933 resultados para ultrastructural localization


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OBJECTIVES To assess the diagnostic value of panoramic views (2D) of patients with impacted maxillary canines by a group of trained orthodontists and oral surgeons, and to quantify the subjective need and reasons for further three-dimensional (3D) imaging. MATERIALS AND METHODS The study comprises 60 patients with panoramic radiographs (2D) and cone beam computed tomography (CBCT) scans (3D), and a total of 72 impacted canines. Data from a standardized questionnaire were compared within (intragroup) and between (intergroup) a group of orthodontists and oral surgeons to assess possible correlations and differences. Furthermore, the questionnaire data were compared with the findings from the CBCT scans to estimate the correlation within and between the two specialties. Finally, the need and reasons for further 3D imaging was analysed for both groups. RESULTS When comparing questionnaire data with the analysis of the respective CBCT scans, orthodontists showed probability (Pr) values ranging from 0.443 to 0.943. Oral surgeons exhibited Pr values from 0.191 to 0.946. Statistically significant differences were found for the labiopalatal location of the impacted maxillary canine (P = 0.04), indicating a higher correlation in the orthodontist group. The most frequent reason mentioned for the further need of 3D analysis was the labiopalatal location of the impacted canines. Oral surgeons were more in favour of performing further 3D imaging (P = 0.04). CONCLUSIONS Orthodontists were more likely to diagnose the exact labiopalatal position of impacted maxillary canines when using panoramic views only. Generally, oral surgeons more often indicated the need for further 3D imaging.

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Meditation is a self-induced and willfully initiated practice that alters the state of consciousness. The meditation practice of Zazen, like many other meditation practices, aims at disregarding intrusive thoughts while controlling body posture. It is an open monitoring meditation characterized by detached moment-to-moment awareness and reduced conceptual thinking and self-reference. Which brain areas differ in electric activity during Zazen compared to task-free resting? Since scalp electroencephalography (EEG) waveforms are reference-dependent, conclusions about the localization of active brain areas are ambiguous. Computing intracerebral source models from the scalp EEG data solves this problem. In the present study, we applied source modeling using low resolution brain electromagnetic tomography (LORETA) to 58-channel scalp EEG data recorded from 15 experienced Zen meditators during Zazen and no-task resting. Zazen compared to no-task resting showed increased alpha-1 and alpha-2 frequency activity in an exclusively right-lateralized cluster extending from prefrontal areas including the insula to parts of the somatosensory and motor cortices and temporal areas. Zazen also showed decreased alpha and beta-2 activity in the left angular gyrus and decreased beta-1 and beta-2 activity in a large bilateral posterior cluster comprising the visual cortex, the posterior cingulate cortex and the parietal cortex. The results include parts of the default mode network and suggest enhanced automatic memory and emotion processing, reduced conceptual thinking and self-reference on a less judgmental, i.e., more detached moment-to-moment basis during Zazen compared to no-task resting.

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Background: Very few mitochondrial myopathies have been described in horses. Objective: To examine the ultrastructure of muscle mitochondria in equine cases of myopathy of unknown origin. Materials & methods: Biopsies of vastus lateralis of the Musculus quadriceps femoris were taken predominantly immediately post mortem and processed for transmission electron microscopy. As a result, electron micrographs of 90 horses in total were available for analysis comprising 4 control horses, 16 horses suffering from myopathy and 70 otherwise diseased horses. Results: Following a thorough clinical and laboratory work-up, four out of five patients that did not fit into the usual algorithm to detect known causes of myopathy showed ultrastructural mitochondrial alterations. Small mitochondria with zones with complete disruption of cristae associated with lactic acidemia were detected in a 17-year-old pony mare, extremely long and slender mitochondria with longitudinal cristae in a 5-year-old Quarter horse stallion, a mixture of irregular extremely large mitochondria (measuring 2500 by 800 nm) next to smaller ones in an 8-year-old Hanoverian mare and round mitochondria with only few cristae in a 11-year-old pony gelding. It remains uncertain whether the subsarcolemmal mitochondrial accumulations observed in the fifth patient have any pathological significance. Conclusions: Ultrastructural alterations in mitochondria were detected in at least four horses. To conclude that these are due to mitochondrial dysfuntions, biochemical tests should be performed. Practical applications: The possibility of a mitochondrial myopathy should be included in the differential diagnosis of muscle weakness.

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We present a numerical study of electromagnetic wave transport in disordered quasi-one-dimensional waveguides at terahertz frequencies. Finite element method calculations of terahertz wave propagation within LiNbO3 waveguides with randomly arranged air-filled circular scatterers exhibit an onset of Anderson localization at experimentally accessible length scales. Results for the average transmission as a function of waveguide length and scatterer density demonstrate a clear crossover from diffusive to localized transport regime. In addition, we find that transmission fluctuations grow dramatically when crossing into the localized regime. Our numerical results are in good quantitative agreement with theory over a wide range of experimentally accessible parameters both in the diffusive and localized regime opening the path towards experimental observation of terahertz wave localization.

