817 research outputs found

    Metabolic response of early-lactating cows exposed to transport and high altitude grazing conditions

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    The metabolic response of dairy cows to high as opposed to low altitude conditions (2000 m v. 400 m above sea level) was determined. In the first experiment, four cows were subjected to a series of measurements before, during and after transport from lowland to high altitude pasture. During transport, cortisol, l-lactate and non-esterified fatty acids were significantly elevated but decreased within 1 to 3 days to initial levels. After transport, ÎČ-hydroxybutyrate and the thyroid hormones immediately increased and returned within 3 weeks to initial levels. Plasma urea increased during transport and subsequently was at an intermediate level due to the different diet. There were no direct carry-over effects of transport on metabolic traits during pasturing. In the second experiment, three groups of six different dairy cows were either grazed in one of two consecutive years or kept inside (2nd year only). Lowland sojourn lasted for 4 weeks, and high altitude period for 8 weeks. At the end of high altitude sojourn, both outside and inside groups were found still to have significantly higher plasma cortisol values than at lowland. Thyroid hormones and ketosis related metabolites sharply increased at the start of the alpine period and were elevated for 1 to 3 weeks thereafter. According to the hormonal and metabolic profiles, the permanently housed cows did not benefit from the less adverse climatic conditions and the lower physical strain. Plasma urea closely reflected dietary changes in the ratio of nitrogen to fermentable organic matter. Plasma protein, albumin, creatinine, and liver enzyme activities were not affected by transport or high altitude sojourn in both experiments. The results indicate that the metabolic response to transport and high altitude conditions can be mostly explained by the efforts to cover the additional energy requirements. Overall the data suggest a wide but nevertheless limited ability of early-lactating cows to adapt to high altitude condition

    Tracking magnetic bright point motions through the solar atmosphere

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    High-cadence, multiwavelength observations and simulations are employed for the analysis of solar photospheric magnetic bright points (MBPs) in the quiet Sun. The observations were obtained with the Rapid Oscillations in the Solar Atmosphere (ROSA) imager and the Interferometric Bidimensional Spectrometer at the Dunn Solar Telescope. Our analysis reveals that photospheric MBPs have an average transverse velocity of approximately 1 km s−1, whereas their chromospheric counterparts have a slightly higher average velocity of 1.4 km s−1. Additionally, chromospheric MBPs were found to be around 63 per cent larger than the equivalent photospheric MBPs. These velocity values were compared with the output of numerical simulations generated using the MURAM code. The simulated results were similar, but slightly elevated, when compared to the observed data. An average velocity of 1.3 km s−1 was found in the simulated G-band images and an average of 1.8 km s−1 seen in the velocity domain at a height of 500 km above the continuum formation layer. Delays in the change of velocities were also analysed. Average delays of ∌4 s between layers of the simulated data set were established and values of ∌29 s observed between G-band and Ca II K ROSA observations. The delays in the simulations are likely to be the result of oblique granular shock waves, whereas those found in the observations are possibly the result of a semi-rigid flux tube

    How to make ecological models useful for environmental management

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    Understanding and predicting the ecological consequences of different management alternatives is becoming increasingly important to support environmental management decisions. Ecological models could contribute to such predictions, but in the past this was often not the case. Ecological models are often developed within research projects but are rarely used for practical applications. In this synthesis paper, we discuss how to strengthen the role of ecological modeling in supporting environmental management decisions with a focus on methodological aspects. We address mainly ecological modellers but also potential users of modeling results. Various modeling approaches can be used to predict the response of ecosystems to anthropogenic interventions, including mechanistic models, statistical models, and machine learning approaches. Regardless of the chosen approach, we outline how to better align the modeling to the decision making process, and identify six requirements that we believe are important to increase the usefulness of ecological models for management support, especially if management decisions need to be justified to the public. These cover: (i) a mechanistic understanding regarding causality, (ii) alignment of model input and output with the management decision, (iii) appropriate spatial and temporal resolutions, (iv) uncertainty quantification, (v) sufficient predictive performance, and (vi) transparent communication. We discuss challenges and synthesize suggestions for addressing these points. © 2019 The Author(s)This paper was initialized during a special session on Ecological Modelling at the 10th Symposium for European Freshwater Science 2017 ( http://www.sefs10.cz/ ) and further developed during the AQUACROSS project, funded by European Union's Horizon 2020 research and innovation programme (Grant agreement No. 642317 ). SD, SDL and MF were partly funded by the “GLANCE” project (Global Change Effects in River Ecosystems; 01 LN1320A) through the German Federal Ministry of Education and Research ( BMBF ). SDL has received additional funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 748625 . JML acknowledges the support of the Spanish Government through MarĂ­a de Maeztu excellence accreditation 2018–2021 (Ref. MDM-2017-0714 )

