Locating the source of volcanic tremor at stromboli volcano, italy

We have developed a method for locating sources of volcanic tremor and applied it to a dataset recorded on Stromboli volcano before and after the onset of the February 27th 2007 effusive eruption. Volcanic tremor has attracted considerable attention by seismologists because of its potential value as a tool for forecasting eruptions and for better understanding the physical processes that occur inside active volcanoes. Commonly used methods to locate volcanic tremor sources are: 1) array techniques, 2) semblance based methods, 3) calculation of wave field amplitude. We have choosen the third approach, using a quantitative modeling of the seismic wavefield. For this purpose, we have calculated the Green Functions (GF) in the frequency domain with the Finite Element Method (FEM). We have used this method because it is well suited to solve elliptic problems, as the elastodynamics in the Fourier domain. The volcanic tremor source is located by determining the source function over a regular grid of points. The best fit point is choosen as the tremor source location. The source inversion is performed in the frequency domain, using only the wavefield amplitudes. We illustrate the method and its validation over a synthetic dataset. We show some preliminary results on the Stromboli dataset, evidencing temporal variations of the volcanic tremor sources.

Study of medicinal and food plants as a source of biologically active compounds.

In the last few decades, scientific evidence has pointed out the health-beneficial effects of phenolic compounds in foods, including a decrease in risk of developing degenerative and chronic diseases, known to be caused by oxidative stress. In this frame can be inserted research carried out during my PhD thesis, which concerns the phytochemical investigation of phenolic composition in sweet cherries (Prunus avium L.), apple fruits (Malus domestica L.) and quinoa seeds (Chenopodium quinoa Willd.). The first project was focused on the investigation of phytochemical profile and nutraceutical value of fruits of new sweet cherry cultivars. Their phenolic profile and antioxidant activity were investigated and compared with those of commonly commercialized cultivars. Their nutraceutical value was evaluated in terms of antioxidant/neuroprotective capacity in neuron-like SH-SY5Y cells, in order to investigate their ability to counteract the oxidative stress and/or neurodegeneration process The second project was focused on phytochemical analysis of phenolic compounds in apples of ancient cultivars with the aim of selecting the most diverse cultivars, that will then be assayed for their anti-carcinogenic and anti-proliferative activities against the hepato-biliary and pancreatic tumours. The third project was focused on the analysis of polyphenolic pattern of seeds of two quinoa varieties grown at different latitudes. Analysis of phenolic profile and in vitro antioxidant activity of seed extracts both in their free and soluble-conjugated forms, showed that the accumulation of some classes of flavonoids is strictly regulated by environmental factors, even though the overall antioxidant capacity does not differ in quinoa Regalona grown in Chile and Italy. During the internship period carried out at the Department of Organic Chemistry at Universidad Autónoma de Madrid (UAM), it was achieved the isolation of two pentacyclic triterpenoids, from an endemic Peruvian plant, Jatropha macrantha Müll. Arg., with bio-guided fractionation technique.

Gastrointestinal stromal tumors: Arbutus unedo L. as a source of novel chemotherapeutics & mechanisms behind metastasis

Gastrointestinal stromal tumors (GIST) are mesenchymal neoplasms frequently caused by a gain of function mutation in KIT or PDGFRα, two tyrosine kinase receptors (TKR). For this reason, they are successfully treated with imatinib, a tyrosine kinase inhibitor (TKI). However, the therapy is typically long-term ineffective due to imatinib resistance, which represents the main issue in the clinic of GISTs. Although numerous efforts have been made in the last two decades to develop novel therapies for imatinib-resistant GISTs, the approvals of multi-target TKIs have only improved the clinical outcomes modestly. Emblematic is the recent failure of ripretinib in the phase III INTRIGUE trial, decisively marking the end of the paradigm only based on the central role of KIT secondary mutations in imatinib resistance, and the consequent seeking of multi-target TKIs as the solution. Consistent with this clinical result, preclinical studies have revealed numerous mechanisms of resistance that are not targetable with multi-target TKIs, indicating that imatinib resistance is more multifaceted than initially hypothesized and explaining the modest efficacy of these latter. In this scenario, the absence of drugs capable of long-term counteracting the rise of imatinib-resistant subclones unavoidably leads to progressive disease and metastasis. In particular, the onset of metastases remarkably impacts the median overall survival and determines the most GIST-related deaths. Therefore, new therapy proposals are needed. Here, we present two project lines investigating novel strategies to counteract imatinib-resistant GISTs.

Application of innovative methods of source apportionment in air contamination assessment

In this work, new tools in atmospheric pollutant sampling and analysis were applied in order to go deeper in source apportionment study. The project was developed mainly by the study of atmospheric emission sources in a suburban area influenced by a municipal solid waste incinerator (MSWI), a medium-sized coastal tourist town and a motorway. Two main research lines were followed. For what concerns the first line, the potentiality of the use of PM samplers coupled with a wind select sensor was assessed. Results showed that they may be a valid support in source apportionment studies. However, meteorological and territorial conditions could strongly affect the results. Moreover, new markers were investigated, particularly focusing on the processes of biomass burning. OC revealed a good biomass combustion process indicator, as well as all determined organic compounds. Among metals, lead and aluminium are well related to the biomass combustion. Surprisingly PM was not enriched of potassium during bonfire event. The second research line consists on the application of Positive Matrix factorization (PMF), a new statistical tool in data analysis. This new technique was applied to datasets which refer to different time resolution data. PMF application to atmospheric deposition fluxes identified six main sources affecting the area. The incinerator’s relative contribution seemed to be negligible. PMF analysis was then applied to PM2.5 collected with samplers coupled with a wind select sensor. The higher number of determined environmental indicators allowed to obtain more detailed results on the sources affecting the area. Vehicular traffic revealed the source of greatest concern for the study area. Also in this case, incinerator’s relative contribution seemed to be negligible. Finally, the application of PMF analysis to hourly aerosol data demonstrated that the higher the temporal resolution of the data was, the more the source profiles were close to the real one.