G01N2333/5421

Diagnosis of sepsis

Methods for predicting the development of sepsis in a subject at risk for developing sepsis are provided. In one method, features in a biomarker profile of the subject are evaluated. The subject is likely to develop sepsis if these features satisfy a particular value set. Methods for predicting the development of a stage of sepsis in a subject at risk for developing a stage of sepsis are provided. In one method, a plurality of features in a biomarker profile of the subject is evaluated. The subject is likely to have the stage of sepsis if these feature values satisfy a particular value set. Methods of diagnosing sepsis in a subject are provided. In one such method, a plurality of features in a biomarker profile of the subject is evaluated. The subject is likely to develop sepsis when the plurality of features satisfies a particular value set.

MATERIALS AND METHODS FOR INFLAMMATORY MOLECULAR MARKERS
20230003719 · 2023-01-05 ·

A method of determining a pharmacodynamics or pharmacokinetic effect of an inhibitor of IL 1α comprising providing a sample from a subject; administering the inhibitor of IL 1α to the sample; measuring levels of one or more biomarkers in the sample; and determining the pharmacodynamic or the pharmacokinetic effect of the inhibitor of IL 1α based on the levels of the one or more biomarkers.

Lateral flow assay device
11519910 · 2022-12-06 · ·

The present invention provides a diagnostic kit for detecting the presence or quantity of one or more test analytes within a test sample taken from a body surface of a mammal, the diagnostic kit comprising: a separate insert for a lateral flow device (200, 411) comprising a membrane (201) fixed to a rigid support (202) and, the separate insert being configured to obtain the test sample; a lateral-flow assay device configured (300, 400) to accept the separate insert (200, 411); a securing member (210) configured to releasably attach (211) the separate insert to a body surface of a mammal (213); wherein the securing member (210) comprise an expandable layer (212) configured to apply pressure to the separate insert (200, 411) thereby pressing the separate insert (200, 411) against the body surface of the mammal (213).

TYPE 2 CYTOKINES AS PREDICTORS OF DISEASE SEVERITY AND/OR AS THERAPEUTIC TARGETS FOR COVID-19

Methods for treating coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, is described. The methods can be used to reduce the severity of outcomes related to COVID-19, such as hospitalization and ventilation. For example, treatment of a subject with a therapeutic agent that neutralizes interleukin 13 (IL-13) can result in reduced risk for mechanical ventilation in the subject. Also described are methods of predicting risk of mechanical ventilation in subjects with COVID-19.

COMPOSITIONS AND METHODS FOR REDUCING CYTOKINE EXPRESSION
20230019986 · 2023-01-19 ·

Provided herein are methods and compositions related to Prevotella bacteria for the reduction of IL-8, IL-6, IL-Iβ, and/C or TNFα expression and/or for the treatment of viral infections.

METHOD FOR EVALUATING SAFETY OF SUBSTANCE IN VITRO USING HUMAN IMMORTALIZED MYELOID CELLS
20220412958 · 2022-12-29 ·

[Problem]

To find a method having higher stability, reproducibility, economic efficiency, and operation easiness in an evaluation method of safety of a substance in vitro, by using human immortalized myeloid cells.

[Solving Means]

A method for evaluating the skin sensitizing property and/or the pyrogenic property of a test substance, a method for detecting a skin sensitizer and/or a pyrogen in a sample, and a method for evaluating the action of a sample on a function of immune cells, each using human immortalized myeloid cells and including measuring the production amount of IL-6 and/or IL-8 in a culture medium of human immortalized myeloid cells.

SYSTEM FOR DETECTING INFECTION IN SYNOVIAL FLUID

The invention provides methods and systems for detecting a biomarker in a synovial fluid wherein the system also includes a control to ensure that the test sample is indeed synovial fluid. The biomarkers and the control for synovial fluid can be identified using proteomic methods, including but not limited to antibody based methods, such as an enzyme-linked immunosorbant assay (ELISA), a radioimmunoassay (RIA), or a lateral flow immunoassay.

System for detecting infection in synovial fluid

The invention provides methods and systems for detecting a biomarker in a synovial fluid wherein the system also includes a control to ensure that the test sample is indeed synovial fluid. The biomarkers and the control for synovial fluid can be identified using proteomic methods, including but not limited to antibody based methods, such as an enzyme-linked immunosorbant assay (ELISA), a radioimmunoassay (RIA), or a lateral flow immunoassay.

Combination therapy with anti-IL-8 antibodies and anti-PD-1 antibodies for treating cancer

Provided herein are methods for the clinical treatment of tumors (e.g., advanced solid tumors) in patients having certain levels of serum IL-8 using an anti-IL-8 antibody in combination with an anti-PD-1 antibody.

BIOMARKERS FOR DETECTING OF OUTCOME/RISK OF THE PATIENTS WITH A RESPIRATORY ILLNESS

Methods and kits for screening, diagnosing, detecting or predicting a patient outcome/risk in a patient with a respiratory illness, the method comprising: a. obtaining a sample obtained from the patient; b. quantitatively measuring in the sample a polypeptide level of one or more biomarkers selected from: IL-6, CXCL8, IL-10, IL-IRA, IL-2, IL-4, IL-7, IL-9, IL-13, IL-17, IFN-g, IP-10, MCP-1, G-CSF, GM-CSF, FGF-basic, SCGF-β, GRO-α, MIP1-α, MIP1-β, CK-18, PDGF-bb, caspase 3, HMGB-1, TNF α, VEGF, sTNFR1 and sTREM1; and c. i) comparing the level of the one or more biomarkers in the sample with a control or cut-off level, wherein the differential level is indicative of patient outcome risk; or ii) using the polypeptide level of several of the biomarkers in combination, as inputs for an algebraic calculation or machine learning model of patient outcome risk.