Personalised Medicine

Not all pain is the same. Depending on the cause, it requires different therapies. A team led by ETH Zurich has now developed a method that enables physicians to better distinguish between physical and psychosocial pain.

Addressing problems with diagnosing and treating breast cancer, scientists at EPFL have developed EMBER, a tool that integrates breast cancer transcriptomic data from multiple databases. EMBER can improve precision oncology by accurately predicting molecular subtypes and therapy responses.

Using machine-learning methods, researchers at ETH Zurich have shown that more than half of all killer T cells exhibit nuclear invaginations, or folds in the cell’s nuclear envelope. Thanks to this particular cellular architecture, such cells are able to mount a faster and stronger response to pathogens.

Researchers from ETH Zurich and KUNO Klinik St. Hedwig in Regensburg have developed an algorithm that provides an automatic and reliable method of detecting a certain heart defect in newborns.

Knee operations on the meniscus cartilage are a frequent procedure on a particularly complex part of the human body. Empa researchers want to provide an improved basis for clinicians in order to reduce the risks of the operation. Using 3D models based on micro-computed tomography analyses in the laboratory, they are mapping the blood vessel network of the meniscus on a nanometer scale.