    Combining eight research areas to foster the uptake of ecosystem-based management in fresh waters

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    Freshwater ecosystems are under a constant risk of being irreversibly damaged by human pressures that threaten their biodiversity, the sustainability of ecosystem services (ESs), and human well-being. Despite the implementation of various environmental regulations, the challenges of safeguarding freshwater assets have so far not been tackled successfully. A promising way forward to stop the loss of freshwater biodiversity and to sustain freshwater-based ESs is by implementing ecosystem-based management (EBM), an environmental planning and adaptive management approach that jointly considers social and ecological needs. Responsible for considerable recent success in sustainably managing and conserving marine ecosystems, EBM has not yet been championed for fresh waters. A major reason for the delayed uptake of EBM in fresh waters is likely to be its complexity, requiring planners to be familiar with the latest developments in a range of different research areas. EBM would therefore benefit from becoming more tangible to receive attention on the ground. To facilitate uptake, eight core research areas for EBM and their innovations are introduced, and the way in which they feed into the workflow that guides the EBM planning stage is explained. The workflow links biodiversity distributions with ES supply-and-demand modelling and SMART (specific, measurable, attainable, relevant, and timely) target planning, including scenario- and cross-realm perspectives, the prioritization of management alternatives, spatial prioritization of biodiversity conservation and ES areas, and the quantification of uncertainties. Given the extensive resources, time, and technical capacity required to implement the full workflow, a light and an ultralight version of the workflow are also provided. Applied in concert, the eight well-known research areas allow for better planning and operationalizing, and eventually for implementing EBM in freshwater ecosystems. EBM has great potential to increase public acceptance by introducing the consideration of human needs and aspirations into typically biodiversity-driven conservation and management approaches. This will ultimately improve the integrity of freshwater ecosystems. © 2019 John Wiley & Sons, Ltd.German Federal Ministry of Education and Research, Grant/Award Number: 01 LN1320A; Horizon 2020 Framework Programme, Grant/Award Number: 642317; Marie Sklodowska‐Curie Global Fellowship, Grant/Award Number: 748625; RamĂłn y Cajal, Grant/Award Number: RYC‐2013‐1397

    FOXP3 Inhibitory Peptide P60 Increases Efficacy of Cytokine-induced Killer Cells against Renal and Pancreatic Cancer Cells

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    Background/Aim: Cytokine-induced killer (CIK) cells are ex vivo expanded major histocompatibility complex (MHC)-unrestricted cytotoxic cells with promising effects against a variety of cancer types. Regulatory T-cells (T-reg) have been shown to reduce the effectiveness of CIK cells against tumor cells. Peptide P60 has been shown to inhibit the immunosuppressive functions of T-regs. This study aimed at examining the effect of p60 on CIK cells efficacy against renal and pancreatic cancer cells. Materials and Methods: The effect of P60 on CIK cytotoxicity was examined using flow cytometry, WST-8-based cell viability assay and interferon Îł (IFNÎł) ELISA. Results: P60 treatment resulted in a significant decrease in the viability of renal and pancreatic cancer cell lines co-cultured with CIK cells. No increase in IFNÎł secretion from CIK cells was detected following treatment with P60. P60 caused no changes in the distribution of major effector cell populations in CIK cell cultures. Conclusion: P60 may potentiate CIK cell cytotoxicity against tumor cells

