49 resultados para decomposition rank


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OBJECTIVE: To determine if the receptor activator of nuclear factor-kappaB-receptor activator of nuclear factor-kappaB ligand-osteoprotegerin (RANK-RANKL-OPG) system is active in bone remodeling in dogs and, if so, whether differences in expression of these mediators occur in healthy and arthritic joints. STUDY DESIGN: Experimental study. SAMPLE POPULATION: Fragmented processus coronoidei (n=20) were surgically removed from dogs with elbow arthritis and 5 corresponding healthy samples from dogs euthanatized for reasons other than elbow joint disease. METHODS: Bright-field immunohistochemistry and high-resolution fluorescence microscopy were used to investigate the distribution of RANK, RANKL, and OPG in healthy and arthritic joints. RESULTS: All 3 molecules were identified by immunostaining of canine bone tissue. In elbow dysplasia, the number of RANK-positive osteoclasts was increased. In their vicinity, cells expressing RANKL, a mediator of osteoclast activation, were abundant whereas the number of osteoblasts having the potential to limit osteoclastogenesis and bone resorption via OPG was few. CONCLUSIONS: The RANK-RANKL-OPG system is active in bone remodeling in dogs. In elbow dysplasia, a surplus of molecules promoting osteoclastogenesis was evident and is indicative of an imbalance between the mediators regulating bone resorption and bone formation. Both OPG and neutralizing antibodies against RANKL have the potential to counterbalance bone resorption. CLINICAL RELEVANCE: Therapeutic use of neutralizing antibodies against RANKL to inhibit osteoclast activation warrants further investigation.

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In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

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A number of hydrological, botanical, macro- and micro-climatological processes are involved in the formation of patterned peatlands. La Grande Tsa at 2336 m a.s.l. is probably the highest bog in the central Swiss Alps and is unique in its pattern. In two of five pools there is in the contact zone between the basal peat and the overlying gyttja an unconformity in the depth-age models based on radiocarbon dates. Palynostratigraphies of cores from a ridge and a pool confirm the occurrence of an unconformity in the contact zone. We conclude that deepening of the pools results from decomposition of peat. The fact that the dated unconformities in the two pools and the unconformity in the ridge-core all fall within the Bronze Age suggest they were caused by events external to the bog. We hypothesize that early transhumance resulted in anthropogenic lowering of the timberline, which resulted in a reduction in the leaf-area index and evapotranspiration, and in higher water levels and thus pool formation.

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Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.