifteen species are new to science and only Anamixis bazimut has been previously reported from the Great Barrier Reef

    FRESHWATER MACROINVERTEBRATE COMMUNITIES IN BALDWIN COUNTY, GEORGIA

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    Freshwater ecosystems are critical habitats for maintaining biodiversity, often providing refuge for organisms especially in urban settings. Baldwin County, GA is home to many freshwater lakes that are part of the Oconee River watershed. Despite ongoing water quality monitoring, aquatic macroinvertebrates are under studied in the area. Aquatic macroinvertebrate diversity of one forested and one residential lake in Milledgeville, GA was documented for the first time. Despite low sample size, community composition was significantly different between lakes, with 27 families in Lake Laurel (forested), 44 families in Lake Oliver Hardy (residential), and only 19 families collected from both lakes. Seasonal trends revealed the highest diversity in the summer. These data provide a baseline for the potential use of monitoring aquatic ecosystem health using aquatic macroinvertebrates in Milledgeville, GA

    Severity of Giardia infection associated with post-infectious fatigue and abdominal symptoms two years after

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    <p>Abstract</p> <p>Background</p> <p>A high rate of post-infectious fatigue and abdominal symptoms two years after a waterborne outbreak of giardiasis in Bergen, Norway in 2004 has previously been reported. The aim of this report was to identify risk factors associated with such manifestations.</p> <p>Methods</p> <p>All laboratory confirmed cases of giardiasis (n = 1262) during the outbreak in Bergen in 2004 received a postal questionnaire two years after. Degree of post-infectious abdominal symptoms and fatigue, as well as previous abdominal problems, was recorded. In the statistical analyses number of treatment courses, treatment refractory infection, delayed education and sick leave were used as indices of protracted and severe <it>Giardia </it>infection. Age, gender, previous abdominal problems and symptoms during infection were also analysed as possible risk factors. Simple and multiple ordinal logistic regression models were used for the analyses.</p> <p>Results</p> <p>The response rate was 81% (1017/1262), 64% were women and median age was 31 years (range 3-93), compared to 61% women and 30 years (range 2-93) among all 1262 cases. Factors in multiple regression analysis significantly associated with abdominal symptoms two years after infection were: More than one treatment course, treatment refractory infection, delayed education, bloating and female gender. Abdominal problems prior to <it>Giardia </it>infection were not associated with post-infectious abdominal symptoms. More than one treatment course, delayed education, sick leave more than 2 weeks, and malaise at the time of infection, were significantly associated with fatigue in the multiple regression analysis, as were increasing age and previous abdominal problems.</p> <p>Conclusion</p> <p>Protracted and severe <it>giardiasis </it>seemed to be a risk factor for post-infectious fatigue and abdominal symptoms two years after clearing the <it>Giardia </it>infection.</p

    Exhaled Aerosol Transmission of Pandemic and Seasonal H1N1 Influenza Viruses in the Ferret

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    Person-to-person transmission of influenza viruses occurs by contact (direct and fomites) and non-contact (droplet and small particle aerosol) routes, but the quantitative dynamics and relative contributions of these routes are incompletely understood. The transmissibility of influenza strains estimated from secondary attack rates in closed human populations is confounded by large variations in population susceptibilities. An experimental method to phenotype strains for transmissibility in an animal model could provide relative efficiencies of transmission. We developed an experimental method to detect exhaled viral aerosol transmission between unanesthetized infected and susceptible ferrets, measured aerosol particle size and number, and quantified the viral genomic RNA in the exhaled aerosol. During brief 3-hour exposures to exhaled viral aerosols in airflow-controlled chambers, three strains of pandemic 2009 H1N1 strains were frequently transmitted to susceptible ferrets. In contrast one seasonal H1N1 strain was not transmitted in spite of higher levels of viral RNA in the exhaled aerosol. Among three pandemic strains, the two strains causing weight loss and illness in the intranasally infected ‘donor’ ferrets were transmitted less efficiently from the donor than the strain causing no detectable illness, suggesting that the mucosal inflammatory response may attenuate viable exhaled virus. Although exhaled viral RNA remained constant, transmission efficiency diminished from day 1 to day 5 after donor infection. Thus, aerosol transmission between ferrets may be dependent on at least four characteristics of virus-host relationships including the level of exhaled virus, infectious particle size, mucosal inflammation, and viral replication efficiency in susceptible mucosa

    Markov Chain Monte Carlo and the Application to Geodetic Time Series Analysis

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    The time evolution of geophysical phenomena can be characterised by stochastic time series. The stochastic nature of the signal stems from the geophysical phenomena involved and any noise, which may be due to, e.g., un-modelled effects or measurement errors. Until the 1990's, it was usually assumed that white noise could fully characterise this noise. However, this was demonstrated to be not the case and it was proven that this assumption leads to underestimated uncertainties of the geophysical parameters inferred from the geodetic time series. Therefore, in order to fully quantify all the uncertainties as robustly as possible, it is imperative to estimate not only the deterministic but also the stochastic parameters of the time series. In this regard, the Markov Chain Monte Carlo (MCMC) method can provide a sample of the distribution function of all parameters, including those regarding the noise, e.g., spectral index and amplitudes. After presenting the MCMC method and its implementation in our MCMC software we apply it to synthetic and real time series and perform a cross-evaluation using Maximum Likelihood Estimation (MLE) as implemented in the CATS software. Several examples as to how the MCMC method performs as a parameter estimation method for geodetic time series are given in this chapter. These include the applications to GPS position time series, superconducting gravity time series and monthly mean sea level (MSL) records, which all show very different stochastic properties. The impact of the estimated parameter uncertainties on sub-sequentially derived products is briefly demonstrated for the case of plate motion models. Finally, the MCMC results for weekly downsampled versions of the benchmark synthetic GNSS time series as provided in Chapter 2 are presented separately in an appendix

    A framework for human microbiome research

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    A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

    Structure, function and diversity of the healthy human microbiome

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    Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

    The World Amphipoda Database: history and progress

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    We provide an overview of the World Amphipoda Database (WAD), a global species database that is part of the World Register of Marine Species (WoRMS). Launched in 2013, the database contains entries for over 10,500 accepted species names. Edited currently by 31 amphipod taxonomists, following WoRMS priorities, the WAD has at least one editor per major group. All accepted species are checked by the editors, as is the authorship available for all of the names. The higher classification is documented for every species and a type species is recorded for every genus name. This constitutes five of the 13 priorities for completion, set by WoRMS. In 2015, five LifeWatch grants were allocated for WAD activities. These included a general training workshop in 2016, together with data input for the superfamily Lysianassoidea and for a number of non-marine groups. Philanthropy grants in 2019 and 2021 covered more important gaps across the whole group. Further work remains to complete the linking of unaccepted names, original descriptions, and environmental information. Once these tasks are completed, the database will be considered complete for 8 of the 13 priorities, and efforts will continue to input new taxa annually and focus on the remaining priorities, particularly the input of type localities. We give an overview of the current status of the order Amphipoda, providing counts of the number of genera and species within each family belonging to the six suborders currently recognized
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