492 research outputs found

    Experience-Dependent Modulation of C. elegans Behavior by Ambient Oxygen

    Get PDF
    SummaryBackground: Ambient oxygen (O2) influences the behavior of organisms from bacteria to man. In C. elegans, an atypical O2 binding soluble guanylate cyclase (sGC), GCY-35, regulates O2 responses. However, how acute and chronic changes in O2 modify behavior is poorly understood.Results: Aggregating C. elegans strains can respond to a reduction in ambient O2 by a rapid, reversible, and graded inhibition of roaming behavior. This aerokinetic response is mediated by GCY-35 and GCY-36 sGCs, which appear to become activated as O2 levels drop and to depolarize the AQR, PQR, and URX neurons. Coexpression of GCY-35 and GCY-36 is sufficient to transform olfactory neurons into O2 sensors. Natural variation at the npr-1 neuropeptide receptor alters both food-sensing and O2-sensing circuits to reconfigure the salient features of the C. elegans environment. When cultivated in 1% O2 for a few hours, C. elegans reset their preferred ambient O2, seeking instead of avoiding 0%–5% O2. This plasticity involves reprogramming the AQR, PQR, and URX neurons.Conclusions: To navigate O2 gradients, C. elegans can modulate turning rates and speed of movement. Aerotaxis can be reprogrammed by experience or engineered artificially. We propose a model in which prolonged activation of the AQR, PQR, and URX neurons by low O2 switches on previously inactive O2 sensors. This enables aerotaxis to low O2 environments and may encode a “memory” of previous cultivation in low O2

    Tissue chemistry and carbon allocation in seedlings of Pinus palustris subjected to elevated atmospheric CO2 and water stress

    Get PDF
    Longleaf pine (Pinus palustris Mill.) seedlings were grown in 45-1 pots and exposed to ambient or elevated (365 or 730 uamol CO2 mol-1 ) CO2 concentration in open-top chambers for 20 months. Two water-stress treatments (target values of -0.5 or -1.5 MPa xylem pressure potential) were imposed 19 weeks after initiation of the study. At harvest, tissues (needles, stems, taproots, coarse roots, and fine roots) were analyzed for carbon (C), nitrogen (N), nonpolar extractives (fats, waxes, and oils), nonstructural carbohydrates (sugars and starch), structural components (cellulose and lignin), and tannins. The greatest dry weights and lowest N concentrations occurred in tissues of plants grown at elevated CO 2 or with adequate water. Although allocation of C fractions among tissues was generally unaffected by treatments, concentrations of the analyzed compounds were influenced by treatments in needles and taproots, but not in stems and lateral roots. Needles and taproots of plants exposed to elevated CO2 had increased concentrations of nonstructural carbohydrates. Among plant tissues, elevated CO2 caused reductions in structural C concentrations and foliar concentrations of fats, waxes and oils

    Fine Root Productivity and Dynamics on a Forested Floodplain in South Carolina

    Get PDF
    The highly dynamic, fine-root component of forested wetland ecosystems has received inadequate attention in the literature. Characterizing fine root dynamics is a challenging endeavor in any system, but the difficulties are particularly evident in forested floodplains where frequent hydrologic fluctuations directly influence fine root dynamics. Fine root (\u3c 3mm) biomass, production, and turnover were estimated for three soils exhibiting different drainage patterns within a mixed-oak community on the Coosawhatchie River floodplain, Jasper County, SC. Within a 45-cm deep vertical profile, 74% of total fine root biomass was restricted to the upper 15 cm of the soil surface. Fine root biomass decreased as the soil became less well-drained (e.g., fine root biomass in well-drained soil \u3e intermediately drained soil \u3e poorly drained soil). Fine root productivity was measured for one year using minirhizotrons and in-situ screens. Both methods suggested higher fine root production in better drained soils but showed frequent fluctuations in fine root growth and mortality, suggesting the need for frequent sampling at short intervals (e.g., monthly) to accurately assess fine root growth and turnover. Fine root production, estimated with in-situ screens, was 1.5, 1.8, and 0.9 Mg ha-1 yr-1 in the well-drained, intermediately drained, and poorly drained soils, respectively. Results from minirhizotrons indicated that fine roots in well-drained soils grew to greater depths while fine roots in poorly drained soils were restricted to surface soils. Minirhizotrons also revealed that the distribution of fine roots among morphological classes changed between well-drained and poorly drained soils

    Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

    Get PDF
    Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

    Global Search for New Physics with 2.0/fb at CDF

    Get PDF
    Data collected in Run II of the Fermilab Tevatron are searched for indications of new electroweak-scale physics. Rather than focusing on particular new physics scenarios, CDF data are analyzed for discrepancies with the standard model prediction. A model-independent approach (Vista) considers gross features of the data, and is sensitive to new large cross-section physics. Further sensitivity to new physics is provided by two additional algorithms: a Bump Hunter searches invariant mass distributions for "bumps" that could indicate resonant production of new particles; and the Sleuth procedure scans for data excesses at large summed transverse momentum. This combined global search for new physics in 2.0/fb of ppbar collisions at sqrt(s)=1.96 TeV reveals no indication of physics beyond the standard model.Comment: 8 pages, 7 figures. Final version which appeared in Physical Review D Rapid Communication

    Observation of Orbitally Excited B_s Mesons

    Get PDF
    We report the first observation of two narrow resonances consistent with states of orbitally excited (L=1) B_s mesons using 1 fb^{-1} of ppbar collisions at sqrt{s} = 1.96 TeV collected with the CDF II detector at the Fermilab Tevatron. We use two-body decays into K^- and B^+ mesons reconstructed as B^+ \to J/\psi K^+, J/\psi \to \mu^+ \mu^- or B^+ \to \bar{D}^0 \pi^+, \bar{D}^0 \to K^+ \pi^-. We deduce the masses of the two states to be m(B_{s1}) = 5829.4 +- 0.7 MeV/c^2 and m(B_{s2}^*) = 5839.7 +- 0.7 MeV/c^2.Comment: Version accepted and published by Phys. Rev. Let

    Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

    Get PDF
    We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

    Modern temporal network theory: A colloquium

    Full text link
    The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.Comment: Final accepted versio

    Ecological connectivity between the areas beyond national jurisdiction and coastal waters: Safeguarding interests of coastal communities in developing countries

    Get PDF
    The UN General Assembly has made a unanimous decision to start negotiations to establish an international, legally-binding instrument for the conservation and sustainable use of marine biological diversity within Areas Beyond National Jurisdiction (ABNJ). However, there has of yet been little discussion on the importance of this move to the ecosystem services provided by coastal zones in their downstream zone of influence. Here, we identify the ecological connectivity between ABNJ and coastal zones as critically important in the negotiation process and apply several approaches to identify some priority areas for protection from the perspective of coastal populations of Least Developed Countries (LDCs). Initially, we review the scientific evidence that demonstrates ecological connectivity between ABNJ and the coastal zones with a focus on the LDCs. We then use ocean modelling to develop a number of metrics and spatial maps that serve to quantify the connectivity of the ABNJ to the coastal zone. We find that the level of exposure to the ABNJ influences varies strongly between countries. Similarly, not all areas of the ABNJ are equal in their impacts on the coastline. Using this method, we identify the areas of the ABNJ that are in the most urgent need of protection on the grounds of the strength of their potential downstream impacts on the coastal populations of LDCs. We argue that indirect negative impacts of the ABNJ fishing, industrialisation and pollution, communicated via oceanographic, cultural and ecological connectivity to the coastal waters of the developing countries should be of concern
    corecore