Development of an in vitro three-dimensional colorectal tumor model for drug screening
Gerard Rubí, Biomaterials for Regenerative Therapies
The majority of morphogenetic and pathological processes are driven by cells responding to the surrounding matrix cues, including matrix composition, architecture, and mechanical properties. Despite the increased evidence of extracellular matrix (ECM) properties, in vitro substitutes still fail to effectively mimic the native microenvironment. In this study, we aim to develop and characterize cell-derived extracellular matrices (CDMs) obtained through a protein deposition from human mesenchymal stem cells cultured in sacrificial 3D scaffold templates of poly-lactic acid (PLA) microcarriers. Obtained decellularized CDMs closely mimic biochemical, physical, and mechanical properties of native tissues’ ECM. The produced novel CDMs, are currently tested as a 3D cell culture platform for disease modelling. This is achieved through CDMs repopulation with colorectal cancer cells and cancer associated fibroblasts (CAFs). The new 3D CDMs-cancer platform will provide an in vitro tumor model to study the cells-ECM interactions and potential therapeutic targets, to finally serve as a drug-screening platform for personalized medicine.
Novel m-Health and multimodal physiological biomarkers for non-invasive monitoring and home healthcare of Obstructive Sleep Apnea and COPD patients with comorbidities
Ignasi Ferrer, Biomedical Signal Processing and Interpretation
Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway obstructive events occur during sleep. These events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrovascular diseases. OSA is also known to be position-dependent in some patients, which is referred to as positional OSA (pOSA). The gold-standard technique for diagnosing OSA is nocturnal polysomnography (PSG), which consists in recording multiple physiological signals while the patient is asleep in a hospital sleep lab. However, PSG has some important limitations, such as the high cost of the diagnostic test; the diagnosis is usually performed with a one-night sleep assessment, which does not account for the variability of sleep performance in the patient; and the sleep quality varies from that at home, because the patient has to sleep in a different bed connected to a lot of electrodes and wires.
In this study we aim to study how smartphones could be used to diagnose and monitor sleep apnea at home. Since smartphones are worldwide available devices, with a lot of embedded sensors, they appear as a feasible mHealth tools that could help overcome these limitations.
The PhD discussions session will be held ONLINE at the GoToMeeting platform