Amy J.
Amy J. Docktor, Louisville, CO US
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20130047887 | NOVEL MULTIFUNCTIONAL MOLECULES FOR DENTAL BONDING APPLICATIONS HAVING IMPROVED ADHESION - The present invention describes dental adhesive compositions used for bonding dental biomaterials to hard tissue comprising a polymerizable blend of one or more newly synthesized low shrinkage, stable, multifunctional compounds, where the compounds are acidic-methacrylate derivatives, having excellent properties of bonding the hard tooth substance (enamel or dentin) to dental restorative materials, and present high quality marginal sealing between the tooth and the material thus bond and improved storage stability | 02-28-2013 |
Amy J. Docktor, Boulder, CO US
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20100307378 | CARBAMATE-METHACRYLATE MONOMERS AND THEIR USE IN DENTAL APPLICATIONS - The present invention relates, generally, to monomers containing carbamate-methacrylates or derivatives of carbamate-methacrylates, processes for making the monomers, and compositions comprising the monomers. The present invention also relates to methods of using the monomers, such as in dental applications, and in particular, dental restorative resins. | 12-09-2010 |
Amy J. Drauch, Carnegie, PA US
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20080273199 | Spectroscopic system and method for predicting outcome of disease - A system and method to predict the progression of disease of a test sample. A group of known biological samples is provided. Each known biological sample has an associated known outcome including a non-diseased sample or a diseased sample. A Raman data set is obtained for each known biological sample. Each Raman data set is analyzed to identify a diseased or non-diseased reference Raman data set depending on whether respective biological sample is the non-diseased sample or the diseased sample. A first database is generated where the first database contains reference Raman data sets for all diseased samples. A second database is generated where the second database contains reference Raman data sets for all non-diseased samples. A test Raman data set of a test biological sample is received, where the test biological sample has an unknown disease status. A diagnostic is provided as to whether the test sample is a non-diseased sample or a diseased sample. The diagnostic is obtained by comparing the test Raman data set against the reference Raman data sets in the first and the second databases using a chemometric technique. A prediction of the progression of disease may be then provided. | 11-06-2008 |
Amy J. Johnson, Columbus, OH US
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20140005250 | Compositions and Methods for Increasing Drug Efficacy in Cancer | 01-02-2014 |
Amy J. Midgal, Cupertino, CA US
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20110279473 | TRANSLATION OF REGISTER-COMBINER STATE INTO SHADER MICROCODE - An apparatus and method for translating fixed function state into a shader program. Fixed function state is received and stored and when a new shader program is detected the fixed function state is translated into shader program instructions. Registers specified by the program instructions are allocated for processing in the shader program. The registers may be remapped for more efficient use of the register storage space. | 11-17-2011 |
Amy J. Pressey, Garden Grove, CA US
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20130206797 | Storage Aid for Boots - A storage aid for boots includes a pair of substantially rigid elongated tines secured to a common spacer at one end to support the tines in a spaced generally parallel arrangement. The storage aid is inserted into the leg sheath portions as well as ankle and shoe portions of a host boot pair. The cooperating gently captivity of the boot portions within the tine space is maintained to secure the boots in an extended upward configuration and avoid flopping of the leg sheath portions of the boots during storage. | 08-15-2013 |
Amy J. Sehnert, San Francisco, CA US
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20110184712 | PREDICTIVE MODELS AND METHODS FOR DIAGNOSING AND ASSESSING CORONARY ARTERY DISEASE - Biomarkers useful for diagnosing and assessing the extent of coronary artery disease (CAD) are provided, along with kits for measuring their expression. The invention also provides predictive models, based on the biomarkers, as well as computer systems, and software embodiments of the models for scoring and optionally classifying samples. In a preferred embodiment, the biomarkers are organized into clustered groups. The expression level of the biomarkers within a group are highly correlated to each other in normal and disease states. Expression values of genes chosen from each of two, three, four or five of the clustered gene groups, A, B, C, D, E may be used. Alternatively, expression values of genes chosen from the groups are combined into a metagene. Preferred biomarkers include S100A12, S100A8, S100A9, BCL2A1, and F5 (group A); XK, P62, and FECH (group B); TUBB2 (group C); IFNG, PDGFB, VSIG4, and TNF (group D); CSF3R, TLR5, CD46, and NCF1 (group E); S100A12, S100A9, BCL2A1, TXN and CSTA (group I); OLIG1, OLIG2, ADORA3, CLC, and SLC29A1 (group II); and CBS and ARG1 (group IV). | 07-28-2011 |