Abstract: A method for the parallel identification of one or more metabolite species within a biological sample is provided. The method comprises producing a first spectrum by subjecting the sample to a nuclear magnetic resonance analysis, the first spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; producing a second spectrum by subjecting the sample to a mass spectrometry analysis, the spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting each of the individual spectral peaks to a statistical pattern recognition analysis to identify the one or more metabolite species contained within the sample; and identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the mass and nuclear magnetic resonance spectra.

Abstract: When a user sees a content item presented by a social networking system, the user may select an option to save the content item. The saved content item may be reinserted in a newsfeed presented to the user, integrated into collections, archived, used for notifications to the user, or otherwise subsequently presented to the user. A plug-in may be used to save content items accessed through websites external to the social networking system. As privacy settings associated with a saved content item are modified, the modified privacy settings are applied to the saved content item, which may prevent the user saving the content item from subsequently viewing the saved content item.

Abstract: The present invention relates to a pharmaceutical composition that provides long-term stability of a hydrolytically labile antipsychotic agent

Abstract: A method for differentiating complex biological samples, each sample having one or more metabolite species. The method comprises producing a mass spectrum by subjecting the sample to a mass spectrometry analysis, the mass spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting the individual spectral peaks of the mass spectrum to a statistical pattern recognition analysis; identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the mass spectrum; and assigning the sample into a defined sample class.

Abstract: A method and system for providing both an estimated true mean blood glucose value and estimated glycated hemoglobin (HbA1C) value from spot blood glucose (bG) measurements are disclosed. The bG measurements and associated context of the bG measurement are collected at daily times specified by a structured sampling schema, and the collected bG measurements are weighted based on the associated context. The estimated true mean bG value and the estimate HbA1C value are then determined from the weighted measurements of the collected bG measurements. A computer program for implementing the method for providing both an estimated true mean blood glucose value and estimated glycated hemoglobin (HbA1C) value from spot blood glucose (bG) measurements is also disclosed.

Abstract: A method for the parallel identification of one or more metabolite species within a biological sample is provided. The method comprises producing a first spectrum by subjecting the sample to a nuclear magnetic resonance analysis, the first spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; producing a second spectrum by subjecting the sample to a mass spectrometry analysis, the spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting each of the individual spectral peaks to a statistical pattern recognition analysis to identify the one or more metabolite species contained within the sample; and identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the mass and nuclear magnetic resonance spectra.

Abstract: A method for differentiating complex biological samples, each sample having one or more metabolite species. The method comprises producing a mass spectrum by subjecting the sample to a mass spectrometry analysis, the mass spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting the individual spectral peaks of the mass spectrum to a statistical pattern recognition analysis; identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the mass spectrum; and assigning the sample into a defined sample class.