904 resultados para Simultaneous Localization


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Apis mellifera L., the European honeybee, is a crucial pollinator of many important agricultural crops in the United States. Recently, honeybee colonies have been affected by Colony Collapse Disorder (CCD), a disorder in which the colony fails due to the disappearance of a key functional group of worker bees. Though no direct causalrelationship has been confirmed, hives that experience CCD have been shown to have a high incidence of Deformed Wing Virus (DWV), a common honeybee virus. While the genome sequence and gene-order of DWV has been analyzed fairly recently, few other studies have been performed to understand the molecular characterization of the virus.Since little is known about where DWV proteins localize in infected host cells, the objective of this project was to determine the subcellular localization of two of the important non-structural proteins that are encoded in the DWV genome. This project focused on the protein 3C, an autocatalytic protease which cleaves itself from a longer polyprotein and helps to cut all of the other proteins apart from one another so that they can become functional, and 3D, the RNA-dependent RNA polymerase (RdRp) which is critical for replication of the virus because it copies the viral genome. By tagging nested constructs containing these two proteins and tracking where they localized in living cells, this study aimed to better understand the replication of DWV and to elicit possible targetsfor further research on how to control the virus. Since DWV is a picorna-like virus, distantly related to human viruses such as polio, and picornavirus non-structural proteins aggregate at cellular membranes during viral replication, the major hypothesis was that the 3C and 3CD proteins would localize at cellular organelle membranes as well. Using confocal microscopy, both proteins were found to localize in the cytoplasm, but the 3CDprotein was found to be mostly diffuse cytoplasmic, and the 3C protein was found to localize more specifically on membranous structures just outside of the nucleus.

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The chemotherapeutic drug 5-fluorouracil (5-FU) is widely used for treating solid tumors. Response to 5-FU treatment is variable with 10-30% of patients experiencing serious toxicity partly explained by reduced activity of dihydropyrimidine dehydrogenase (DPD). DPD converts endogenous uracil (U) into 5,6-dihydrouracil (UH(2) ), and analogously, 5-FU into 5-fluoro-5,6-dihydrouracil (5-FUH(2) ). Combined quantification of U and UH(2) with 5-FU and 5-FUH(2) may provide a pre-therapeutic assessment of DPD activity and further guide drug dosing during therapy. Here, we report the development of a liquid chromatography-tandem mass spectrometry assay for simultaneous quantification of U, UH(2) , 5-FU and 5-FUH(2) in human plasma. Samples were prepared by liquid-liquid extraction with 10:1 ethyl acetate-2-propanol (v/v). The evaporated samples were reconstituted in 0.1% formic acid and 10 μL aliquots were injected into the HPLC system. Analyte separation was achieved on an Atlantis dC(18) column with a mobile phase consisting of 1.0 mm ammonium acetate, 0.5 mm formic acid and 3.3% methanol. Positively ionized analytes were detected by multiple reaction monitoring. The analytical response was linear in the range 0.01-10 μm for U, 0.1-10 μm for UH(2) , 0.1-75 μm for 5-FU and 0.75-75 μm for 5-FUH(2) , covering the expected concentration ranges in plasma. The method was validated following the FDA guidelines and applied to clinical samples obtained from ten 5-FU-treated colorectal cancer patients. The present method merges the analysis of 5-FU pharmacokinetics and DPD activity into a single assay representing a valuable tool to improve the efficacy and safety of 5-FU-based chemotherapy.

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Complete resection of grade II gliomas might prolong survival but is not always possible. The goal of the study was to evaluate the location of unexpected grade II gliomas remnants after assumed complete removal with intraoperative (iop) MRI and to assess the reason for their non-detection.

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External beam proton radiation therapy has been used since 1975 to treat choroidal melanoma. For tumor location determination during proton radiation treatment, surgical tantalum clips are registered with image data. This report introduces the intraoperative application of an opto-electronic navigation system to determine with high precision the position of the tantalum markers and their spatial relationship to the tumor and anatomical landmarks. The application of the technique in the first 4 patients is described.

