Traditional methods of detecting blood-borne microbial species in patients suspected of sepsis can be relatively slow, lack sensitivity, and require large volumes of blood. The present invention relates to methods of detecting microbial species in platelet rich plasma, which can be done more rapidly, with greater sensitivity, and with smaller volumes of blood to ensure more prompt and reliable diagnosis and treatment. The present invention also relates to improved methods of antibiotic treatment for patients diagnosed with a microbial infection and improved methods of excluding the diagnosis of viral infection exhibiting symptoms similar to sepsis.

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 invention relates to non-invasive methods for the diagnosis and prognosis of pancreatic cancer. In some embodiments, such methods and compositions relate to particular pancreatic cancer biomarkers and combinations thereof.

Microarray compositions suitable for analysis by one or several spectrographic methods are disclosed. In an embodiment, a microarray composition includes a three-dimensional solid support and a plurality of reactive microbeads positioned on the solid support in spatially distinct and addressable locations.

The present invention relates to peptides, proteins, nucleic acids and cells for use in immunotherapeutic methods. In particular, the present invention relates to the immunotherapy of cancer. The present invention furthermore relates to tumor-associated T-cell peptide epitopes, alone or in combination with other tumor-associated peptides that can for example serve as active pharmaceutical ingredients of vaccine compositions that stimulate anti-tumor immune responses, or to stimulate T cells ex vivo and transfer into patients. Peptides bound to molecules of the major histocompatibility complex (MHC), or peptides as such, can also be targets of antibodies, soluble T-cell receptors, and other binding molecules.

Provided herein are methods and systems for proteome analysis that are at least partially automated and/or performed robotically. In some aspects, the methods and systems described herein can rapidly and efficiently provide protein identification of each of the proteins from a proteome, or a complement of proteins, obtained from extremely small amounts of biological samples. The identified proteins can be imaged quantitatively over a spatial region. Automation and robotics facilitates the throughput of the methods and systems, which enables protein imaging and/or rapid proteome analysis.

The present invention generally provides, in various embodiments, methods of analyzing samples having a low abundance of proteins, e.g., single cells, utilizing liquid chromatography and tandem mass spectroscopy (LC-MS/MS).

The method for aiding ALS detection provided by the present invention includes determining a profile of signal peptides contained in a bodily fluid from a test subject, and comparing the signal peptide profile thus determined for the test subject with a previously-determined profile of signal peptides in a bodily fluid from a healthy subject. The presence of a difference between the signal peptide profile of the test subject and the signal peptide profile of the healthy subject at a specific molecular weight is then associated with the test subject's suffering from or developing ALS.

This document relates to methods for detecting and quantifying heavy and light chains of immunoglobulin using mass spectrometry techniques.

The present disclosure relates to methods of identifying components present in intact lipoprotein particles. Methods provided include single particle mass spectrometry, such as charge detection mass spectrometry (CDMS). Distinct subtypes and subpopulations that exist within lipoprotein density classes are determined based on simultaneously measured m/z and charge of ionized lipoprotein particles.