The United States of America, As Represented by the Secretary, Department of Health and Human Services

Other

Richard D Beger

Jon Gardner Wilkes

Dan Alexander Buzatu

Dwight Wayne Miller

Jerry Darsey

Ryan M Kretzer

Pierre Alusta

Tom Heinze

Alex Birls

Bruce Pearce

Jackson O Lay, Jr

Inessa Im

James P Freeman

A system and method for preprocessing magnetic resonance spectroscopy (MRS) data of brain tissue for pattern-based diagnostics is disclosed. The MRS preprocessing system includes an MRS preprocessing module that executes an operation that normalizes MRS spectrum data, recalibrates and scales the normalized MRS spectrum data, and then renormalizes the scaled MRS spectrum data. The resulting preprocessed MRS data is used to assist in identifying abnormalities in tissues shown in MRS scans.

System for magnetic resonance spectroscopy of brain tissue for pattern-based diagnostics

Structure-activity methods based on molecular descriptors that are a combination of structural information about the through-space and through-bond relationships between components of a molecule's structure and spectral data attributable to those components are disclosed. In some embodiments, a molecule is described by multiple sets of such descriptors to account for flexibility in the structure of the molecule. In a particularly disclosed embodiment, predictedC&#x2014;C COSY data andC&#x2014;C distance data are used as descriptors. Models of molecular properties may be established using the disclosed spectral data-activity methods and used to predict the properties of molecules.

Methods for predicting properties of molecules

The present invention provides a novel approach to cancer therapy and diagnostics that utilizes nanotubes and other similar nanostructures as both an indirect source of radiation therapy (BNCT), and as delivery vehicles for other types of radio- and chemo-therapeutic materials, as well as imaging agents for diagnostic purposes.

Nanotubes for cancer therapy and diagnostics

Methods are disclosed for establishing a quantitative relationship between spectral properties of molecules and a biological, chemical, or physical endpoint of the molecules. Spectral data including data from nuclear magnetic resonance, mass spectrometric, infrared, and ultraviolet-visible techniques are used along with endpoint data to train a pattern-recognition program. The training yields a spectral data-activity relationship that may be used to predict the endpoint value of a molecule from its spectral data alone. Methods for rapidly screening isolated compounds or mixtures of compounds based upon their spectral data are included.

Methods for predicting the biological, chemical, and physical properties of molecules from their spectral properties

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White Hall, AR, United States of America

Richard D Beger