52 resultados para Compact Hermitian Component
Resumo:
In excisional body-contouring surgery the surgeon is often confronted with time-consuming closure of long wounds. Recently, a new combination of a self-adhering mesh together with a liquid 2-octyl cyanoacrylate adhesive (Prineo™; Ethicon, Inc., Somerville, NJ, USA) has been introduced to replace intracutaneous running suture.
Resumo:
The study describes brain areas involved in medial temporal lobe (mTL) seizures of 12 patients. All patients showed so-called oro-alimentary behavior within the first 20 s of clinical seizure manifestation characteristic of mTL seizures. Single photon emission computed tomography (SPECT) images of regional cerebral blood flow (rCBF) were acquired from the patients in ictal and interictal phases and from normal volunteers. Image analysis employed categorical comparisons with statistical parametric mapping and principal component analysis (PCA) to assess functional connectivity. PCA supplemented the findings of the categorical analysis by decomposing the covariance matrix containing images of patients and healthy subjects into distinct component images of independent variance, including areas not identified by the categorical analysis. Two principal components (PCs) discriminated the subject groups: patients with right or left mTL seizures and normal volunteers, indicating distinct neuronal networks implicated by the seizure. Both PCs were correlated with seizure duration, one positively and the other negatively, confirming their physiological significance. The independence of the two PCs yielded a clear clustering of subject groups. The local pattern within the temporal lobe describes critical relay nodes which are the counterpart of oro-alimentary behavior: (1) right mesial temporal zone and ipsilateral anterior insula in right mTL seizures, and (2) temporal poles on both sides that are densely interconnected by the anterior commissure. Regions remote from the temporal lobe may be related to seizure propagation and include positively and negatively loaded areas. These patterns, the covarying areas of the temporal pole and occipito-basal visual association cortices, for example, are related to known anatomic paths.
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The purpose of this study was to determine whether changes in glenoid version are associated with humeral head displacement and changes in the joint reaction forces, as these might contribute to instability or loosening in total shoulder replacement. A total shoulder prosthesis was implanted in neutral version in 6 cadaveric shoulders. Glenoid version was then changed in steps of 4 degrees toward more anteversion and retroversion. An increase in anteversion resulted in anterior translation of the humeral head and in eccentric loading of the anterior part of the glenoid. Retroversion was associated with posterior displacement and posterior loading of the glenoid. A change in rotation of the humeral component did not compensate for altered version of the glenoid component. These results suggest that both instability and glenoid component loosening may be related to the version of the glenoid component. Therefore, assessment of loosening and instability justifies precise assessment of glenoid component version.
Resumo:
Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.
Resumo:
CONCLUSIONS: Speech understanding is better with the Baha Divino than with the Baha Compact in competing noise from the rear. No difference was found for speech understanding in quiet. Subjectively, overall sound quality and speech understanding were rated better for the Baha Divino. OBJECTIVES: To compare speech understanding in quiet and in noise and subjective ratings for two different bone-anchored hearing aids: the recently developed Baha Divino and the Baha Compact. PATIENTS AND METHODS: Seven adults with bilateral conductive or mixed hearing losses who were users of a bone-anchored hearing aid were tested with the Baha Compact in quiet and in noise. Tests were repeated after 3 months of use with the Baha Divino. RESULTS: There was no significant difference between the two types of Baha for speech understanding in quiet when tested with German numbers and monosyllabic words at presentation levels between 50 and 80 dB. For speech understanding in noise, an advantage of 2.3 dB for the Baha Divino vs the Baha Compact was found, if noise was emitted from a loudspeaker to the rear of the listener and the directional microphone noise reduction system was activated. Subjectively, the Baha Divino was rated statistically significantly better in terms of overall sound quality.