    Effect of concurrent vitamin A and iodine deficiencies on the thyroid-pituitary axis in rats

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    OBJECTIVE: Deficiencies of vitamin A and iodine are common in many developing countries. Vitamin A deficiency (VAD) may adversely affect thyroid metabolism. The study aim was to investigate the effects of concurrent vitamin A and iodine deficiencies on the thyroid-pituitary axis in rats. DESIGN: Weanling rats (n = 56) were fed diets deficient in vitamin A (VAD group), iodine (ID group), vitamin A and iodine (VAD + ID group), or sufficient in both vitamin A and iodine (control) for 30 days in a pair-fed design. Serum retinol (SR), thyroid hormones (FT(4), TT(4), FT(3), and TT(3)), serum thyrotropin (TSH), pituitary TSHbeta mRNA expression levels, and thyroid weights were determined at the end of the depletion period. MAIN OUTCOME: Compared to the control and ID groups, SR concentrations were about 35% lower in the VAD and VAD + ID groups (p < 0.001), indicating moderate VA deficiency. Comparing the VAD and control groups, there were no significant differences in TSH, TSHbeta mRNA, thyroid weight, or thyroid hormone levels. Compared to the control group, serum TSH, TSHbeta mRNA, and thyroid weight were higher (p < 0.05), and FT4 and TT4 were lower (p < 0.001), in the VAD + ID and ID groups. Compared to the ID group, TSH, TSHbeta mRNA, and thyroid weight were higher (p < 0.01) and FT(4) and TT(4) were lower (p < 0.001) in the VAD + ID group. There were no significant differences in TT3 or FT3 concentrations among groups. CONCLUSION: Moderate VAD alone has no measurable effect on the pituitary-thyroid axis. Concurrent ID and VAD produce more severe primary hypothyroidism than ID alone

    Observation of two new Ξb−\Xi_b^- baryon resonances

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    Two structures are observed close to the kinematic threshold in the Ξb0π−\Xi_b^0 \pi^- mass spectrum in a sample of proton-proton collision data, corresponding to an integrated luminosity of 3.0 fb−1^{-1} recorded by the LHCb experiment. In the quark model, two baryonic resonances with quark content bdsbds are expected in this mass region: the spin-parity JP=12+J^P = \frac{1}{2}^+ and JP=32+J^P=\frac{3}{2}^+ states, denoted Ξbâ€Č−\Xi_b^{\prime -} and Ξb∗−\Xi_b^{*-}. Interpreting the structures as these resonances, we measure the mass differences and the width of the heavier state to be m(Ξbâ€Č−)−m(Ξb0)−m(π−)=3.653±0.018±0.006m(\Xi_b^{\prime -}) - m(\Xi_b^0) - m(\pi^{-}) = 3.653 \pm 0.018 \pm 0.006 MeV/c2/c^2, m(Ξb∗−)−m(Ξb0)−m(π−)=23.96±0.12±0.06m(\Xi_b^{*-}) - m(\Xi_b^0) - m(\pi^{-}) = 23.96 \pm 0.12 \pm 0.06 MeV/c2/c^2, Γ(Ξb∗−)=1.65±0.31±0.10\Gamma(\Xi_b^{*-}) = 1.65 \pm 0.31 \pm 0.10 MeV, where the first and second uncertainties are statistical and systematic, respectively. The width of the lighter state is consistent with zero, and we place an upper limit of Γ(Ξbâ€Č−)<0.08\Gamma(\Xi_b^{\prime -}) < 0.08 MeV at 95% confidence level. Relative production rates of these states are also reported.Comment: 17 pages, 2 figure

    Quantum numbers of the X(3872)X(3872) state and orbital angular momentum in its ρ0Jψ\rho^0 J\psi decay

