36 resultados para Domain analysis


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The bacterial phosphoenolpyruvate: sugar phosphotransferase system serves the combined uptake and phosphorylation of carbohydrates. This structurally and functionally complex system is composed of several conserved functional units that, through a cascade of phosphorylated intermediates, catalyze the transfer of the phosphate moiety from phosphoenolpyruvate to the substrate, which is bound to the integral membrane domain IIC. The wild-type glucose-specific IIC domain (wt-IIC(glc)) of Escherichia coli was cloned, overexpressed and purified for biochemical and functional characterization. Size-exclusion chromatography and scintillation-proximity binding assays showed that purified wt-IIC(glc) was homogenous and able to bind glucose. Crystallization was pursued following two different approaches: (i) reconstitution of wt-IIC(glc) into a lipid bilayer by detergent removal through dialysis, which yielded tubular 2D crystals, and (ii) vapor-diffusion crystallization of detergent-solubilized wt-IIC(glc), which yielded rhombohedral 3D crystals. Analysis of the 2D crystals by cryo-electron microscopy and the 3D crystals by X-ray diffraction indicated resolutions of better than 6Å and 4Å, respectively. Furthermore, a complete X-ray diffraction data set could be collected and processed to 3.93Å resolution. These 2D and 3D crystals of wt-IIC(glc) lay the foundation for the determination of the first structure of a bacterial glucose-specific IIC domain.

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BACKGROUND In contrast to objective structured clinical examinations (OSCEs), mini-clinical evaluation exercises (mini-CEXs) take place at the clinical workplace. As both mini-CEXs and OSCEs assess clinical skills, but within different contexts, this study aims at analyzing to which degree students' mini-CEX scores can be predicted by their recent OSCE scores and/or context characteristics. METHODS Medical students participated in an end of Year 3 OSCE and in 11 mini-CEXs during 5 different clerkships of Year 4. The students' mean scores of 9 clinical skills OSCE stations and mean 'overall' and 'domain' mini-CEX scores, averaged over all mini-CEXs of each student were computed. Linear regression analyses including random effects were used to predict mini-CEX scores by OSCE performance and characteristics of clinics, trainers, students and assessments. RESULTS A total of 512 trainers in 45 clinics provided 1783 mini-CEX ratings for 165 students; OSCE results were available for 144 students (87 %). Most influential for the prediction of 'overall' mini-CEX scores was the trainers' clinical position with a regression coefficient of 0.55 (95 %-CI: 0.26-0.84; p < .001) for residents compared to heads of department. Highly complex tasks and assessments taking place in large clinics significantly enhanced 'overall' mini-CEX scores, too. In contrast, high OSCE performance did not significantly increase 'overall' mini-CEX scores. CONCLUSION In our study, Mini-CEX scores depended rather on context characteristics than on students' clinical skills as demonstrated in an OSCE. Ways are discussed which focus on either to enhance the scores' validity or to use narrative comments only.

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FGFRL1 is a single-pass transmembrane protein with three extracellular Ig domains. When overexpressed in CHO cells or related cell types, it induces cell-cell fusion and formation of large, multinucleated syncytia. For this fusion-promoting activity, only the membrane-proximal Ig domain (Ig3) and the transmembrane domain are required. It does not matter whether the transmembrane domain is derived from FGFRL1 or from another receptor, but the distance of the Ig3 domain to the membrane is crucial. Fusion can be inhibited with soluble recombinant proteins comprising the Ig1-Ig2-Ig3 or the Ig2-Ig3 domains as well as with monoclonal antibodies directed against Ig3. Mutational analysis reveals a hydrophobic site in Ig3 that is required for fusion. If a single amino acid from this site is mutated, fusion is abolished. The site is located on a β-sheet, which is part of a larger β-barrel, as predicted by computer modeling of the 3D structure of FGFRL1. It is possible that this site interacts with a target protein of neighboring cells to trigger cell-cell fusion.

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PURPOSE: To differentiate diabetic macular edema (DME) from pseudophakic cystoid macular edema (PCME) based solely on spectral-domain optical coherence tomography (SD-OCT). METHODS: This cross-sectional study included 134 participants: 49 with PCME, 60 with DME, and 25 with diabetic retinopathy (DR) and ME after cataract surgery. First, two unmasked experts classified the 25 DR patients after cataract surgery as either DME, PCME, or mixed-pattern based on SD-OCT and color-fundus photography. Then all 134 patients were divided into two datasets and graded by two masked readers according to a standardized reading-protocol. Accuracy of the masked readers to differentiate the diseases based on SD-OCT parameters was tested. Parallel to the masked readers, a computer-based algorithm was established using support vector machine (SVM) classifiers to automatically differentiate disease entities. RESULTS: The masked readers assigned 92.5% SD-OCT images to the correct clinical diagnose. The classifier-accuracy trained and tested on dataset 1 was 95.8%. The classifier-accuracy trained on dataset 1 and tested on dataset 2 to differentiate PCME from DME was 90.2%. The classifier-accuracy trained and tested on dataset 2 to differentiate all three diseases was 85.5%. In particular, higher central-retinal thickness/retinal-volume ratio, absence of an epiretinal-membrane, and solely inner nuclear layer (INL)-cysts indicated PCME, whereas higher outer nuclear layer (ONL)/INL ratio, the absence of subretinal fluid, presence of hard exudates, microaneurysms, and ganglion cell layer and/or retinal nerve fiber layer cysts strongly favored DME in this model. CONCLUSIONS: Based on the evaluation of SD-OCT, PCME can be differentiated from DME by masked reader evaluation, and by automated analysis, even in DR patients with ME after cataract surgery. The automated classifier may help to independently differentiate these two disease entities and is made publicly available.

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FGFRL1 is a member of the fibroblast growth factor receptor (FGFR) family. Similar to the classical receptors FGFR1-FGFR4, it contains three extracellular Ig-like domains and a single transmembrane domain. However, it lacks the intracellular tyrosine kinase domain that would be required for signal transduction, but instead contains a short intracellular tail with a peculiar histidine-rich motif. This motif has been conserved during evolution from mollusks to echinoderms and vertebrates. Only the sequences of FgfrL1 from a few rodents diverge at the C-terminal region from the canonical sequence, as they appear to have suffered a frameshift mutation within the histidine-rich motif. This mutation is observed in mouse, rat and hamster, but not in the closely related rodents mole rat (Nannospalax) and jerboa (Jaculus), suggesting that it has occurred after branching of the Muridae and Cricetidae from the Dipodidae and Spalacidae. The consequence of the frameshift is a deletion of a few histidine residues and an extension of the C-terminus by about 40 unrelated amino acids. A similar frameshift mutation has also been observed in a human patient with a craniosynostosis syndrome as well as in several patients with colorectal cancer and bladder tumors, suggesting that the histidine-rich motif is prone to mutation. The reason why this motif was conserved during evolution in most species, but not in mice, is not clear.

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We introduce gradient-domain rendering for Monte Carlo image synthesis.While previous gradient-domain Metropolis Light Transport sought to distribute more samples in areas of high gradients, we show, in contrast, that estimating image gradients is also possible using standard (non-Metropolis) Monte Carlo algorithms, and furthermore, that even without changing the sample distribution, this often leads to significant error reduction. This broadens the applicability of gradient rendering considerably. To gain insight into the conditions under which gradient-domain sampling is beneficial, we present a frequency analysis that compares Monte Carlo sampling of gradients followed by Poisson reconstruction to traditional Monte Carlo sampling. Finally, we describe Gradient-Domain Path Tracing (G-PT), a relatively simple modification of the standard path tracing algorithm that can yield far superior results.