Abstract: The present invention provides a computer-implemented method for analysing a urine sample from a subject. The method comprises providing the value of one or more cell-free DNA fragment size metrics for said sample, and determining whether the sample has a high or low likelihood of being from a brain cancer patient by providing said values of said cell-free DNA fragment size metrics as input to a machine learning model. The machine learning model is trained to classify sample data into one of at least two classes, the at least two classes comprising a first class having a high likelihood of being from a brain cancer patient and a second class having a low likelihood of being from a brain cancer patient. Methods for diagnosing or screening for brain cancer, detecting recurrence or residual disease, providing a prognosis or selecting a treatment for brain cancer are also described.

Abstract: A reader device for detecting the presence of a transponder within an operating distance of the reader device, the reader device comprising a resonant circuit adapted for generating an electromagnetic field having a frequency distribution around a resonance frequency, and a transponder detection unit adapted for detecting the presence of the transponder within the operating distance of the reader device by a shift of the resonance frequency of the resonant circuit in the presence of the transponder within the operating distance of the reader device.

Abstract: A reader device for detecting the presence of a transponder within an operating distance of the reader device, the reader device comprising a resonant circuit adapted for generating an electromagnetic field having a frequency distribution around a resonance frequency, and a transponder detection unit adapted for detecting the presence of the transponder within the operating distance of the reader device by a shift of the resonance frequency of the resonant circuit in the presence of the transponder within the operating distance of the reader device.