Abstract: Composition of non-radioactive traceable metal isotope-enriched nanoparticles, and methods of their use for determining in-vivo biodistribution are provided. The methods comprise the steps of: (a) introducing the nanoparticles into the biological material, wherein the nanoparticles comprise at least one inorganic core, and the inorganic core comprises at least two metal isotopes in a predetermined ratio; wherein at least one metal isotope is enriched non-radioactive traceable metal isotope and (b) determining the distribution of the nanoparticles in the biological material based on the predetermined ratio of the metal isotopes.

Abstract: The present invention is generally directed to core/shell nanoparticles, wherein such core/shell nanoparticles comprise a nanoparticle core and a nanoshell disposed about the nanoparticle core such that, in the aggregate, they form a core/shell nanoparticle that is operable for use as an imaging agent in X-ray/computed tomography (CT). Typically, such core/shell nanoparticle-based X-ray CT imaging agents further comprise a targeting species for targeting the imaging agent to diseased sites. Included herein are methods for forming such agents, comprising forming an ensemble of core/shell nanoparticles, wherein the mean diameter of the ensemble of core/shell nanoparticles is selected so as to render the nanoparticles in the ensemble substantially clearable by a mammalian kidney.

Abstract: The present technique provides for the analysis of a data series to identify sequences of interest within the series. Specifically, in accordance with one embodiment of the present technique, a method is provided comprising generating a data structure that stores characteristics about a plurality of sequences present in a data series. One or more sequences are identified based upon the contents of the data structure. In accordance with other aspects of the invention, more than one heuristic is calculated for each sequence under review. The plurality of heuristics associated with each sequence are evaluated to identify a sequence of interest.

Abstract: The present technique provides for the analysis of a data series to identify sequences of interest within the series. The analysis may be used to iteratively update a grammar used to analyze the data series or updated versions of the data series. Furthermore, the technique provides for the calculation of a minimum description length heuristic, such as a symbol compression ratio, for each sub-sequence of the analyzed data sequence. The technique may then compare a selected heuristic value against one or more reference conditions to determine if additional iteration is to be performed. The grammar and the data sequence may be updated between iterations to include a symbol representing a string corresponding to the selected heuristic value based upon a non-termination result of the comparison. Alternatively, the string corresponding to the selected heuristic value may be identified as a sequence of interest based upon a termination result of the comparison.