Universo di de Sitter

Lo scopo dell'elaborato è di studiare la geometria di de Sitter ovvero la soluzione nel vuoto delle equazioni di Einstein con un termine cosmologico. La trattazione viene sviluppata in due capitoli. Il primo capitolo vuole motivare l'interesse alla soluzione di de Sitter presentando due fasi dell'evoluzione dell'universo, l'inflazione cosmologica e l'attuale espansione accelerata, entrambe descrivibili approssimativamente dalla geometria di de Sitter. Il secondo capitolo si concentra sull'analisi dello spaziotempo di de Sitter descrivendolo in quattro diversi sistemi di coordinate, analizzandone le geodetiche e studiandone la struttura causale attraverso i diagrammi di Penrose

HDAC class I inhibitor domatinostat sensitizes pancreatic cancer to chemotherapy by targeting cancer stem cell compartment via FOXM1 modulation

Pancreatic ductal adenocarcinoma (PDAC) represents an unmet clinical need due to the very poor prognosis and the lack of effective therapy. Here we investigated the potential of domatinostat (4SC-202), a new class I histone deacetylase (HDAC) inhibitor, currently in clinical development, to sensitize PDAC to first line standard gemcitabine (G)/taxol (T) doublet chemotherapy treatment. Methods: Synergistic anti-tumor effect of the combined treatment was assessed in PANC1, ASPC1 and PANC28 PDAC cell lines in vitro as well as on tumor spheroids and microtissues, by evaluating combination index (CI), apoptosis, clonogenic capability. The data were confirmed in vivo xenograft models of PANC28 and PANC1 cells in athymic mice. Cancer stem cells (CSC) targeting was studied by mRNA and protein expression of CSC markers, by limiting dilution assay, and by flow cytometric and immunofluorescent evaluation of CSC mitochondrial and cellular oxidative stress. Mechanistic role of forkhead box M1 (FOXM1) and downstream targets was evaluated in FOXM1-overexpressing PDAC cells. Results: We showed that domatinostat sensitized in vitro and in vivo models of PDAC to chemotherapeutics commonly used in PDAC patients management and particularly to GT doublet, by targeting CSC compartment through the induction of mitochondrial and cellular oxidative stress. Mechanistically, we showed that domatinostat hampers the expression and function of FOXM1, a transcription factor playing a crucial role in stemness, oxidative stress modulation and DNA repair. Domatinostat reduced FOXM1 protein levels by downregulating mRNA expression and inducing proteasome-mediated protein degradation thus preventing nuclear translocation correlated with a reduction of FOXM1 target genes. Furthermore, by overexpressing FOXM1 in PDAC cells we significantly reduced domatinostatinducing oxidative mitochondrial and cellular stress and abolished GT sensitization, both in adherent and spheroid cells, confirming FOXM1 crucial role in the mechanisms described. Finally, we found a correlation of FOXM1 expression with poor progression free survival in PDAC chemotherapy-treated patients

A Spatially Resolved Dark- versus Light-Zone Microenvironment Signature Subdivides Germinal Center-Related Aggressive B Cell Lymphomas

We applied digital spatial profiling for 87 immune and stromal genes to lymph node germinal center (GC) dark- and light-zone (DZ/LZ) regions of interest to obtain a differential signature of these two distinct microenvironments. The spatially resolved 53-genes signature, comprising key genes of the DZmutational machinery and LZ immune and mesenchymal milieu, was applied to the transcriptomes of 543 GC-related diffuse large B cell lymphomas and double-hit ( DH) lymphomas. According to the DZ/LZ signature, the GC-related lymphomas were sub-classified into two clusters. The subgroups differed in the distribution of DH cases and survival, with most DH displaying a distinct DZ-like profile. The clustering analysis was also performed using a 25-genes signature composed of genes positively enriched in the non-B, stromal sub-compartments, for the first time achieving DZ/LZ discrimination based on stromal/immune features. The report offers new insight into the GC microenvironment, hinting at a DZ microenvironment of origin in DH lymphomas

Valproic Acid Synergizes With Cisplatin and Cetuximab in vitro and in vivo in Head and Neck Cancer by Targeting the Mechanisms of Resistance

Recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) is a devastating malignancy with a poor prognosis. The combination of cisplatin (CDDP) plus cetuximab (CX) is one of the standard first-line treatments in this disease. However, this therapeutic regimen is often associated with high toxicity and resistance, suggesting that new combinatorial strategies are needed to improve its therapeutic index. In our study, we evaluated the antitumor effects of valproic acid (VPA), a well-known antiepileptic agent with histone deacetylase inhibitory activity, in combination with CDDP/CX doublet in head and neck squamous cell carcinoma (HNSCC) models. We demonstrated, in HNSCC cell lines, but not in normal human fibroblasts, that simultaneous exposure to equitoxic doses of VPA plus CDDP/CX resulted in a clear synergistic antiproliferative and pro-apoptotic effects. The synergistic antitumor effect was confirmed in four different 3D-self-assembled spheroid models, suggesting the ability of the combined approach to affect also the cancer stem cells compartment. Mechanistically, VPA enhanced DNA damage in combination treatment by reducing the mRNA expression of ERCC Excision Repair 1, a critical player in DNA repair, and by increasing CDDP intracellular concentration via upregulation at transcriptional level of CDDP influx channel copper transporter 1 and downregulation of the ATPAse ATP7B involved in CDDP-export. Valproic acid also induced a dose-dependent downregulation of epidermal growth factor receptor (EGFR) expression and of MAPK and AKT downstream signaling pathways and prevent CDDP- and/or CX-induced EGFR nuclear translocation, a well-known mechanism of resistance to chemotherapy. Indeed, VPA impaired the transcription of genes induced by non-canonical activity of nuclear EGFR, such as cyclin D1 and thymidylate synthase. Finally, we confirmed the synergistic antitumor effect also in vivo in both heterotopic and orthotopic models, demonstrating that the combined treatment completely blocked HNSCC xenograft tumors growth in nude mice. Overall, the introduction of a safe and generic drug such as VPA into the conventional treatment for R/M HNSCC represents an innovative and feasible antitumor strategy that warrants further clinical evaluation. A phase II clinical trial exploring the combination of VPA and CDDP/CX in R/M HNSCC patients is currently ongoing in our institute

Automated nested co-design framework for structural/control dynamics in flexible space systems

Modern space missions for Earth Observation (EO) purposes often rely on satellites equipped with very large flexible appendages, such as antennas and solar panels, which are demanded to perform agile slew manoeuvres. In most cases, the elasticity of such systems cannot be neglected in the design of the attitude controller, as excessive elastic displacements of the structural elements may compromise their stability and pointing performance. In this scenario, this paper aims at proposing an automated nested optimization framework to simultaneously optimize spacecraft structural and control dynamics, to be applicable to a wide range of flexible spacecraft. The objective of such a co-design architecture is to modify design parameters, at both structural and control levels, to minimize the mass of the spacecraft while maximizing its agility and satisfying imposed requirements. Moreover, as robust multivariable techniques have become more and more applied to ensure satisfactory robust performance margins, this paper's goal is to pose a multi-channel structured control architecture in the co-design problem. To guarantee the generality of implementation, a structural design tool (MSC Nastran) is interfaced with a coding environment (Matlab/Simulink) to set-up an autonomous exchange of information between structural and control domains. Starting from an initial definition of the spacecraft material, geometry and control requirements (in terms of loop-shaping transfer functions), relevant parameters are extracted from the structural tool and a linearized dynamic model assembled. Then, a controller is synthetized based on the provided requirements, followed by a verification on the nonlinear plant of the satellite. The procedure is repeated until the stop criteria (based on tolerance and max iterations) is satisfied. Finally, the output of the proposed architecture is obtained as an optimized structural model and robust controller tailored for the satellite dynamics

A Deep Reinforcement Learning Approach to Autonomous Spacecraft Docking

A great deal of research interest is currently granted to enhance the autonomy of space systems, with particular attention to future on-orbit servicing and docking operations. In this scenario, modern machine learning algorithms are a key asset to the development of such activities. This paper aims at giving a contribution in this field by implementing a Deep Reinforcement Learning (DRL) Actor/Critic approach as a feedback control law for a three-degrees-of-freedom autonomous docking manoeuvre. In detail, the agent's policy is estimated to map a set of generally available observations (i.e. spacecraft attitude, position and corresponding rates) to a group of actions (represented by the commands exerted on the chaser spacecraft) to maximize a given reward signal. The policy is learned to successfully carry out the manoeuvre while both preventing collisions and respecting constraints in terms of docking conditions, without relying on pre-programmed reference controllers. To this purpose, the DRL framework is developed in Matlab/Simulink environment by coupling three different Matlab tools, namely Simscape Multibody to simulate the spacecraft dynamics, the Reinforcement Learning Toolbox to set-up the learning environment and the Deep Learning Toolbox to design the DLR policy Neural Networks. Finally, simulations are carried out to verify the efficacy of the proposed solution, aiming at offering ground for further developments