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    Angular correlations in B+→X(3872)K+B^+\to X(3872) K^+ decays, with X(3872)→ρ0J/ψX(3872)\to \rho^0 J/\psi, ρ0→π+π−\rho^0\to\pi^+\pi^- and J/ψ→Ό+Ό−J/\psi \to\mu^+\mu^-, are used to measure orbital angular momentum contributions and to determine the JPCJ^{PC} value of the X(3872)X(3872) meson. The data correspond to an integrated luminosity of 3.0 fb−1^{-1} of proton-proton collisions collected with the LHCb detector. This determination, for the first time performed without assuming a value for the orbital angular momentum, confirms the quantum numbers to be JPC=1++J^{PC}=1^{++}. The X(3872)X(3872) is found to decay predominantly through S wave and an upper limit of 4%4\% at 95%95\% C.L. is set on the fraction of D wave.Comment: 16 pages, 4 figure

    Observation of J/ψpJ/\psi p resonances consistent with pentaquark states in Λb0→J/ψK−p{\Lambda_b^0\to J/\psi K^-p} decays

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    Observations of exotic structures in the J/ψpJ/\psi p channel, that we refer to as pentaquark-charmonium states, in Λb0→J/ψK−p\Lambda_b^0\to J/\psi K^- p decays are presented. The data sample corresponds to an integrated luminosity of 3/fb acquired with the LHCb detector from 7 and 8 TeV pp collisions. An amplitude analysis is performed on the three-body final-state that reproduces the two-body mass and angular distributions. To obtain a satisfactory fit of the structures seen in the J/ψpJ/\psi p mass spectrum, it is necessary to include two Breit-Wigner amplitudes that each describe a resonant state. The significance of each of these resonances is more than 9 standard deviations. One has a mass of 4380±8±294380\pm 8\pm 29 MeV and a width of 205±18±86205\pm 18\pm 86 MeV, while the second is narrower, with a mass of 4449.8±1.7±2.54449.8\pm 1.7\pm 2.5 MeV and a width of 39±5±1939\pm 5\pm 19 MeV. The preferred JPJ^P assignments are of opposite parity, with one state having spin 3/2 and the other 5/2.Comment: 48 pages, 18 figures including the supplementary material, v2 after referee's comments, now 19 figure

    Differential branching fraction and angular analysis of Λb0→ΛΌ+Ό−\Lambda^{0}_{b} \rightarrow \Lambda \mu^+\mu^- decays

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    The differential branching fraction of the rare decay Λb0→ΛΌ+Ό−\Lambda^{0}_{b} \rightarrow \Lambda \mu^+\mu^- is measured as a function of q2q^{2}, the square of the dimuon invariant mass. The analysis is performed using proton-proton collision data, corresponding to an integrated luminosity of 3.0 \mbox{ fb}^{-1}, collected by the LHCb experiment. Evidence of signal is observed in the q2q^2 region below the square of the J/ψJ/\psi mass. Integrating over 15 < q^{2} < 20 \mbox{ GeV}^2/c^4 the branching fraction is measured as d\mathcal{B}(\Lambda^{0}_{b} \rightarrow \Lambda \mu^+\mu^-)/dq^2 = (1.18 ^{+ 0.09} _{-0.08} \pm 0.03 \pm 0.27) \times 10^{-7} ( \mbox{GeV}^{2}/c^{4})^{-1}, where the uncertainties are statistical, systematic and due to the normalisation mode, Λb0→J/ψΛ\Lambda^{0}_{b} \rightarrow J/\psi \Lambda, respectively. In the q2q^2 intervals where the signal is observed, angular distributions are studied and the forward-backward asymmetries in the dimuon (AFBlA^{l}_{\rm FB}) and hadron (AFBhA^{h}_{\rm FB}) systems are measured for the first time. In the range 15 < q^2 < 20 \mbox{ GeV}^2/c^4 they are found to be A^{l}_{\rm FB} = -0.05 \pm 0.09 \mbox{ (stat)} \pm 0.03 \mbox{ (syst)} and A^{h}_{\rm FB} = -0.29 \pm 0.07 \mbox{ (stat)} \pm 0.03 \mbox{ (syst)}.Comment: 27 pages, 10 figures, Erratum adde
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