Methods and system for identifying and/or quantifying a protein are provided herein.

Aspects of the present application relate to techniques of diagnosing whether a pathogen (e.g., SARS-CoV-2) is present in a subject using infrared (IR) spectroscopy and machine learning techniques. The techniques use spectral data obtained from performing IR spectroscopy on a biological sample (e.g., saliva or nasal sample, or genetic material extracted therefrom) to generate a set of feature values. The feature values are provided as input to a machine learning model to obtain output indicating whether the pathogen is present in the biological sample. The output of the machine learning model may be used to determine a diagnosis result for a subject.

The present disclosure describes a method of identifying serine hydrolase in a biological test sample obtained from protein production with a fluorophosphonate-containing probe. The present disclosure also provides a method of identifying one or more serine hydrolases in the biological test sample as causing PS-80 or PS-20 degradation.

The present invention refers to a method for determining peptide fragments of glycated hemoglobin A (HbA1c) molecules by mass spectrometry (MS), a reagent kit, and a clinical diagnostic system adapted for performing the method.

A method of quantifying a target compound includes applying an oxidation/reduction potential to an electrochemical cell (14); measuring an electrochemical current during the application of the oxidation/reduction potential; and ionizing and directing the target compound before and after the application of the oxidation/reduction potential to a mass spectrometer (16) that measures a target compound ion intensity. The method further includes determining a target compound ion intensity change due to the application of the oxidation/reduction potential and determining a total amount of the target compound in the sample using the measured electrochemical current and the target compound ion intensity change. Determining the target compound ion intensity change may comprise either comparing the target compound ion intensity before and after the electrolysis relative to a reference peak or comparing the integrated peak area of a target compound ion in an extracted ion chromatogram before and after the electrolysis.

Methods disclosed herein include an improved technique for comparing a glycosylation profile of a first protein (e.g., an innovator protein drug) with a glycosylation profile of a second protein (e.g., a corresponding biogeneric/biosimilar). For example, a method of manufacture can include providing or obtaining a batch of a test glycoprotein drug substance, using mass spectrometry to acquire a test oxonium ion profile from a sample of the test glycoprotein drug substance batch, comparing the test oxonium ion profile to a corresponding target oxonium ion profile of a target glycoprotein drug product, and processing the batch of the test glycoprotein drug substance as a drug product if the difference between the test oxonium ion profile and the corresponding target oxonium ion profile is tolerable, or taking an alternative action if the difference between the test oxonium ion profile and the target oxonium ion profile is not tolerable.

The present invention refers to a method for determining intact glycated hemoglobin A (HbA1c) by mass spectrometry (MS), a kit and a diagnostic system adapted for performing the method.

The invention generally relates to mass spectrometry via frequency tagging.

Disclosed is a method for high-throughput screening of non-target biomarkers based on metabolic disturbance caused by pollutants, belonging to the field of environmental exposure and health. The method includes the following steps: (1) extracting to obtain extracts to be tested; (2) performing chromatographic analysis to obtain a spectrum containing chromatographic peaks; (3) identifying and labeling features of pollutants, taking chromatographic peaks other than the features of the pollutants as features of potential metabolites, and performing non-target labeling of the features of the potential metabolites; (4) establishing a linear regression model by taking the peak areas of the features of the potential metabolites as dependent variables and the peak areas of the features of the pollutants as independent variables; (5) operating the model, and performing non-target screening of the biomarkers to preliminarily obtain related biomarkers; (6) identifying the MS spectra and MS/MS spectra of the preliminarily obtained biomarkers, and identifying biomarkers related to pollutant exposure. The method of the present invention obviously improves the accuracy of biomarker screening, and improves the throughput of biomarker screening.

A method for determining a quantity of an analyte in a liquid sample, comprises: adding a known quantity of an internal standard comprising an isotopically labeled version of the analyte to the sample; (b) providing a continuous stream of the sample having the internal standard to an inlet of a Liquid Chromatography Mass Spectrometry (LCMS) system; and repeatedly performing the steps of: performing a data-independent analysis of the precursor ion species using a mass analyzer, whereby mass spectra of a plurality of fragment-ion species are acquired; calculating one or more degree-of-matching scores that relate to either a number of ions of the internal standard that overlap between results of the data-independent analysis and tabulated mass spectral data of the internal standard; and performing quantitative tandem mass spectrometric analyses of the internal standard and the analyte if each of the degree-of-matching scores meets a respective degree-of-matching condition.