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Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

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Methane and nitrous oxide are important greenhouse gases which show a strong increase in atmospheric mixing ratios since pre-industrial time as well as large variations during past climate changes. The understanding of their biogeochemical cycles can be improved using stable isotope analysis. However, high-precision isotope measurements on air trapped in ice cores are challenging because of the high susceptibility to contamination and fractionation. Here, we present a dry extraction system for combined CH4 and N2O stable isotope analysis from ice core air, using an ice grating device. The system allows simultaneous analysis of δD(CH4) or δ13C(CH4), together with δ15N(N2O), δ18O(N2O) and δ15N(NO+ fragment) on a single ice core sample, using two isotope mass spectrometry systems. The optimum quantity of ice for analysis is about 600 g with typical "Holocene" mixing ratios for CH4 and N2O. In this case, the reproducibility (1σ ) is 2.1‰ for δD(CH4), 0.18‰ for δ13C(CH4), 0.51‰ for δ15N(N2O), 0.69‰ for δ18O(N2O) and 1.12‰ for δ15N(NO+ fragment). For smaller amounts of ice the standard deviation increases, particularly for N2O isotopologues. For both gases, small-scale intercalibrations using air and/or ice samples have been carried out in collaboration with other institutes that are currently involved in isotope measurements of ice core air. Significant differences are shown between the calibration scales, but those offsets are consistent and can therefore be corrected for.

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AIM: The aim of this study was to compare the clinical outcomes after 2 years with bone level implants placed to restore a single missing teeth that needed simultaneous augmentation and were treated with a transmucosal or submerged approach. METHODS: This study analyzed a subset of patients included in an ongoing prospective multicenter randomized clinical trial (RCT) involving12 centers where patients were to be followed-up to 5 years after loading. Of the 120 implants that were placed in the original study, and randomly assigned to submerged or non-submerged healing, 52 needed simultaneous augmentation (28 women patients and 24 men patients, between 23 and 78 years of age). Twenty-seven of them received implants with submerged healing (AuS), while in 25 patients the implants were inserted with a non-submerged protocol (AuNS). At the 2-year follow-up visit, radiographic crestal bone level changes were recorded as well as soft tissue parameters included Pocket probing depth (PPD), bleeding on probing (BoP) and clinical attachment level (CAL) at teeth adjacent to the implant site. RESULTS: After 2 years a small amount of bone resorption was found in both groups (0.37 ± 0.49 mm in the AuS group and 0.54 ± 0.76 in the AuNS group; P < 0.001). There was no statistically significant difference between AuS Group and AuNS group for PPD (2.5 vs. 2.4 mm), BOP (BOP + sites: 8.8% vs. 11.5%) and CAL (2.8 vs. 2.4 mm) at the 2-year follow-up visit. CONCLUSIONS: When a single implant is placed in the aesthetic zone in conjunction with bone augmentation for a moderate peri-implant defect, submerged and transmucosal healing determine similar outcome, hence there is no need to submerge an implant in this given clinical situation.

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Locally affine (polyaffine) image registration methods capture intersubject non-linear deformations with a low number of parameters, while providing an intuitive interpretation for clinicians. Considering the mandible bone, anatomical shape differences can be found at different scales, e.g. left or right side, teeth, etc. Classically, sequential coarse to fine registration are used to handle multiscale deformations, instead we propose a simultaneous optimization of all scales. To avoid local minima we incorporate a prior on the polyaffine transformations. This kind of groupwise registration approach is natural in a polyaffine context, if we assume one configuration of regions that describes an entire group of images, with varying transformations for each region. In this paper, we reformulate polyaffine deformations in a generative statistical model, which enables us to incorporate deformation statistics as a prior in a Bayesian setting. We find optimal transformations by optimizing the maximum a posteriori probability. We assume that the polyaffine transformations follow a normal distribution with mean and concentration matrix. Parameters of the prior are estimated from an initial coarse to fine registration. Knowing the region structure, we develop a blockwise pseudoinverse to obtain the concentration matrix. To our knowledge, we are the first to introduce simultaneous multiscale optimization through groupwise polyaffine registration. We show results on 42 mandible CT images.