The disclosure provides for mass spectrometry (MS)-cleavable heterobifunctional photoactivated cross-linkers. The MS-cleavable heterobifunctional photoactivated cross-linkers can be used in mass spectrometry to facilitate structural analysis of intra-protein interactions in proteins and inter-protein interactions in protein complexes.

Disclosed are compositions and methods for performing a proteomic analysis. Particularly disclosed are compositions and methods for preparing a sample for quantitative single-cell proteomics.

The present invention relates to improvements in female health monitoring and treatment wherein menstrual blood samples are analyzed for biomarkers of interests to monitor the health status and treatment of a female patient.

This disclosure relates to the identification of interactions between ligands and in-membrane proteins using nuclear magnetic resonance spectroscopy. Also provided are methods for high-throughput identification of in-membrane ligand-membrane protein interactions.

Compositions and methods for detection of protein interaction with a target biomolecule are provided. Compositions can include biomolecule sensors having at least a genetically modified ubiquitin peptide; an ADP-Ribosyltransferase (ART) peptide domain of a SidE-ligase protein or a homolog thereof; and a phosphodiesterase (PDE) domain of a SidE-ligase protein or a homolog thereof.

Methods are provided for detecting insulin-like growth factor-I (IGF-I) variant(s) in a sample. Methods provided herein are further directed to using the detected ion or ions to determine the presence of IGF1 variant(s) in the sample.

Objects of the disclosure are to provide a preanalysis treatment method for a sample, which can reduce mixing of a reagent into the sample, and to provide a sample pretreatment system capable of performing the preanalysis treatment method. An aspect of the present embodiment is a preanalysis treatment method for a sample, which includes a step A of mixing the sample and a reagent A containing a support and a reducing agent immobilized on the support, a step B of mixing the sample and a reagent B containing a support and an enzyme immobilized on the support, a step X-A of, after the step A, separating the reagent A and a supernatant from each other, and a step X-B of, after the step B, separating the reagent B and a supernatant from each other.

Disclosed herein are compositions, systems, and methods for identifying neurological diseases from biological sample analysis. A biological sample from a subject may be contacted to a particle to form a biomolecule corona, which may contain a subset of biomolecules from the biological sample and which can have utility for diagnosing a neurological disease state. Further disclosed herein are machine learning algorithms and trained classifiers for distinguishing neurological disease states based on biological data.

The present invention describes a test kit for the detection of fat-soluble vitamins in serum using a method based on high performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). The internal standard (IS) solution included in the kit is based on methanol, acetonitrile and isopropyl alcohol solvents. Ammonium acetate is added to the IS solution to make it more stable and last for longer storage time. The application of this kit can significantly improve the recovery and detection sensitivity of vitamins A, E, K1 and K2 in serum without additional sample enrichment, make sample preparation process simpler and more efficient, keep processed samples stable for longer time, and lower the overall cost for more accurate and repeatable test results.

The present disclosure provides a system comprising a communication interface and computer for assigning a label to the biomolecule fingerprint, wherein the label corresponds to a biological state. The present disclosure also provides a sensor arrays for detecting biomolecules and methods of use. In some embodiments, the sensor arrays are capable of determining a disease state in a subject.