Clinical impact of next-generation sequencing multi-gene panel highlighting the landscape of germline alterations in ovarian cancer patients

BRCA1 and BRCA2 are the most frequently mutated genes in ovarian cancer (OC), crucial both for the identification of cancer predisposition and therapeutic choices. However, germline variants in other genes could be involved in OC susceptibility. We characterized OC patients to detect mutations in genes other than BRCA1/2 that could be associated with a high risk to develop OC, and that could permit patients to enter the most appropriate treatment and surveillance program. Next-Generation Sequencing analysis with a 94-gene panel was performed on germline DNA of 219 OC patients. We identified 34 pathogenic/likely-pathogenic variants in BRCA1/2 and 38 in other 21 genes. Patients with pathogenic/likely-pathogenic variants in non-BRCA1/2 genes developed mainly OC alone compared to the other groups that developed also breast cancer or other tumors (p=0.001). Clinical correlation analysis showed that low-risk patients were significantly associated with platinum sensitivity (p<0.001). Regarding PARP inhibitors (PARPi) response, patients with pathogenic mutations in non-BRCA1/2 genes had significantly worse PFS and OS. Moreover, a statistically significant worse PFS was found for every increase of one thousand platelets before PARPi treatment. To conclude, knowledge about molecular alterations in genes beyond BRCA1/2 in OC could allow for more personalized diagnostic, predictive, prognostic, and therapeutic strategies for OC patients.

A chemical-loop approach for the generation of hydrogen by means of ethanol reforming

The work investigates the feasibility of a new process aimed at the production of hydrogen with inherent separation of carbon oxides. The process consists in a cycle in which, in the first step, a mixed metal oxide is reduced by ethanol (obtained from biomasses). The reduced metal is then contacted with steam in order to split the water and sequestrating the oxygen into the looping material’s structure. The oxides used to run this thermochemical cycle, also called “steam-iron process” are mixed ferrites in the spinel structure MeFe2O4 (Me = Fe, Co, Ni or Cu). To understand the reactions involved in the anaerobic reforming of ethanol, diffuse reflectance spectroscopy (DRIFTS) was used, coupled with the mass analysis of the effluent, to study the surface composition of the ferrites during the adsorption of ethanol and its transformations during the temperature program. This study was paired with the tests on a laboratory scale plant and the characterization through various techniques such as XRD, Mössbauer spectroscopy, elemental analysis... on the materials as synthesized and at different reduction degrees In the first step it was found that besides the generation of the expected CO, CO2 and H2O, the products of ethanol anaerobic oxidation, also a large amount of H2 and coke were produced. The latter is highly undesired, since it affects the second step, during which water is fed over the pre-reduced spinel at high temperature. The behavior of the different spinels was affected by the nature of the divalent metal cation; magnetite was the oxide showing the slower rate of reduction by ethanol, but on the other hand it was that one which could perform the entire cycle of the process more efficiently. Still the problem of coke formation remains the greater challenge to solve.

Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.

Analysis of charge-transport properties in GST materials for next generation phase-change memory devices

The quest for universal memory is driving the rapid development of memories with superior all-round capabilities in non-volatility, high speed, high endurance and low power. The memory subsystem accounts for a significant cost and power budget of a computer system. Current DRAM-based main memory systems are starting to hit the power and cost limit. To resolve this issue the industry is improving existing technologies such as Flash and exploring new ones. Among those new technologies is the Phase Change Memory (PCM), which overcomes some of the shortcomings of the Flash such as durability and scalability. This alternative non-volatile memory technology, which uses resistance contrast in phase-change materials, offers more density relative to DRAM, and can help to increase main memory capacity of future systems while remaining within the cost and power constraints. Chalcogenide materials can suitably be exploited for manufacturing phase-change memory devices. Charge transport in amorphous chalcogenide-GST used for memory devices is modeled using two contributions: hopping of trapped electrons and motion of band electrons in extended states. Crystalline GST exhibits an almost Ohmic I(V) curve. In contrast amorphous GST shows a high resistance at low biases while, above a threshold voltage, a transition takes place from a highly resistive to a conductive state, characterized by a negative differential-resistance behavior. A clear and complete understanding of the threshold behavior of the amorphous phase is fundamental for exploiting such materials in the fabrication of innovative nonvolatile memories. The type of feedback that produces the snapback phenomenon is described as a filamentation in energy that is controlled by electron–electron interactions between trapped electrons and band electrons. The model thus derived is implemented within a state-of-the-art simulator. An analytical version of the model is also derived and is useful for discussing the snapback behavior and the scaling properties of the device.

Movement Analysis by means of inertial sensors: from bench to bedside

in the everyday clinical practice. Having this in mind, the choice of a simple setup would not be enough because, even if the setup is quick and simple, the instrumental assessment would still be in addition to the daily routine. The will to overcome this limit has led to the idea of instrumenting already existing and widely used functional tests. In this way the sensor based assessment becomes an integral part of the clinical assessment. Reliable and validated signal processing methods have been successfully implemented in Personal Health Systems based on smartphone technology. At the end of this research project there is evidence that such solution can really and easily used in clinical practice in both supervised and unsupervised settings. Smartphone based solution, together or in place of dedicated wearable sensing units, can truly become a pervasive and low-cost means for providing suitable testing solutions for quantitative movement analysis with a clear clinical value, ultimately providing enhanced balance and mobility support to an aging population.

Dynamic analysis of the motorcycle chattering behaviour by means of symbolic multibody modelling

Aim of this research is the development and validation of a comprehensive multibody motorcycle model featuring rigid-ring tires, taking into account both slope and roughness of road surfaces. A novel parametrization for the general kinematics of the motorcycle is proposed, using a mixed reference-point and relative-coordinates approach. The resulting description, developed in terms of dependent coordinates, makes it possible to efficiently include rigid-ring kinematics as well as road elevation and slope. The equations of motion for the multibody system are derived symbolically and the constraint equations arising from the dependent-coordinate formulation are handled using a projection technique. Therefore the resulting system of equations can be integrated in time domain using a standard ODE algorithm. The model is validated with respect to maneuvers experimentally measured on the race track, showing consistent results and excellent computational efficiency. More in detail, it is also capable of reproducing the chatter vibration of racing motorcycles. The chatter phenomenon, appearing during high speed cornering maneuvers, consists of a self-excited vertical oscillation of both the front and rear unsprung masses in the range of frequency between 17 and 22 Hz. A critical maneuver is numerically simulated, and a self-excited vibration appears, consistent with the experimentally measured chatter vibration. Finally, the driving mechanism for the self-excitation is highlighted and a physical interpretation is proposed.