2,211 research outputs found

    The control of indirect effects of biomanipulation

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    Results from long-term investigations on biomanipulation show that indirect effects are at least as important as direct effects are for the stability of biomanipulation. Three types of indirect effects can be distinguished: (1) a change in quantity or quality of the resource base, (2) behavioural change of the prey, and (3) development of anti-predator traits. Although indirect effects of type (2), (e.g. a change in the pattern of vertical migration of zooplankton), and type (3), (e.g. development of helmets and neck teeth in Daphnia), are important mechanisms, the most essential indirect effects regarding biomanipulation belong to type (1). An example of the latter will be demonstrated: the complex of indirect effects of enhanced grazing by large herbivores on the phosphorus metabolism of the lake. It is concluded that control of the indirect effects is absolutely necessary to stabilize biomanipulation measures, but this is much more difficult than the control of direct effects and needs deeper insights into the structuring mechanisms of food webs. Proper management of fish stocks, in combination with the control of phosphorus load and/or the physical conditions, seems to be the most promising way of controlling the indirect effects of biomanipulation

    Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity

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    The process of anaerobic digestion in which waste biomass is transformed to methane by complex microbial communities has been modeled for more than 16 years by parametric gray box approaches that simplify process biology and do not resolve intracellular microbial activity. Information on such activity, however, has become available in unprecedented detail by recent experimental advances in metatranscriptomics and metaproteomics. The inclusion of such data could lead to more powerful process models of anaerobic digestion that more faithfully represent the activity of microbial communities. We augmented the Anaerobic Digestion Model No. 1 (ADM1) as the standard kinetic model of anaerobic digestion by coupling it to Flux-Balance-Analysis (FBA) models of methanogenic species. Steady-state results of coupled models are comparable to standard ADM1 simulations if the energy demand for non-growth associated maintenance (NGAM) is chosen adequately. When changing a constant feed of maize silage from continuous to pulsed feeding, the final average methane production remains very similar for both standard and coupled models, while both the initial response of the methanogenic population at the onset of pulsed feeding as well as its dynamics between pulses deviates considerably. In contrast to ADM1, the coupled models deliver predictions of up to 1,000s of intracellular metabolic fluxes per species, describing intracellular metabolic pathway activity in much higher detail. Furthermore, yield coefficients which need to be specified in ADM1 are no longer required as they are implicitly encoded in the topology of the species’ metabolic network. We show the feasibility of augmenting ADM1, an ordinary differential equation-based model for simulating biogas production, by FBA models implementing individual steps of anaerobic digestion. While cellular maintenance is introduced as a new parameter, the total number of parameters is reduced as yield coefficients no longer need to be specified. The coupled models provide detailed predictions on intracellular activity of microbial species which are compatible with experimental data on enzyme synthesis activity or abundance as obtained by metatranscriptomics or metaproteomics. By providing predictions of intracellular fluxes of individual community members, the presented approach advances the simulation of microbial community driven processes and provides a direct link to validation by state-of-the-art experimental techniques

    Bemerkungen zur griechischen Kunstgeschichte

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    Elementary Functional Properties of Single HCN2 Channels

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    AbstractHyperpolarization-activated cyclic-nucleotide-gated (HCN) channels are tetramers that evoke rhythmic electrical activity in specialized neurons and cardiac cells. These channels are activated by hyperpolarizing voltage, and the second messenger cAMP can further enhance the activation. Despite the physiological importance of HCN channels, their elementary functional properties are still unclear. In this study, we expressed homotetrameric HCN2 channels in Xenopus oocytes and performed single-channel experiments in patches containing either one or multiple channels. We show that the single-channel conductance is as low as 1.67 pS and that channel activation is a one-step process. We also observed that the time between the hyperpolarizing stimulus and the first channel opening, the first latency, determines the activation process alone. Notably, at maximum hyperpolarization, saturating cAMP drives the channel to open for unusually long periods. In particular, at maximum activation by hyperpolarization and saturating cAMP, the open probability approaches unity. In contrast to other reports, no evidence of interchannel cooperativity was observed. In conclusion, single HCN2 channels operate only with an exceptionally low conductance, and both activating stimuli, voltage and cAMP, exclusively control the open probability

    Unraveling Subunit Cooperativity in Homotetrameric HCN2 Channels

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    AbstractIn a multimeric receptor protein, the binding of a ligand can modulate the binding of a succeeding ligand. This phenomenon, called cooperativity, is caused by the interaction of the receptor subunits. By using a complex Markovian model and a set of parameters determined previously, we analyzed how the successive binding of four ligands leads to a complex cooperative interaction of the subunits in homotetrameric HCN2 pacemaker channels. The individual steps in the model were characterized by Gibbs free energies for the equilibria and activation energies, specifying the affinity of the binding sites and the transition rates, respectively. Moreover, cooperative free energies were calculated for each binding step in both the closed and the open channel. We show that the cooperativity sequence positive-negative-positive determined for the binding affinity is generated by the combined effect of very different cooperativity sequences determined for the binding and unbinding rates, which are negative-negative-positive and no-negative-no, respectively. It is concluded that in the ligand-induced activation of HCN2 channels, the sequence of cooperativity based on the binding affinity is caused by two even qualitatively different sequences of cooperativity that are based on the rates of ligand binding and unbinding

    Behavioral Forces Driving Information Unraveling

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    Information unraveling is an elegant theoretical argument suggesting that private information may be fully and voluntarily surrendered. The experimental literature has, however, failed to provide evidence of complete unraveling and has suggested senders' limited depth of reasoning as one behavioral explanation. In our novel design, decision-making is essentially sequential, which removes the requirements on subjects' reasoning and should enable subjects to play the standard Nash equilibrium with full revelation. However, our design also facilitates coordination on equilibria with partial unraveling which exist with other-regarding preferences. Our data confirm that the new design is successful in that it avoids miscoordination entirely. Roughly half of the groups fully unravel whereas other groups exhibit monotonic outcomes with partial unraveling. Altogether, we nd more information unraveling with the new design, but there is clear evidence that other-regarding preferences do play a role in impeding unraveling

    Deactivation of CNGA2 Channels follows Intricate Pathways

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    No One Size (PPM) Fits All: Towards Privacy in Stream Processing Systems

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    Stream processing systems (SPSs) have been designed to process data streams in real-time, allowing organizations to analyze and act upon data on-the-fly, as it is generated. However, handling sensitive or personal data in these multilayered SPSs that distribute resources across sensor, fog, and cloud layers raises privacy concerns, as the data may be subject to unauthorized access and attacks that can violate user privacy, hence facing regulations such as the GDPR across the SPS layers. To address these issues, different privacy-preserving mechanisms (PPMs) are proposed to protect user privacy in SPSs. Yet, selecting and applying such PPMs in SPSs is challenging, since they must operate in real-time while tolerating little overhead. The multilayered nature of SPSs complicates privacy protection because each layer may confront different privacy threats, which must be addressed by specific PPMs. To overcome these challenges, we present Prinseps, our comprehensive privacy vision for SPSs. Towards this vision, we (1) identify critical privacy threats on different layers of the multilayered SPS, (2) evaluate the effectiveness of existing PPMs in addressing such threats, and (3) integrate privacy considerations into the decision-making processes of SPSs.Comment: Vision paper accepted to DEBS 202
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