A predicted three-dimensional structure of human cytochrome P450: implications for substrate specificity

A three-dimensional structure for human cytochrome P450IA1 waspredicted based on the crystal coordinates of cytochrome P450camfrom Pseudomonas putida. As there was only 15% residue identitybetween the two enzymes, additional information was used toestablish an accurate sequence alignment that is a prerequisitefor model building. Twelve representative eukaryotic sequenceswere aligned and a net prediction of secondary structure wasmatched against the known -helices and ß-sheets ofP450cam. The cam secondary structure provided a fixed main-chainframework onto which loops of appropriate length from the humanP450IA1 structure were added. The model-built structure of thehuman cytochrome conformed to the requirements for the segregationof polar and nonpolar residues between the core and the surface.The first 44 residues of human cytochrome P450 could not bebuilt into the model and sequence analysis suggested that residues1–26 formed a single membrane-spanning segment. Examinationof the sequences of cytochrome P450s from distinct gene familiessuggested specific residues that could account for the differencesin substrate specificity. A major substrate for P450IA1, 3-methyl-cholanthrene,was fitted into the proposed active site and this planar aromaticmolecule could be accommodated into the available cavity. Residuesthat are likely to interact with the haem were identified. Thesequence similarity between 59 eukaryotic enzymes was representedas a dendrogram that in general clustered according to genefamily. Until a crystallographic structure is available, thismodel-building study identifies potential residues in cytochromeP450s important in the function of these enzymes and these residuesare candidates for site-directed mutagenesis.     

Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging

Objective

Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation.

Materials and methods

Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader’s subjective confidence to assess the images (not confident, confident, very confident).

Results

Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as ‘perfusion deficit’, 113 vs. 109 as ‘dark rim artifacts’, 9 vs. 7 as ‘uncertain signal loss’, and 817 vs. 824 as ‘normal’. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as ‘good’ or ‘excellent’ (92 vs. 63%), and the diagnostic confidence more often as “very confident” (71 vs. 45%) compared to non-MoCo.

Conclusions

The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader’s subjective confidence to assess the images were rated more favorably for MoCo.

     

Summary Maps for Lifelong Visual Localization

Robots that use vision for localization need to handle environments that are subject to seasonal and structural change, and operate under changing lighting and weather conditions. We present a framework for lifelong localization and mapping designed to provide robust and metrically accurate online localization in these kinds of changing environments. Our system iterates between offline map building, map summary, and online localization. The offline mapping fuses data from multiple visually varied datasets, thus dealing with changing environments by incorporating new information. Before passing these data to the online localization system, the map is summarized, selecting only the landmarks that are deemed useful for localization. This Summary Map enables online localization that is accurate and robust to the variation of visual information in natural environments while still being computationally efficient. We present a number of summary policies for selecting useful features for localization from the multisession map, and we explore the tradeoff between localization performance and computational complexity. The system is evaluated on 77 recordings, with a total length of 30 kilometers, collected outdoors over 16 months. These datasets cover all seasons, various times of day, and changing weather such as sunshine, rain, fog, and snow. We show that it is possible to build consistent maps that span data collected over an entire year, and cover day‐to‐night transitions. Simple statistics computed on landmark observations are enough to produce a Summary Map that enables robust and accurate localization over a wide range of seasonal, lighting, and weather conditions.     

Improved Quality Output through Computer‐Based Training: An Automotive Assembly Field Study

In this article, two field experiments, conducted in an automotive assembly plant, evaluate how computer‐based training of operational sequences and related quality information can support the assembly performance of the operators. The experiments were performed during the launch of a new vehicle. A comparison was made of learning progress and quality performance between a reference group of operators that only had regular training and a test group for which some of the regular training was replaced with individual computer‐based training. Both quantitative measures of the quality output and questionnaires and observations were used to evaluate the effects of computer‐based training. The results show a clear positive difference in learning progress and improvements in quality output for the test group compared with the reference group. This combined with positive attitudes expressed by the operators and their team leaders shows that this type of training is an effective way to train operators during launches of new vehicles in automotive production.     

Towards social behavior in virtual-agent navigation

We present Social Groups and Navigation (SGN), a method to simulate the walking behavior of small pedestrian groups in virtual environments. SGN is the first method to simulate group behavior on both global and local levels of an underlying planning hierarchy. We define quantitative metrics to measure the coherence and the sociality of a group based on existing empirical data of real crowds. SGN does not explicitly model coherent and social formations, but it lets such formations emerge from simple geometric rules. In addition to a previous version, SGN also handles group-splitting to smaller groups throughout navigation as well as social sub-group behavior whenever a group has to temporarily split up to re-establish its coherence. For groups of four, SGN generates between 13% and 53% more socially-friendly behavior than previous methods, measured over the lifetime of a group in the simulation. For groups of three, the gain is between 15% and 31%, and for groups of two, the gain is between 1% and 4%. SGN is designed in a flexible way, and it can be integrated into any crowd-simulation framework that handles global path planning and any path following as separate steps. Experiments show that SGN enables the simulation of thousands of agents in real time.     

Experiences with large-scale operational trials of ALTO-enhanced P2P filesharing in an intra-ISP scenario

Application Layer Traffic Optimization (ALTO) has recently gained attention in the research and standardisation community as a way for a network operator to guide the peer selection process of distributed applications by providing network layer topology information. In particular P2P applications are expected to gain from ALTO, due to the many connections peers form among each other, often without taking network layer topology information into account. In this paper, we present results of an extensive intra-ISP trial with an ALTO-enhanced P2P filesharing software. In summary, our results show that—depending on the concrete setting and on the distribution of upload capacity in the network—ALTO enables an ISP to save operational costs significantly while not degrading application layer performance noticeably. In addition, based on our experience we are able to give advice to operators on how to save costs with ALTO while not sacrificing application layer performance at all.     

High pressure cell for neutron reflectivity measurements up to 2500 bar

The design of a high pressure (HP) cell for neutron reflectivity experiments is described. The cell can be used to study solid-liquid interfaces under pressures up to 2500 bar (250 MPa). The sample interface is based on a thick silicon block with an area of about 14 cm(2). This area is in contact with the sample solution which has a volume of only 6 cm(3). The sample solution is separated from the pressure transmitting medium, water, by a thin flexible polymer membrane. In addition, the HP cell can be temperature-controlled by a water bath in the range 5-75°C. By using an aluminum alloy as window material, the assembled HP cell provides a neutron transmission as high as 41%. The maximum angle of incidence that can be used in reflectivity experiments is 7.5°. The large accessible pressure range and the low required volume of the sample solution make this HP cell highly suitable for studying pressure-induced structural changes of interfacial proteins, supported lipid membranes, and, in general, biomolecular systems that are available in small quantities, only. To illustrate the performance of the HP cell, we present neutron reflectivity data of a protein adsorbate under high pressure and a lipid film which undergoes several phase transitions upon pressurization.     

A strong direct product theorem for quantum query complexity

We show that quantum query complexity satisfies a strong direct product theorem. This means that computing k copies of a function with fewer than k times the quantum queries needed to compute one copy of the function implies that the overall success probability will be exponentially small in k. For a boolean function f, we also show an XOR lemma—computing the parity of k copies of f with fewer than k times the queries needed for one copy implies that the advantage over random guessing will be exponentially small. We do this by showing that the multiplicative adversary method, which inherently satisfies a strong direct product theorem, characterizes bounded-error quantum query complexity. In particular, we show that the multiplicative adversary bound is always at least as large as the additive adversary bound, which is known to characterize bounded-error quantum query complexity.