Methods are described for measuring the amount of C peptide in a sample. More specifically, mass spectrometric methods are described for detecting and quantifying C peptide in a sample utilizing on-line extraction methods coupled with tandem mass spectrometric or high resolution/high accuracy mass spectrometric techniques.

The present disclosure describes a method of quantifying amounts of phosphopeptides using isotopically-enriched peptides as internal standards. A kit comprising at least one isotopically-enriched phosphorylated peptide can be used to quantify changes in amounts of phosphopeptides using parallel reaction monitoring mass spectrometry techniques. The invention can be used to indicate the pathologic mechanism, severity of the disease, and treatment response of a subject. The invention can also be used to identify subjects who require more aggressive therapeutic interventions or alternative treatments.

An integrated sample processing system including an analyzer and a mass spectrometer is disclosed. The integrated sample processing system can perform multiple different types of detection, thereby providing improved flexibility and better accuracy in processing samples. The detection systems in the sample processing system may include an optical detection system and a mass spectrometer.

The present invention provides a detection method for a monoclonal antibody in a sample, comprising: (a) a step of capturing the monoclonal antibody in the sample and immobilizing the monoclonal antibody in pores of a porous body; (b) a step of bringing the porous body in which the monoclonal antibody is immobilized with nanoparticles on which protease is immobilized to conduct selective protease digestion of the monoclonal antibody; (c) a step of detecting, by a liquid chromatography mass spectrometry (LC-MS), peptide fragments obtained by the selective protease digestion; and (a) a step of conducting a reduction reaction under an acidic condition after the step (a). By the present invention, further applicability of the detection method for the monoclonal antibodies using mass spectrometry is expected.

The present invention provides assays and assay systems for use in spatially encoded biological assays. The invention provides an assay system comprising an assay capable of high levels of multiplexing where reagents are provided to a biological sample in defined spatial patterns; instrumentation capable of controlled delivery of reagents according to the spatial patterns; and a decoding scheme providing a readout that is digital in nature.

A system and method for using new biomarkers to assess individual diseases is provided. In one embodiment of the present invention, absolute quantification of annotated metabolites by mass spectrometry is used to identify certain biomarkers and derivatives thereof (i.e., signatures), which are then used to screen for, diagnose, predict, prognose, and treat various diseases, including, but not limited to, breast cancer, ovarian cancer, colorectal cancer, pancreatic cancer, and acute graft-versus-host disease.

Particular disclosed embodiments disclosed herein concern using a one or more various mass tags, which can be specifically deposited at targets through direct or indirect enzymatic-catalyzed transformation, to provide a method for identifying targets in tissue samples. The mass tags may be labeled with stable isotopes to produce mass tags having the same chemical structure but different masses. Mass codes produced by ionizing the mass tags are detected and/or quantified using mass spectrometry. The method can be used for multiplexed detection of multiple targets in a particular sample. In some embodiments, a map divided into sections representing sections of the tissue sample may be prepared, with the map sections including data corresponding to quantification data wherein the size of a mass peak is determined and correlated with the amount of a target for the corresponding tissue sample section.

The present invention relates to methods and products associated with in vivo enzyme profiling. In particular, the invention relates to methods of in vivo processing of exogenous molecules followed by detection of signature molecules as representative of the presence of active enzymes associated with diseases or conditions. The invention also relates to products, kits, and databases for use in the methods of the invention.

The present disclosure provides systems, media, and methods for applying machine learning to determine the biological age of a sample. A method of using a biological age predictor may comprise: (a) providing data of a sample to the biological age predictor; (b) treating the sample with a substance, thereby generating a treated sample; and (c) providing data of the treated sample to the biological age predictor. The biological age predictor may generate the first biological age and/or the second biological age.

Provided herein are in situ generated conformationally constrained peptide arrays, methods for synthesizing such arrays, and methods, systems and assays comprising the use of the synthesized constrained peptide arrays for characterizing protein-target Interactions including: antibody-target interactions, receptor agonist interactions, receptor antagonist interactions, enzyme substrate interactions, enzyme inhibitor interactions, and other protein-protein interactions.