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I graduated in Chemical Sciences from the University of Valladolid in 2004.

In 2005 I started my PhD studies at the Instituto de Biología y Genética Molecular (Universidad de Valladolid-Consejo Superior de Investigaciones Científicas), which I defended in 2009. During this time I did research on arachidonic acid metabolism in macrophages using mass spectrometry.

As a postdoctoral researcher and as a continuation of the study of arachidonic acid, I studied the regulation of its lipid mediators (e.g. prostaglandins and leukotrienes) and other oxylipins in respiratory diseases at the Karolinska Institute (Stockholm) from 2010 to 2013.

I then joined OWL Metabolomics (Bilbao) under a Marie Curie mobility contract. There I stayed until 2016 when I joined the French National Institute for Agricultural Research (INRA) to investigate the digestion of triglyceride regioisomers by developing bioinformatics models.

In 2018, I moved to the University of Uppsala as a researcher, where I impacted the development of analytical and bioinformatics tools in lipidomics to obtain better biological information on lipid involvement in biologics. In addition, I applied these tools to the study of anthracycline-induced cell death.

Finally, in February 2022 I moved to the University of Valladolid with a María Zambrano research contract.

At IBGM, I study the relationship between lipidoma and ferroptosis in macrophages. Ferroptosis is a type of programmed cell death in which membrane lipid peroxidation occurs. Thus, lipidoma and ferroptosis play a key role in inflammation and especially in the pro/anti-inflammatory regulation of macrophages. However, it is not fully described today how lipid regulation can elicit ferroptosis in inflammatory cells and thereby regulate inflammation.

My vision is the comprehensive development of analytical, bioinformatics and biological tools to actively understand metabolism in inflammatory cells (immunometabolism). Bioinformatic modeling is fundamental in integrating metabolic information into chemical networks that can predict metabolic response to drugs. These models will open the door to controlling the response of inflammatory cells by drugs that affect lipid metabolism (e.g. statins). In the long term, immunometabolic interventions could improve the treatments and prognosis of, for example, cancer patients.