Abstract: The present invention provides a method for predicting whether a patient having, suspected of having, or at risk of developing an inflammatory condition will respond to treatment with a disease-modifying antirheumatic drug (DMARD) comprising measuring the level of at least one specialized pro-resolving mediator (SPM) in a DMARD naïve patient sample and classifying the patient as a predicted DMARD responder or a predicted DMARD non-responder. The present invention also provides a method of assessing the efficacy of a disease-modifying antirheumatic drug (DMARD) for use in the treatment of an inflammatory condition in a patient. The present invention also provides a method of predicting which rheumatoid arthritis pathotype a patient having, suspected of having, or at risk of developing rheumatoid arthritis will develop.

Abstract: The present invention relates to biomarkers and biomarker panels useful in the prognosis and diagnosis of cancers, in particular epithelial cancers. The present invention also provides methods of treatment of patients diagnosed or having undergone diagnosis or prognosis using the biomarkers and biomarker panels of the invention. Kits for the analysis of the biomarkers and biomarker panels are also provided. The biomarker panel consists of COL11A1, CTS, ANXA6, LGALS3, ANXA1, AB13BP, COMP, COL1A1, LAMB1, CTSG, LAMA4, TNXB, FN1, AGT, FBLN2, HSPG2, COL6A6, VCAN, ANXA5, LAMC1, COL15A1 and VWF.

Abstract: For the determination of analytes in body fluids, voltammetry using a simple, non-selective, electrode sensor system has been found to work. The signal is desirably processed by a technique such as neural network analysis, which can permit plural analytes to be determined simultaneously.

Abstract: A state, particularly a disease state, associated with the production of volatiles is detected by passing a sample containing the volatiles to a single sensor. This may be a semiconductor gas sensor element or a surface acoustic wave device. This provides an output signal, e.g. in the form of a tailing peak. A plurality of characteristics of the signal (e.g. peak height and maximum positive gradient) are measured to characterise the sample and hence the underlying state. For example we can discriminate between urine samples which are (a) infected with proteus, (b) infected with E. coli or (c) uninfected.