891 research outputs found

    Phosphorus removal by a fixed-bed hybrid polymer nanocomposite biofilm reactor

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    Eutrophication is one of the main challenges regarding the ecological quality of surface waters, phosphorus bioavailability being its main driver. In this context, a novel hybrid polymer nanocomposite (HPN-Pr) biofilm reactor aimed at integrated chemical phosphorus adsorption and biological removal was conceived. The assays pointed to removal of 1.2 mg P/g of reactive phosphorus and 1.01 mg P/g of total phosphorus under steady-state conditions. A mathematical adsorption–biological model was applied to predict reactor performance, which indicated that biological activity has a positive effect on reactor performance, increasing the amount of reactive phosphorus removed.The authors acknowledge the Portuguese Foundation for Science and Technology for the financial support under Project SFRH/BD/39085/2007

    Modes, mechanisms and evidence of bet hedging in rotifer diapause traits

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    In this contribution, we review our knowledge on bet-hedging strategies associated with rotifer diapause. First, we describe the ecological scenario under which bet hedging is likely to have evolved in three diapause-related traits in monogonont rotifer populations: (1) the timing of sex (because diapausing eggs are produced via sexual reproduction), (2) the sexual reproduction ratio (i.e. the fraction of sexually reproducing females) and (3) the timing of diapausing egg hatching. Then, we describe how to discriminate among bet-hedging modes and discuss which modes and mechanisms better fit the variability observed in these traits in rotifers. Finally, we evaluate the strength of the empirical evidence for bet hedging in the scarce studies available, and we call for the need of research at different levels of biological complexity to fully understand bet hedging in rotifer diapause

    High-yield methods for accurate two-alternative visual psychophysics in head-fixed mice

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    Research in neuroscience relies increasingly on the mouse, a mammalian species that affords unparalleled genetic tractability and brain atlases. Here we introduce high-yield methods for probing mouse visual decisions. Mice are head-fixed, which facilitates repeatable visual stimulation, eye tracking, and brain access. They turn a steering wheel to make two-alternative choices, forced or unforced. Learning is rapid thanks to intuitive coupling of stimuli to wheel position. The mouse decisions deliver high-quality psychometric curves for detection and discrimination, and conform to the predictions of a simple probabilistic observer model. The task is readily paired with two-photon imaging of cortical activity. Optogenetic inactivation reveals that the task requires the visual cortex. Mice are motivated to perform the task by fluid reward or optogenetic stimulation of dopaminergic neurons. This stimulation elicits larger number of trials and faster learning. These methods provide a platform to accurately probe mouse vision and its neural basis

    Modelling diverse root density dynamics and deep nitrogen uptake — a simple approach

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    We present a 2-D model for simulation of root density and plant nitrogen (N) uptake for crops grown in agricultural systems, based on a modification of the root density equation originally proposed by Gerwitz and Page in J Appl Ecol 11:773–781, (1974). A root system form parameter was introduced to describe the distribution of root length vertically and horizontally in the soil profile. The form parameter can vary from 0 where root density is evenly distributed through the soil profile, to 8 where practically all roots are found near the surface. The root model has other components describing root features, such as specific root length and plant N uptake kinetics. The same approach is used to distribute root length horizontally, allowing simulation of root growth and plant N uptake in row crops. The rooting depth penetration rate and depth distribution of root density were found to be the most important parameters controlling crop N uptake from deeper soil layers. The validity of the root distribution model was tested with field data for white cabbage, red beet, and leek. The model was able to simulate very different root distributions, but it was not able to simulate increasing root density with depth as seen in the experimental results for white cabbage. The model was able to simulate N depletion in different soil layers in two field studies. One included vegetable crops with very different rooting depths and the other compared effects of spring wheat and winter wheat. In both experiments variation in spring soil N availability and depth distribution was varied by the use of cover crops. This shows the model sensitivity to the form parameter value and the ability of the model to reproduce N depletion in soil layers. This work shows that the relatively simple root model developed, driven by degree days and simulated crop growth, can be used to simulate crop soil N uptake and depletion appropriately in low N input crop production systems, with a requirement of few measured parameters

    Calculating the energy spectra of magnetic molecules: application of real- and spin-space symmetries

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    The determination of the energy spectra of small spin systems as for instance given by magnetic molecules is a demanding numerical problem. In this work we review numerical approaches to diagonalize the Heisenberg Hamiltonian that employ symmetries; in particular we focus on the spin-rotational symmetry SU(2) in combination with point-group symmetries. With these methods one is able to block-diagonalize the Hamiltonian and thus to treat spin systems of unprecedented size. In addition it provides a spectroscopic labeling by irreducible representations that is helpful when interpreting transitions induced by Electron Paramagnetic Resonance (EPR), Nuclear Magnetic Resonance (NMR) or Inelastic Neutron Scattering (INS). It is our aim to provide the reader with detailed knowledge on how to set up such a diagonalization scheme.Comment: 29 pages, many figure

    Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

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    Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

    Dependence of cancer cell adhesion kinetics on integrin ligand surface density measured by a high-throughput label-free resonant waveguide grating biosensor

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    A novel high-throughput label-free resonant waveguide grating (RWG) imager biosensor, the Epic® BenchTop (BT), was utilized to determine the dependence of cell spreading kinetics on the average surface density (vRGD) of integrin ligand RGD-motifs. vRGD was tuned over four orders of magnitude by co-adsorbing the biologically inactive PLL-g-PEG and the RGD-functionalized PLL-g-PEG-RGD synthetic copolymers from their mixed solutions onto the sensor surface. Using highly adherent human cervical tumor (HeLa) cells as a model system, cell adhesion kinetic data of unprecedented quality were obtained. Spreading kinetics were fitted with the logistic equation to obtain the spreading rate constant (r) and the maximum biosensor response (Δλmax), which is assumed to be directly proportional to the maximum spread contact area (Amax). r was found to be independent of the surface density of integrin ligands. In contrast, Δλmax increased with increasing RGD surface density until saturation at high densities. Interpreting the latter behavior with a simple kinetic mass action model, a 2D dissociation constant of 1753 ± 243 μm−2 (corresponding to a 3D dissociation constant of ~30 μM) was obtained for the binding between RGD-specific integrins embedded in the cell membrane and PLL-g-PEG-RGD. All of these results were obtained completely noninvasively without using any labels

    Antimicrobial Peptides and Skin: A Paradigm of Translational Medicine

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    Antimicrobial peptides (AMPs) are small, cationic, amphiphilic peptides with broad-spectrum microbicidal activity against both bacteria and fungi. In mammals, AMPs form the first line of host defense against infections and generally play an important role as effector agents of the innate immune system. The AMP era was born more than 6 decades ago when the first cationic cyclic peptide antibiotics, namely polymyxins and tyrothricin, found their way into clinical use. Due to the good clinical experience in the treatment of, for example, infections of mucus membranes as well as the subsequent understanding of mode of action, AMPs are now considered for treatment of inflammatory skin diseases and for improving healing of infected wounds. Based on the preclinical findings, including pathobiochemistry and molecular medicine, targeted therapy strategies are developed and first results indicate that AMPs influence processes of diseased skin. Importantly, in contrast to other antibiotics, AMPs do not seem to propagate the development of antibiotic-resistant micro-organisms. Therefore, AMPs should be tested in clinical trials for their efficacy and tolerability in inflammatory skin diseases and chronic wounds. Apart from possible fields of application, these peptides appear suited as an example of the paradigm of translational medicine for skin diseases which is today seen as a `two-way road' - from bench to bedside and backwards from bedside to bench. Copyright (c) 2012 S. Karger AG, Base
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