The present invention relates to a method of simultaneously diagnosing active tuberculosis and latent tuberculosis infection (LTBI) using one or more biomarkers selected from a white blood cell count, a hemoglobin concentration, a neutrophil count, a lymphocyte count, a monocyte count, a procalcitonin concentration, a C-reactive protein concentration, an α1-acid glycoprotein concentration and an erythrocyte sedimentation rate, or a combination thereof. The present invention may provide a diagnostic method for simultaneously differentiating active tuberculosis and LTBI without a separate additional test on a patient diagnosed as positive by a conventional tuberculosis infection assay such as a tuberculin skin test (TST) or an interferon-γ release assay (IGRA).

In one aspect the invention provides a method for distinguishing between a viral-only infection of the upper respiratory tract or a bacterial or viral/bacterial coinfection in a patient by analyzing a respiratory sample.

The present invention provides a system and method for diagnosing, screening or monitoring a disease by analyzing the breath of a test subject using a selected definitive sensor set in conjunction with a pattern recognition analyzer, wherein the pattern recognition analyzer receives output signals of the sensor set, compares them to disease-specific patterns derived from a database of response patterns of the sensor set to exhaled breath of subjects with known diseases, wherein each of the disease-specific patterns is characteristic of a particular disease, and selects a closest match between the output signals of the sensor set and the disease-specific pattern. The present invention further provides a method of diagnosing, screening or monitoring a disease based on the determination of levels of volatile organic compounds (VOCs) from a universal biomarker set, including 2-ethylhexanol, 3-methylhexane, 5-ethyl-3-methyl-octane, acetone, ethanol, ethyl acetate, ethylbenzene, isononane, isoprene, nonanal, styrene, toluene and undecane.

The present invention relates to methods and kits for diagnosing a postoperative pulmonary infection in a patient who underwent surgery. More particularly, the present invention relates to a method for diagnosing a postoperative pulmonary infection in a patient who underwent surgery, comprising a step consisting of measuring the concentration of endocan in a blood sample obtained from said patient, at a time point comprised between 3 h and 30 h after surgery.

A method may predict risk of onset of severe interstitial pneumonia caused by an immune checkpoint inhibitor to achieve a safe and highly effective cancer immunotherapy. Any one or more selected from: (a) cell count or proportion of Vδ2.sup.+γδ T cells in peripheral blood mononuclear cells isolated from a subject; (b) cell count or proportion of Vδ2.sup.+γδ T cells after antigenic stimulation in peripheral blood mononuclear cells isolated from a subject; (c) cell count or proportion of Vδ2.sup.+γδ T cells in peripheral blood T cells isolated from a subject; and (d) cell count or proportion of Vδ2.sup.+γδ T cells after antigenic stimulation in peripheral blood T cells isolated from a subject are measured, and the risk of onset of severe interstitial pneumonia is predicted by using the cell count or proportion as an index.

The present invention concerns methods and tools for analysing biomarkers useful for diagnosing an individual, in particular a newborn, with a respiratory disease, especially a newborn suffering from respiratory distress syndrome (RDS). The method and tools of the invention can in one embodiment be used for very rapidly detecting the ratio between lecithin and sphingomyelin in very small body fluid samples, e.g. gastric aspirate of a newborn. The invention is thus useful for obtaining a rapid treatment of RDS by administration of surfactant.

Excessive deposition of extracellular matrix is a hallmark of Idiopathic pulmonary fibrosis (IPF), it is advantageous to target the cells and the mechanisms associated with this process. By targeting myofibroblasts (specialized contractile fibroblasts) that are key for the development of IPF with drugs conjugated with fibroblast activation protein (FAP), this technology helps minimize the production of extracellular matrix in the lungs and provides a new treatment option for patients diagnosed with IPF.

The present invention relates to methods for diagnosing Respiratory Distress Syndrome of newborn.

The disclosure concerns a method of obtaining information about the disease status of an individual by processing input data using a trained machine learning algorithm model to generate an output representing the information. The disclosure also concerns a related computer program, data processing apparatus, and system, as well as a method for training a machine learning algorithm model to generate information about the disease status of an individual. The information may, for example, relate to the presence, absence or type of M. tuberculosis complex infection in the individual.

The present invention provides an isolated binding protein comprising a cTnI antigen binding domain. The antigen binding domain comprises at least one complementarity determining region selected from amino acid sequences defined herein, or has sequence identity of at least 80% to the complementarity determining region of said amino acid sequence and an affinity of K.sub.D≤1.41×10.sup.−9 mol/L to cTnI. The binding protein can be used for detection of cTnI protein.