Described is an assay for diagnosing an infection such as peritonitis in a subject. The assay includes a binding molecule, such as an antibody that specifically binds to an inflammatory marker in a sample from the subject, and a second binding molecule that binds to a marker indicative of a pathogen in the sample. For diagnosing peritonitis in a subject, the pathogen will be at least one bacterium and/or fungus. Typically, the assay will be incorporated into a lateral flow device and may include a binding molecule that specifically binds to an antigen indicative of the presence of a specific pathogen species. The described assay(s) may further include filter(s), enriching antigen(s), and buffer(s). Also described are methods of diagnosing and treating peritonitis in a subject who is a peritoneal dialysis patient that include utilizing the herein described assay(s) or assay kit(s) to analyze the subject's peritoneal dialysis effluent.

Methods and kits for screening, diagnosing, detecting or predicting a patient outcome/risk variable for a lung transplant recipient after transplant or an EVLP outcome by measuring biomarker levels of one or more biomarkers selected from IL-6, IL-8, sTNFR1 and sTREM-1 in EVLP perfusate are described. The methods involve for example, i. obtaining one or more test EVLP perfusate samples of a donor lung; ii. determining in one or more test EVLP perfusate sample of a donor lung, a polypeptide level of one or more biomarkers selected from IL-8, IL-6, sTNFR1 and sTREM-1; and iii. a) comparing the polypeptide level of the one or more biomarkers in the perfusate sample with a control or cut-off level, wherein the differential level is indicative of outcome/risk of after transplant or of an EVLP outcome; or b) using the polypeptide level of one or several of the one or more biomarkers in combination, as part of an algebraic calculation of outcome/risk.

In some aspects, the present invention provides methods for predicting whether a subject will develop autoantibodies to an anti-TNF drug during the course of anti-TNF drug therapy. In other aspects, the present invention provides methods for predicting the level of an anti-TNF drug in a subject during the course of anti-TNF drug therapy. Systems for predicting anti-TNF drug levels and the likelihood of autoantibody formation during the course of anti-TNF drug therapy are also provided herein. The present invention further provides methods for predicting a clinical outcome (e.g., endoscopic response) of a subject on anti-TNF drug therapy.

The present invention concerns the use of interleukin-8 (IL-8) as a biomarker for predicting the outcome of the treatment with aflibercept, or ziv-aflibercept of a patient suspected to suffer from a cancer.

The present invention relates to a method for identifying inhibitors of breast cancer metastasis based on a screening with proteins that are specific for the secretome of a chondrocyte, preferably cytokines and/or chemokines. The ligands as identified lead to a decrease of the migration and/or a re-differentiation of a breast cancer cell and/or a reduction of the number and/or size of breast cancer metastases. The present invention further relates to a method for detecting breast cancer metastasis, comprising the step of detecting at least one protein that is specific for the secretome of a chondrocyte, and for methods for treating and/or preventing breast cancer metastasis in a patient in need thereof, comprising the step of administering an effective amount of at least one ligand for one protein that is specific for the secretome of a chondrocyte to said patient in need thereof.

The invention provides methods and compositions for treating attention-deficit/hyperactivity disorder (ADHD) in an individual. The methods provided herein entail administering a composition comprising an isolated Mycobacterium or antigenic fragments derived therefrom. Also provided herein are methods for assessing alleviation of symptoms and/or alteration of immune system functioning following administration of a composition comprising an isolated Mycobacterium or antigenic fragments derived therefrom.

In some aspects, the present invention provides methods for predicting whether a subject will develop autoantibodies to an anti-TNF drug during the course of anti-TNF drug therapy. In other aspects, the present invention provides methods for predicting the level of an anti-TNF drug in a subject during the course of anti-TNF drug therapy. Systems for predicting anti-TNF drug levels and the likelihood of autoantibody formation during the course of anti-TNF drug therapy are also provided herein. The present invention further provides methods for predicting a clinical outcome (e.g., endoscopic response) of a subject on anti-TNF drug therapy.

Methods of treating IBD in a subject using an anti-SMAD7 therapy, such as a SMAD7 antisense oligonucleotide, to reduce CCL20, IL8, or TNF levels are disclosed. Methods of treating and managing IBD in a subject using an anti-SMAD7 therapy, such as a SMAD7 antisense oligonucleotide, based on CCL20, IL8, or TNF levels are also disclosed. Also disclosed are methods of determining whether a subject with IBD is responsive or likely to be responsive to treatment an anti-SMAD7 therapy. Reduction of CCL20, IL8, or TNF levels may correlated with IBD remission or decreases in CDAI score.

This disclosure provides kits and methods for detecting markers in a sample from a subject with unknown status and generating a risk assessment of the presence or absence of cancer, such as colorectal cancer. In embodiments, a kit comprises at least four reagents, each specifically binding to one of at least four polypeptides in a sample from the subject. The polypeptides include GDF15, keratin 1-10, and two or more of hepsin, IL-8, CEA, L1CAM, MCP-1, and OPG. The kit further includes at least one standard comprising a known amount of at least one of the polypeptides. The kit can also include computer readable media comprising instructions to analyze the detected amounts of the at least four polypeptides using a machine learning algorithm to determine whether a subject has an increased risk of the presence of colorectal cancer.

The present disclosure relates to the biological markers Ferritin and IL-8 that are predictive for patient response to treatment with a vascular disrupting agent. In particular, the present disclosure relates to biological markers predictive for cancer patient response to treatment with a vascular disrupting agent, as well as methods of treating a cancer patient with a vascular disrupting agent.