Mixed Kane–Newton Multi‑Body Analysis of a Dual‑Arm Robotic System for On‑Orbit Servicing Missions

A currently relevant topic is the development of on-orbit servicing missions designed to repair, refuel or deorbit non-co-operative spacecraft. For this purpose, it is possible to use space robotic systems composed of a main platform and one or more robotic arms. In this paper, the capacity of a dual-arm robotic system to manipulate and to deorbit a generic target will be analyzed. For this purpose, a mixed Kane–Newton multi-body model will be implemented; this model will allow to switch automatically from an open-chain configuration (target captured via a single robotic arm) to a closed-chain configuration (target captured via both robotic arms) and vice versa. The flexibility of the joints of the system and the flexibility of the components of the robotic arms will be considered in the model. The system will be properly sized to operate the deorbit-ing of the target. Under the hypothesis of planar motion, numerical results will be presented to validate the model and to demonstrate the correct sizing of the system

L'arte come attivatore sociale: il progetto di Servizio Civile Street Art a Roma

Partecipare alla prima edizione del progetto Street art a Roma nel 2017 ci ha permesso di conoscere in maniera profonda un fenomeno complesso come la Street Art, fortemente rivalutato negli ultimi anni e sempre più importante nel contesto romano (tanto da richiedere l'accrescimento delle forze in campo per la sua documentazione e conservazione attraverso il nostro coinvolgimento), offrendoci anche un'occasione per comprendere meglio la nostra città, osservare dall'interno tutti i meccanismi, le difficoltà e le forze che si dispiegano quotidianamente per la sua amministrazione

Active vibration control of large space structures: Modelling and experimental testing of offset piezoelectric stack actuators

To meet demanding mission objectives, most current satellites for Earth and Universe observation are equipped with large flexible appendages. However, due to the coupling between spacecraft rigid and elastic dynamics, unwanted elastic vibrations of such flexible elements may compromise the achievement of pointing and stability requirements. Therefore, control solutions aiming at avoiding instabilities and, at worst, the failure of the mission, are currently needed. In this scenario, growing interest has been recently devoted to Active Vibration Control (AVC) strategies relying on the use of smart materials. Among them, piezoelectric patches are the most studied and tested devices for both actuating and sensing purposes. This paper aims to contribute to this line of research by investigating a different type of actuator, namely an Offset Piezoelectric Stack Actuator (OPSA), to assess its performance in damping out elastic vibrations of large space structures. Moreover, special attention is devoted to compare OPSA performance with standard patch actuators behaviour. In order to develop the AVC system, an equivalent electro-mechanical coupled Finite Element (FE) formulation is implemented, integrating both sensors and piezo-stack elements on the passive hosting structure. The final structural model including both electrical inputs/outputs, as well as modified mass and stiffness due to the additional piezo devices, is then obtained. A parametric analysis is carried out to optimize the maximum control action exerted by the OPSA device. Finally, the OPSA numerical model is experimentally validated by mounting it on a cantilever plate, representative of a scaled solar panel. Experimental data are used not only to verify the device expected functioning, but also to tune the parameters in the OPSA FE model, which can be finally integrated in a planar satellite dynamics simulator to evaluate the AVC system efficiency when performing attitude manoeuvres

A Study on Structural Health Monitoring of a Large Space Antenna via Distributed Sensors and Deep Learning

Most modern Earth and Universe observation spacecraft are now equipped with large lightweight and flexible structures, such as antennas, telescopes, and extendable elements. The trend of hosting more complex and bigger appendages, essential for high-precision scientific applications, made orbiting satellites more susceptible to performance loss or degradation due to structural damages. In this scenario, Structural Health Monitoring strategies can be used to evaluate the health status of satellite substructures. However, in particular when analysing large appendages, traditional approaches may not be sufficient to identify local damages, as they will generally induce less observable changes in the system dynamics yet cause a relevant loss of payload data and information. This paper proposes a deep neural network to detect failures and investigate sensor sensitivity to damage classification for an orbiting satellite hosting a distributed network of accelerometers on a large mesh reflector antenna. The sensors-acquired time series are generated by using a fully coupled 3D simulator of the in-orbit attitude behaviour of a flexible satellite, whose appendages are modelled by using finite element techniques. The machine learning architecture is then trained and tested by using the sensors’ responses gathered in a composite scenario, including not only the complete failure of a structural element (structural break) but also an intermediate level of structural damage. The proposed deep learning framework and sensors configuration proved to accurately detect failures in the most critical area or the structure while opening new investigation possibilities regarding geometrical properties and sensor distribution