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Time-based indoor localization has been investigated for several years but the accuracy of existing solutions is limited by several factors, e.g., imperfect synchronization, signal bandwidth and indoor environment. In this paper, we compare two time-based localization algorithms for narrow-band signals, i.e., multilateration and fingerprinting. First, we develop a new Linear Least Square (LLS) algorithm for Differential Time Difference Of Arrival (DTDOA). Second, fingerprinting is among the most successful approaches used for indoor localization and typically relies on the collection of measurements on signal strength over the area of interest. We propose an alternative by constructing fingerprints of fine-grained time information of the radio signal. We offer comprehensive analytical discussions on the feasibility of the approaches, which are backed up by evaluations in a software defined radio based IEEE 802.15.4 testbed. Our work contributes to research on localization with narrow-band signals. The results show that our proposed DTDOA-based LLS algorithm obviously improves the localization accuracy compared to traditional TDOA-based LLS algorithm but the accuracy is still limited because of the complex indoor environment. Furthermore, we show that time-based fingerprinting is a promising alternative to power-based fingerprinting.

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In this work, we provide a passive location monitoring system for IEEE 802.15.4 signal emitters. The system adopts software defined radio techniques to passively overhear IEEE 802.15.4 packets and to extract power information from baseband signals. In our system, we provide a new model based on the nonlinear regression for ranging. After obtaining distance information, a Weighted Centroid (WC) algorithm is adopted to locate users. In WC, each weight is inversely proportional to the nth power of propagation distance, and the degree n is obtained from some initial measurements. We evaluate our system in a 16m-18m area with complex indoor propagation conditions. We are able to achieve a median error of 2:1m with only 4 anchor nodes.

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Purpose. For accurate resection of nonpalpable malignant breast lesions with a tumor-free resection rim, an exact and stable wire localization is essential. We tested the resistance towards traction force of different localization devices used in our clinic for breast lesions in two types of tissue. Materials and Methods. Eight different commercially available hook-wire devices were examined for resistance towards traction force using an analogue spring scale. Results. Most systems showed a high level of movement already under small traction force. Retractable systems with round hooks such as the Bard DuaLok , the Fil d'Ariane, and the RPLN Breast Localization Device withstood less traction force than the other systems. However, the Bard DuaLok system was very resistant towards a small traction force of 50 g when compared to the other systems. The Ultrawire Breast Localization Device withstood the most traction force in softer tissue and Kopans Breast Lesion Localization Needle withstood the most force in harder tissue. Conclusion. The Ultrawire Breast Localization Device and Kopans Breast Lesion Localization Needle withstood the most traction force. In general retractable systems withstand less traction force than nonretractable systems.

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Low viscosity domains such as localized shear zones exert an important control on the geodynamics of the uppermost mantle. Grain size reduction and subsequent strain localization related to a switch from dislocation to diffusion creep is one mechanism to form low viscosity domains. To sustain strain localization, the grain size of mantle minerals needs to be kept small over geological timescales. One way to keep olivine grain sizes small is by pinning of mobile grain boundaries during grain growth by other minerals (second phases). Detailed microstructural studies based on natural samples from three shear zones formed at different geodynamic settings, allowed the derivation of the olivine grain-size dependence on the second-phase content. The polymineralic olivine grain-size evolution with increasing strain is similar in the three shear zones. If the second phases are to pin the mobile olivine grain boundary the phases need to be well mixed before grain growth. We suggest that melt-rock and metamorphic reactions are crucial for the initial phase mixing in mantle rocks. With ongoing deformation and increasing strain, grain boundary sliding combined with mass transfer processes and nucleation of grains promotes phase mixing resulting in fine-grained polymineralic mixtures that deform by diffusion creep. Strain localization due to the presence of volumetrically minor minerals in polymineralic mantle rocks is only important at high strain deformation (ultramylonites) at low temperatures (<~800°C). At smaller strain and stress conditions and/or higher temperatures other parameters like overall energy available to deform a given rock volume, the inheritance of mechanical anisotropies or the presence of water or melts needs to be considered to explain strain localization in the upper mantle.

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In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

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This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

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The endocannabinoid system (ECS) comprises the cannabinoid receptors CB1 and CB2 and their endogenous arachidonic acid-derived agonists 2-arachidonoyl glycerol and anandamide, which play important neuromodulatory roles. Recently, a novel class of negative allosteric CB1 receptor peptide ligands, hemopressin-like peptides derived from alpha hemoglobin, has been described, with yet unknown origin and function in the CNS. Using monoclonal antibodies we now identified the localization of RVD-hemopressin (pepcan-12) and N-terminally extended peptide endocannabinoids (pepcans) in the CNS and determined their neuronal origin. Immunohistochemical analyses in rodents revealed distinctive and specific staining in major groups of noradrenergic neurons, including the locus coeruleus (LC), A1, A5 and A7 neurons, which appear to be major sites of production/release in the CNS. No staining was detected in dopaminergic neurons. Peptidergic axons were seen throughout the brain (notably hippocampus and cerebral cortex) and spinal cord, indicative of anterograde axonal transport of pepcans. Intriguingly, the chromaffin cells in the adrenal medulla were also strongly stained for pepcans. We found specific co-expression of pepcans with galanin, both in the LC and adrenal gland. Using LC-MS/MS, pepcan-12 was only detected in non-perfused brain (∼40 pmol/g), suggesting that in the CNS it is secreted and present in extracellular compartments. In adrenal glands, significantly more pepcan-12 (400-700 pmol/g) was measured in both non-perfused and perfused tissue. Thus, chromaffin cells may be a major production site of pepcan-12 found in blood. These data uncover important areas of peptide endocannabinoid occurrence with exclusive noradrenergic immunohistochemical staining, opening new doors to investigate their potential physiological function in the ECS. This article is part of a Special Issue entitled 'Fluorescent Neuro-Ligands'.

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Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.