Pubblicazioni

This work evaluates the predictive ability of a novel personalized computational tool for simulating the growth of brain tumours using the neuroimaging data collected during one clinical case study. The mathematical model consists of an evolutionary fourth-order partial differential equation with degenerate motility, in which the spreading dynamics of the multiphase tumour is coupled with […]

Movement of cargos along microtubules plays key roles in diverse cellular processes, from signalling to mitosis. In cilia, rapid movement of ciliary components along the microtubules to and from the assembly site is essential for the assembly and disassembly of the structure itself1. This bidirectional transport, known as intraflagellar transport (IFT)2, is driven by the […]

Multiple approaches to use deep learning for image restoration have recently been proposed. Training such approaches requires well registered pairs of high and low quality images. While this is easily achievable for many imaging modalities, e.g. fluorescence light microscopy, for others it is not. Cryo-transmission electron microscopy (cryo-TEM) could profoundly benefit from improved denoising methods, […]

Cerebral organoids are 3D stem cell-derived models that can be utilized to study the human brain. The current consensus is that cerebral organoids consist of cells derived from the neuroectodermal lineage. This limits their value and applicability, as mesodermal-derived microglia are important players in neural development and disease. Remarkably, here we show that microglia can […]

Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. RAS pathway aberrations can be tracked in cfDNA to monitor resistance to anti-EGFR monoclonal antibodies in patients with metastatic colorectal cancer. […]