TomoSim comes as part of project ATMOS, a miniaturised DOAS tomographic atmospheric evaluation device, designed to fit a small drone. During the development of the project, it became necessary to write a simulation tool for system validation. TomoSim is the answer to this problem. The software has two main goals: to mathematically validate the tomographic acquisition method; and to allow some adjustments to the system before reaching final product stages. This measurement strategy was based on a drone performing a sequential trajectory and gathering projections arranged in fan beams, before using some classical tomographic methods to reconstruct a spectral image. The team tested three different reconstruction algorithms, all of which were able to produce an image, validating the team’s initial assumptions regarding the trajectory and acquisition strategy. All algorithms were assessed on their computational performance and their ability for reconstructing spectral "images", using two phantoms, one of which custom made for this purpose. In the end, the team was also able to uncover certain limitations of the TomoSim approach that should be addressed before the final stages of the system.

SARS-CoV-2 infection triggers distinct patterns of disease development, characterized by significant alterations in host regulatory responses. Severe cases exhibit profound lung inflammation and systemic repercussions. Remarkably, critically ill patients display a "lipid storm", influencing the inflammatory process and tissue damage. Sphingolipids (SL) play pivotal roles in various cellular and tissue processes, including inflammation, metabolic disorders, and cancer. In this study, we employed high-resolution mass spectrometry to investigate SL metabolism in plasma samples obtained from control subjects (n=55), COVID-19 patients (n=204), and convalescent individuals (n=77). These data were correlated with inflammatory parameters associated with the clinical severity of COVID-19. Additionally, we utilized RNAseq analysis to examine the gene expression of enzymes involved in the SL pathway. Our analysis revealed the presence of thirty-eight SL species from seven families in the plasma of study participants. The most profound alterations in the SL species profile were observed in patients with severe disease. Notably, the predominant sphingomyelin (SM d18:1) species emerged as a potential biomarker for COVID-19 severity, showing decreased levels in the plasma of convalescent individuals. Elevated SM levels were positively correlated with age, hospitalization duration, clinical score, neutrophil count, as well as the production of IL-6 and IL-8. Intriguingly, we identified a putative protective effect against disease severity mediated by SM (d18:1/24:0), while ceramide (Cer) d18:1/24:1 and d18:1/24:0 was associated with increased risk. Moreover, we observed enhanced expression of key enzymes involved in SL pathway, in blood cells from severe COVID-19 patients, suggesting a primary flow towards Cer generation in tandem with SM synthesis. These findings underscore the potential of SM as a prognostic biomarker for COVID-19 and highlight promising pharmacological targets. By targeting sphingolipid pathways, novel therapeutic strategies may emerge to mitigate the severity of COVID-19 and improve patient outcomes.