Cardiovascular diseases are the leading cause of premature death in developed countries. Among them, abdominal aortic aneurysm (AAA) has become a significant health public challenge worldwide, with extremely high rates of mortality in case of rupture. The only curative treatment relies on surgery and clinicians are confronted to a critical lack of tools to evaluate the outcomes of patients. As a result, some patients are treated while they would never have ruptured and others with an AAA below the threshold for treatment do develop a fatal rupture. By bringing a practical solution to tackle the unpredictability of AAA, PREDICTA project will be a major breakthrough for cares provided to patients. The aim is to create an innovative aid-decision platform to predict AAA outcomes to enable precision medicine and develop a personalized therapeutic approach. We propose to take up the challenge to use innovative techniques in biology and imaging to identify new patterns and to combine them using artificial intelligence (AI) to develop efficient predictive models. The main tools developed in the platform will include: - Automatization of vascular imaging analysis and generation of a novel AI-based tool for pre-surgical planning. – Prediction of AAA progression using Machine Learning by combining clinical, imaging and omics data obtained from patients with AAA. – Prediction of the post-operative outcomes and the risk of endoleaks. The PREDICTA platform will increment all the applications developed and will provide a decision support system that will be tested in a multicentre study to test and optimize its use for clinical practice.

In 2023, intracerebral haemorrhage (ICH) remains the most devastating stroke subtype. Evidence suggests that ICH leads to mortality and disability through a combination of primary and secondary (delayed) injury. Perihematomal area is a promising surrogate marker of secondary brain injury after ICH, and a potential therapeutic target. However, neuroradiological definition of the perihematomal area represents an unmet need for improving knowledge on ICH pathophysiological mechanisms and treatments. Perihematomal vessels are likely to be moved over by the mass effect from the hematoma immediately after ICH, with significant mechanical stress and alterations in their density and architecture, and consequent impact in perihematomal brain perfusion, promoting perihaemorrhagic oedema development and contributing to secondary brain injury and poor functional outcome after ICH. In this context, vessel density and architecture changes occurring in the perihematomal area during the acute phase of ICH, and vessel remodeling during brain recovery, have never been studied. The main goal of this project is to characterize vessel density and architectural changes in the perihematomal area and to study their putative association with perihematomal perfusion, perihematomal oedema and patient’s long-term clinical outcome, in a large prospective cohort of patients with ICH. VINCERE-ICH project aims to use a new available computational tool on vessel extraction, segmentation, and analysis for gathering data on perihaemorrhagic area, for studying the association between perihaemorrhagic vessel density and architectural changes and other radiological ICH features, including perihematomal perfusion and perihaemorrhagic oedema, and ICH long-term outcome. This translational project will provide novel insights on novel radiological biomarkers of secondary brain injury, recovery, and functional outcome after ICH, gathering data from a large prospective cohort of patients with acute ICH.

By affecting more than 3% of adults in the human population, psoriasis is one of the most common skin diseases. Evidence of genetic predisposition has emerged with the association of inflammasome members NLRP1 and NLRP3 polymorphisms with higher risk of psoriasis. In addition, RhoGTPases dysregulation have been also associated with plaque of psoriasis in humans. Rac1 is found highly active in human psoriatic lesional skin and keratinocytes, and keratinocyte-specific overexpression of an activated mutant of Rac, in a transgenic mouse model closely mimics the presentation of human psoriasis. Interestingly, the link between Rac activation, inflammasomes and the inflammatory psoriasis-like phenotype observed in mice is still unclear. Our hypothesis is that the Rac-Pak-inflammasome signaling axis determines the psoriasis-like phenotype observed in mice as well as psoriasis in humans and could be a novel target to treat psoriasis in patients. Here, based on solid preliminary data, we propose a multidisciplinary consortium that will dissect the Pak1 regulation of inflammasomes in the context of psoriasis at the molecular level, in vivo using mice genetic model as well as in patient’s samples.