Improving treatment of glioblastoma: new insights in targeting cancer stem cells effectively

Glioblastoma is the most common primary malignant brain tumour in the adult population. Despite multimodality treatment with surgery, radiotherapy and chemotherapy, outcomes are very poor, with less than 15% of patients alive after two years. Increasing evidence suggests that glioblastoma stem cells (GSCs) are likely to play an important role in the biology of this disease and are involved in treatment resistance and tumour recurrence following standard therapy. My thesis aims to address two main aspects of this research area: 1) optimization of methods to evaluate treatment responses of GSCs and their differentiated counterparts (non-GSCs), with a particular focus on a tissue culture model that resembles more closely the tumoral niche; 2) characterization of cell division and centrosome cycle of GSCs, investigating possible differences between these cells and non-GSCs, that would allow the identification of targets for new therapeutic strategies against glioblastomas. In the first part of my project, I optimized a clonogenic survival assay, to compare sensitivity of GSCs and non-GSCs to various treatments, and I developed the use of a 3-dimentional tissue culture system, that allows analysis of features and radiation responses of these two subpopulations in the presence of specific microenvironmental factors from the tumoral niche. In the second part, I show that GSCs display mitotic spindle abnormalities more frequently than non-GSCs and that they have distinctive features with regards to the centrosome cycle. I also demonstrate that GSCs are more sensitive than non-GSCs to subtle changes in Aurora kinase A activity, which result in a rapid increase in polyploidy and subsequently in senescence, with a consistent reduction in clonogenic survival. Based on these findings, I propose that kinases involved in the centrosome cycle need to be explored as a novel strategy to target GSCs effectively and improve outcomes of glioblastoma patients

Modelling of subgrid-scale phenomena in supercritical transitional mixing layers: an a priori study

A database of transitional direct numerical simulation (DNS) realizations of a supercritical mixing layer is analysed for understanding small-scale behaviour and examining subgrid-scale (SGS) models duplicating that behaviour. Initially, the mixing layer contains a single chemical species in each of the two streams, and a perturbation promotes roll-up and a double pairing of the four spanwise vortices initially present. The database encompasses three combinations of chemical species, several perturbation wavelengths and amplitudes, and several initial Reynolds numbers specifically chosen for the sole purpose of achieving transition. The DNS equations are the Navier-Stokes, total energy and species equations coupled to a real-gas equation of state; the fluxes of species and heat include the Soret and Dufour effects. The large-eddy simulation (LES) equations are derived from the DNS ones through filtering. Compared to the DNS equations, two types of additional terms are identified in the LES equations: SGS fluxes and other terms for which either assumptions or models are necessary. The magnitude of all terms in the LES conservation equations is analysed on the DNS database, with special attention to terms that could possibly be neglected. It is shown that in contrast to atmospheric-pressure gaseous flows, there are two new terms that must be modelled: one in each of the momentum and the energy equations. These new terms can be thought to result from the filtering of the nonlinear equation of state, and are associated with regions of high density-gradient magnitude both found in DNS and observed experimentally in fully turbulent high-pressure flows. A model is derived for the momentum-equation additional term that performs well at small filter size but deteriorates as the filter size increases, highlighting the necessity of ensuring appropriate grid resolution in LES. Modelling approaches for the energy-equation additional term are proposed, all of which may be too computationally intensive in LES. Several SGS flux models are tested on an a priori basis. The Smagorinsky (SM) model has a poor correlation with the data, while the gradient (GR) and scale-similarity (SS) models have high correlations. Calibrated model coefficients for the GR and SS models yield good agreement with the SGS fluxes, although statistically, the coefficients are not valid over all realizations. The GR model is also tested for the variances entering the calculation of the new terms in the momentum and energy equations; high correlations are obtained, although the calibrated coefficients are not statistically significant over the entire database at fixed filter size. As a manifestation of the small-scale supercritical mixing peculiarities, both scalar-dissipation visualizations and the scalar-dissipation probability density functions (PDF) are examined. The PDF is shown to exhibit minor peaks, with particular significance for those at larger scalar dissipation values than the mean, thus significantly departing from the Gaussian behaviour

Engineering of an Extreme Rainfall Detection System using Grid Computing

This paper describes a new approach for intensive rainfall data analysis. ITHACA's Extreme Rainfall Detection System (ERDS) is conceived to provide near real-time alerts related to potential exceptional rainfalls worldwide, which can be used by WFP or other humanitarian assistance organizations to evaluate the event and understand the potentially floodable areas where their assistance is needed. This system is based on precipitation analysis and it uses rainfall data from satellite at worldwide extent. This project uses the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis dataset, a NASA-delivered near real-time product for current rainfall condition monitoring over the world. Considering the great deal of data to process, this paper presents an architectural solution based on Grid Computing techniques. Our focus is on the advantages of using a distributed architecture in terms of performances for this specific purpos