Resumo:
Combined EEG/fMRI recordings offer a promising opportunity to detect brain areas with altered BOLD signal during interictal epileptic discharges (IEDs). These areas are likely to represent the irritative zone, which is itself a reflection of the epileptogenic zone. This paper reports on the imaging findings using independent component analysis (ICA) to continuously quantify epileptiform activity in simultaneously acquired EEG and fMRI. Using ICA derived factors coding for the epileptic activity takes into account that epileptic activity is continuously fluctuating with each spike differing in amplitude, duration and maybe topography, including subthreshold epileptic activity besides clear IEDs and may thus increase the sensitivity and statistical power of combined EEG/fMRI in epilepsy. Twenty patients with different types of focal and generalized epilepsy syndromes were investigated. ICA separated epileptiform activity from normal physiological brain activity and artifacts. In 16/20 patients, BOLD correlates of epileptic activity matched the EEG sources, the clinical semiology, and, if present, the structural lesions. In clinically equivocal cases, the BOLD correlates aided to attribute proper diagnosis of the underlying epilepsy syndrome. Furthermore, in one patient with temporal lobe epilepsy, BOLD correlates of rhythmic delta activity could be employed to delineate the affected hippocampus. Compared to BOLD correlates of manually identified IEDs, the sensitivity was improved from 50% (10/20) to 80%. The ICA EEG/fMRI approach is a safe, non-invasive and easily applicable technique, which can be used to identify regions with altered hemodynamic effects related to IEDs as well as intermittent rhythmic discharges in different types of epilepsy.
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Patients with dyskeratosis congenita (DC), a heterogeneous inherited bone marrow failure syndrome, have abnormalities in telomere biology, including very short telomeres and germline mutations in DKC1, TERC, TERT, or NOP10, but approximately 60% of DC patients lack an identifiable mutation. With the very short telomere phenotype and a highly penetrant, rare disease model, a linkage scan was performed on a family with autosomal-dominant DC and no mutations in DKCI, TERC, or TERT. Evidence favoring linkage was found at 2p24 and 14q11.2, and this led to the identification of TINF2 (14q11.2) mutations, K280E, in the proband and her five affected relatives and TINF2 R282H in three additional unrelated DC probands, including one with Revesz syndrome; a fifth DC proband had a R282S mutation. TINF2 mutations were not present in unaffected relatives, DC probands with mutations in DKC1, TERC, or TERT or 298 control subjects. We demonstrate that a fifth gene, TINF2, is mutated in classical DC and, for the first time, in Revesz syndrome. This represents the first shelterin complex mutation linked to human disease and confirms the role of very short telomeres as a diagnostic test for DC.
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The problem of re-sampling spatially distributed data organized into regular or irregular grids to finer or coarser resolution is a common task in data processing. This procedure is known as 'gridding' or 're-binning'. Depending on the quantity the data represents, the gridding-algorithm has to meet different requirements. For example, histogrammed physical quantities such as mass or energy have to be re-binned in order to conserve the overall integral. Moreover, if the quantity is positive definite, negative sampling values should be avoided. The gridding process requires a re-distribution of the original data set to a user-requested grid according to a distribution function. The distribution function can be determined on the basis of the given data by interpolation methods. In general, accurate interpolation with respect to multiple boundary conditions of heavily fluctuating data requires polynomial interpolation functions of second or even higher order. However, this may result in unrealistic deviations (overshoots or undershoots) of the interpolation function from the data. Accordingly, the re-sampled data may overestimate or underestimate the given data by a significant amount. The gridding-algorithm presented in this work was developed in order to overcome these problems. Instead of a straightforward interpolation of the given data using high-order polynomials, a parametrized Hermitian interpolation curve was used to approximate the integrated data set. A single parameter is determined by which the user can control the behavior of the interpolation function, i.e. the amount of overshoot and undershoot. Furthermore, it is shown how the algorithm can be extended to multidimensional grids. The algorithm was compared to commonly used gridding-algorithms using linear and cubic interpolation functions. It is shown that such interpolation functions may overestimate or underestimate the source data by about 10-20%, while the new algorithm can be tuned to significantly reduce these interpolation errors. The accuracy of the new algorithm was tested on a series of x-ray CT-images (head and neck, lung, pelvis). The new algorithm significantly improves the accuracy of the sampled images in terms of the mean square error and a quality index introduced by Wang and Bovik (2002 IEEE Signal Process. Lett. 9 81-4).