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The nature of the immune responses associated with COVID‐19 pathogenesis and disease severity, as well as the breadth of vaccine coverage and duration of immunity, is still unclear. Given the unpredictability for developing a severe/complicated disease, there is an urgent need in the field for predictive biomarkers of COVID‐19. We have analyzed IgG Fc N ‐glycan traits of 82 SARS‐CoV‐2+ unvaccinated patients, at diagnosis, by nano‐LC‐ESI‐MS. We determined the impact of IgG Fc glyco‐variations in the induction of NK cells activation, further evaluating the association between IgG Fc N ‐glycans and disease severity/prognosis. We found that SARS‐CoV‐2+ individuals display, at diagnosis, variations in the glycans composition of circulating IgGs. Importantly, levels of galactose and sialic acid structures on IgGs are able to predict the development of a poor COVID‐19 disease. Mechanistically, we demonstrated that a deficiency on galactose structures on IgG Fc in COVID‐19 patients appears to induce NK cells activation associated with increased release of IFN‐γ and TNF‐α, which indicates the presence of pro‐inflammatory immunoglobulins and higher immune activation, associated with a poor disease course. This study brings to light a novel blood biomarker based on IgG Fc glycome composition with capacity to stratify patients at diagnosis.

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Robotics and Artificial Intelligence are two deeply intertwined fields of study, currently experiencing formidable growth. To foster these developments, the RoboCup initiative is a fantastic test bed to experiment new approaches and ideas. This dissertation is rooted in the groundwork laid by previous FCPortugal3D contributions for the RoboCup simulation 3D robotic soccer league, and seeks to design and implement a humanoid robotic kick system for situations where the robot is moving. It employs Reinforcement Learning (RL) techniques, namely the Proximal Policy Optimization (PPO) algorithm to create fast and reliable skills. The kick was divided into 6 cases according to initial conditions and separately trained for each of the cases. A series of kicks, both static and in motion, using two different gaits were developed. The kicks obtained show very high reliability and, when compared to state of the art kicks, displayed a very high time performance improvement. This opens the door to more dynamic games with faster kicks in the RoboCup simulation 3D league.