Functional asymmetry of transmembrane segments in nicotinic acetylcholine receptors

Nicotinic acetylcholine receptors are heteropentameric ion channels that open upon activation to a single conducting state. The second transmembrane segments of each subunit were identified as channel-forming elements, but their respective contribution in the gating process remains unclear. Moreover, the detailed impact of variations of the membrane potential, such as occurring during an action potential, on the transmembrane domains, is unknown. Residues at the 12′ position, close to the center of each second transmembrane segment, play a key role in channel gating. We examined their functional symmetry by substituting a lysine to that position of each subunit and measuring the electrical activity of single channels. For 12′ lysines in the α, γ and δ subunits rapid transitions between an intermediate and large conductance appeared, which are interpreted as single lysine protonation events. From the kinetics of these transitions we calculated the pK a values of respective lysines and showed that they vary differently with membrane hyperpolarization. Respective mutations in β or ε subunits gave receptors with openings of either intermediate or large conductance, suggesting extreme pK a values in two open state conformations. The results demonstrate that these parts of the highly homologous transmembrane domains, as probed by the 12′ lysines, sense unequal microenvironments and are differently affected by physiologically relevant voltage changes. Moreover, observation of various gating events for mutants of α subunits suggests that the open channel pore exists in multiple conformations, which in turn supports the notion of functional asymmetry of the channe

Ökobilanz von Rind-, Schweine- und Geflügelfleisch aus konventionellen, tierfreundlichen und biologischen Produktionssystemen

The study compared the environmental impacts of different production systems (conventional, increased animal welfare label and organic) for beef, pork and chicken meat at the farm gate using model farms based on Swiss real farm data. Results showed that feeding and feed production had a high influence, particularly for monogastric animals. Organic farming had lower mineral resource use and ecotoxicity due to the ban of mineral fertilisers and pesticides but had a lower productivity per area, which influenced several impact categories such as eutrophication and land use negatively when expressed per kg live weight. Fundamentally, most of the decisive parameters for the environmental impacts of a production system turned out to be generally valid for both conventional and organic production

Application of Risk within Net Present Value Calculations for Government Projects

In January 2004, President Bush announced a new vision for space exploration. This included retirement of the current Space Shuttle fleet by 2010 and the development of new set of launch vehicles. The President's vision did not include significant increases in the NASA budget, so these development programs need to be cost conscious. Current trade study procedures address factors such as performance, reliability, safety, manufacturing, maintainability, operations, and costs. It would be desirable, however, to have increased insight into the cost factors behind each of the proposed system architectures. This paper reports on a set of component trade studies completed on the upper stage engine for the new launch vehicles. Increased insight into architecture costs was developed by including a Net Present Value (NPV) method and applying a set of associated risks to the base parametric cost data. The use of the NPV method along with the risks was found to add fidelity to the trade study and provide additional information to support the selection of a more robust design architecture

A method for high-energy, low-dose mammography using edge illumination x-ray phase-contrast imaging

Since the breast is one of the most radiosensitive organs, mammography is arguably the area where lowering radiation dose is of the uttermost importance. Phase-based x-ray imaging methods can provide opportunities in this sense, since they do not require x-rays to be stopped in tissue for image contrast to be generated. Therefore, x-ray energy can be considerably increased compared to those usually exploited by conventional mammography. In this article we show how a novel, optimized approach can lead to considerable dose reductions. This was achieved by matching the edge-illumination phase method, which reaches very high angular sensitivity also at high x-ray energies, to an appropriate image processing algorithm and to a virtually noise-free detection technology capable of reaching almost 100% efficiency at the same energies. Importantly, while proof-of-concept was obtained at a synchrotron, the method has potential for a translation to conventional sources

Learning Scheduling Algorithms for Data Processing Clusters

Efficiently scheduling data processing jobs on distributed compute clusters requires complex algorithms. Current systems, however, use simple generalized heuristics and ignore workload characteristics, since developing and tuning a scheduling policy for each workload is infeasible. In this paper, we show that modern machine learning techniques can generate highly-efficient policies automatically. Decima uses reinforcement learning (RL) and neural networks to learn workload-specific scheduling algorithms without any human instruction beyond a high-level objective such as minimizing average job completion time. Off-the-shelf RL techniques, however, cannot handle the complexity and scale of the scheduling problem. To build Decima, we had to develop new representations for jobs' dependency graphs, design scalable RL models, and invent RL training methods for dealing with continuous stochastic job arrivals. Our prototype integration with Spark on a 25-node cluster shows that Decima improves the average job completion time over hand-tuned scheduling heuristics by at least 21%, achieving up to 2x improvement during periods of high cluster load

Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers

Evaluation and mitigation of enteric methane (CH4) emissions from ruminant livestock, in particular from dairy cows, have acquired global importance for sustainable, climate-smart cattle production. Based on CH4 reference measurements obtained with the SF6 tracer technique to determine ruminal CH4 production, a current equation permits evaluation of individual daily CH4 emissions of dairy cows based on milk Fourier transform mid-infrared (FT-MIR) spectra. However, the respiration chamber (RC) technique is considered to be more accurate than SF6 to measure CH4 production from cattle. This study aimed to develop an equation that allows estimating CH4 emissions of lactating cows recorded in an RC from corresponding milk FT-MIR spectra and to challenge its robustness and relevance through validation processes and its application on a milk spectral database. This would permit confirming the conclusions drawn with the existing equation based on SF6 reference measurements regarding the potential to estimate daily CH4 emissions of dairy cows from milk FT-MIR spectra. A total of 584 RC reference CH4 measurements (mean ± standard deviation of 400 ± 72 g of CH4/d) and corresponding standardized milk mid-infrared spectra were obtained from 148 individual lactating cows between 7 and 321 d in milk in 5 European countries (Germany, Switzerland, Denmark, France, and Northern Ireland). The developed equation based on RC measurements showed calibration and cross-validation coefficients of determination of 0.65 and 0.57, respectively, which is lower than those obtained earlier by the equation based on 532 SF6 measurements (0.74 and 0.70, respectively). This means that the RC-based model is unable to explain the variability observed in the corresponding reference data as well as the SF6-based model. The standard errors of calibration and cross-validation were lower for the RC model (43 and 47 g/d vs. 66 and 70 g/d for the SF6 version, respectively), indicating that the model based on RC data was closer to actual values. The root mean squared error (RMSE) of calibration of 42 g/d represents only 10% of the overall daily CH4 production, which is 23 g/d lower than the RMSE for the SF6-based equation. During the external validation step an RMSE of 62 g/d was observed. When the RC equation was applied to a standardized spectral database of milk recordings collected in the Walloon region of Belgium between January 2012 and December 2017 (1,515,137 spectra from 132,658 lactating cows in 1,176 different herds), an average ± standard deviation of 446 ± 51 g of CH4/d was estimated, which is consistent with the range of the values measured using both RC and SF6 techniques. This study confirmed that milk FT-MIR spectra could be used as a potential proxy to estimate daily CH4 emissions from dairy cows provided that the variability to predict is covered by the model