0000000000242014

AUTHOR

Giulia Raimondi

0000-0002-1425-4242

showing 2 related works from this author

X-ray Spectroscopy of (Ba,Sr,La)(Fe,Zn,Y)O3-δIdentifies Structural and Electronic Features Favoring Proton Uptake

2020

Mixed protonic–electronic conducting oxides are key functional materials for protonic ceramic fuel cells. Here, (Ba,Sr,La)(Fe,Zn,Y)O3−δ perovskites are comprehensively investigated by X-ray spectroscopy (in oxidized and reduced states). Extended X-ray absorption fine structure shows that Zn,Y doping strongly increases the tendency for Fe–O–Fe buckling. X-ray absorption near-edge spectroscopy at the Fe K-edge and X-ray Raman scattering at the O K edge demonstrate that both iron and oxygen states are involved when the samples are oxidized, and for the Zn,Y doped materials, the hole transfer from iron to oxygen is less pronounced. This can be correlated with the observation that these material…

X-ray spectroscopyMaterials scienceProtonGeneral Chemical Engineeringchemistry.chemical_element02 engineering and technologyGeneral Chemistry010402 general chemistry021001 nanoscience & nanotechnology01 natural sciencesOxygen0104 chemical sciencesExtended X ray absorption fine structure spectroscopy Functional materials Iron OxygenPerovskite Protonic ceramic fuel cells (PCFC) X ray absorptionCrystallographychemistryvisual_artMaterials Chemistryvisual_art.visual_art_mediumFuel cellsCeramicAbsorption (chemistry)0210 nano-technology
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The EU-funded I3LUNG Project:Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy

2023

Although immunotherapy (IO) has changed the paradigm for the treatment of patients with advanced non-small cell lung cancers (aNSCLC), only around 30% to 50% of treated patients experience a long-term benefit from IO. Furthermore, the identification of the 30 to 50% of patients who respond remains a major challenge, as programmed Death-Ligand 1 (PD-L1) is currently the only biomarker used to predict the outcome of IO in NSCLC patients despite its limited efficacy. Considering the dynamic complexity of the immune system-tumor microenvironment (TME) and its interaction with the host's and patient's behavior, it is unlikely that a single biomarker will accurately predict a patient's outcomes. …

Pulmonary and Respiratory MedicineCancer ResearchArtificial intelligenceOncologyNon-small cell lung cancerPredictive biomarkersMachine learningPersonalized medicine
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