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    Influenza forecasting with Google Flu Trends
    (Public Library of Science, 2013-02-14) Dugas, Andrea Freyer; Jalalpour, Mehdi; Gel, Yulia; Levin, Scott; Torcaso, Fred; Igusa, Takeru; Rothman, Richard E.
    Background We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. Methods Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004-2011) divided into seven training and out-of-sample verification sets. Forecasting procedures using classical Box-Jenkins, generalized linear models (GLM), and generalized linear autoregressive moving average (GARMA) methods were employed to develop the final model and assess the relative contribution of external variables such as, Google Flu Trends, meteorological data, and temporal information. Results A GARMA(3,0) forecast model with Negative Binomial distribution integrating Google Flu Trends information provided the most accurate influenza case predictions. The model, on the average, predicts weekly influenza cases during 7 out-of-sample outbreaks within 7 cases for 83% of estimates. Google Flu Trend data was the only source of external information to provide statistically significant forecast improvements over the base model in four of the seven out-of-sample verification sets. Overall, the p-value of adding this external information to the model is 0.0005. The other exogenous variables did not yield a statistically significant improvement in any of the verification sets. Conclusions Integer-valued autoregression of influenza cases provides a strong base forecast model, which is enhanced by the addition of Google Flu Trends confirming the predictive capabilities of search query based syndromic surveillance. This accessible and flexible forecast model can be used by individual medical centers to provide advanced warning of future influenza cases.
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    Multi-parametric clustering for sensor mode coordination in cognitive wireless sensor networks
    (Public Library of Science, 2013-02-13) Wang, Xiao Yu; Wong, Alexander
    The deployment of wireless sensor networks for healthcare applications have been motivated and driven by the increasing demand for real-time monitoring of patients in hospital and large disaster response environments. A major challenge in developing such sensor networks is the need for coordinating a large number of randomly deployed sensor nodes. In this study, we propose a multi-parametric clustering scheme designed to aid in the coordination of sensor nodes within cognitive wireless sensor networks. In the proposed scheme, sensor nodes are clustered together based on similar network behaviour across multiple network parameters, such as channel availability, interference characteristics, and topological characteristics, followed by mechanisms for forming, joining and switching clusters. Extensive performance evaluation is conducted to study the impact on important factors such as clustering overhead, cluster joining estimation error, interference probability, as well as probability of reclustering. Results show that the proposed clustering scheme can be an excellent candidate for use in large scale cognitive wireless sensor network deployments with high dynamics.
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    NALCN ion channels have alternative selectivity filters resembling calcium channels or sodium channels
    (Public Library of Science, 2013-01-28) Senatore, Adriano; Monteil, Arnaud; van Minnen, Jan; Smit, August B.; Spafford, J. David
    NALCN is a member of the family of ion channels with four homologous, repeat domains that include voltage-gated calcium and sodium channels. NALCN is a highly conserved gene from simple, extant multicellular organisms without nervous systems such as sponges and placozoans and mostly remains a single gene compared to the calcium and sodium channels which diversified into twenty genes in humans. The single NALCN gene has alternatively-spliced exons at exons 15 or exon 31 that splices in novel selectivity filter residues that resemble calcium channels (EEEE) or sodium channels (EKEE or EEKE). NALCN channels with alternative calcium, (EEEE) and sodium, (EKEE or EEKE) -selective pores are conserved in simple bilaterally symmetrical animals like flatworms to non-chordate deuterostomes. The single NALCN gene is limited as a sodium channel with a lysine (K)-containing pore in vertebrates, but originally NALCN was a calcium-like channel, and evolved to operate as both a calcium channel and sodium channel for different roles in many invertebrates. Expression patterns of NALCN-EKEE in pond snail, Lymnaea stagnalis suggest roles for NALCN in secretion, with an abundant expression in brain, and an up-regulation in secretory organs of sexually-mature adults such as albumen gland and prostate. NALCN-EEEE is equally abundant as NALCN-EKEE in snails, but is greater expressed in heart and other muscle tissue, and 50% less expressed in the brain than NALCN-EKEE. Transfected snail NALCN-EEEE and NALCN-EKEE channel isoforms express in HEK-293T cells. We were not able to distinguish potential NALCN currents from background, non-selective leak conductances in HEK293T cells. Native leak currents without expressing NALCN genes in HEK-293T cells are NMDG+ impermeant and blockable with 10 µM Gd3+ ions and are indistinguishable from the hallmark currents ascribed to mammalian NALCN currents expressed in vitro by Lu et al. in Cell. 2007 Apr 20;129(2):371-83.
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    Horizontal gene transfer contributed to the evolution of extracellular surface structures: The freshwater polyp Hydra is covered by a complex fibrous cuticle containing glycosaminoglucans and proteins of the PPOD and SWT (sweet tooth) families
    (Public Library of Science, 2012-12-27) Bottger, Angelika; Doxey, Andrew C.; Hess, Michael W.; Pfaller, Kristian; Salvenmoser, Willi; Deutzmann, Rainer; Geissner, Andreas; Pauly, Barbara; Altstatter, Johannes; Munder, Sandra; Heim, Astrid; Gabius, Hans-Joachim; McConkey, Brendan J.; David, Charles N.
    The single-cell layered ectoderm of the fresh water polyp Hydra fulfills the function of an epidermis by protecting the animals from the surrounding medium. Its outer surface is covered by a fibrous structure termed the cuticle layer, with similarity to the extracellular surface coats of mammalian epithelia. In this paper we have identified molecular components of the cuticle. We show that its outermost layer contains glycoproteins and glycosaminoglycans and we have identified chondroitin and chondroitin-6-sulfate chains. In a search for proteins that could be involved in organising this structure we found PPOD proteins and several members of a protein family containing only SWT (sweet tooth) domains. Structural analyses indicate that PPODs consist of two tandem β-trefoil domains with similarity to carbohydrate-binding sites found in lectins. Experimental evidence confirmed that PPODs can bind sulfated glycans and are secreted into the cuticle layer from granules localized under the apical surface of the ectodermal epithelial cells. PPODs are taxon-specific proteins which appear to have entered the Hydra genome by horizontal gene transfer from bacteria. Their acquisition at the time Hydra evolved from a marine ancestor may have been critical for the transition to the freshwater environment.
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    Invasive mussels alter the littoral food web of a large lake: Stable isotopes reveal drastic shifts in sources and flow of energy
    (Public Library of Science, 2012-12-17) Ozersky, Ted; Evans, David O.; Barton, David R.
    We investigated how establishment of invasive dreissenid mussels impacted the structure and energy sources of the littoral benthic food web of a large temperate lake. We combined information about pre- and postdreissenid abundance, biomass, and secondary production of the littoral benthos with results of carbon and nitrogen stable isotope analysis of archival (predreissenid) and recent (postdreissenid) samples of all common benthic taxa. This approach enabled us to determine the importance of benthic and sestonic carbon to the littoral food web before, and more than a decade after dreissenid establishment. Long term dreissenid presence was associated with a 32-fold increase in abundance, 6-fold increase in biomass, and 14-fold increase in secondary production of the littoral benthos. Dreissenids comprised a large portion of the post-invasion benthos, making up 13, 38, and 56% of total abundance, biomass, and secondary production, respectively. The predreissenid food web was supported primarily by benthic primary production, while sestonic material was relatively more important to the postdreissenid food web. The absolute importance of both sestonic material and benthic primary production to the littoral benthos increased considerably following dreissenid establishment. Our results show drastic alterations to food web structure and suggest that dreissenid mussels redirect energy and material from the water column to the littoral benthos both through biodeposition of sestonic material as well as stimulation of benthic primary production.