RNA modifications and post-transcriptional control in cancer and stem cells

Splicing and translation are two of the key steps of post-transcriptional regulation of gene expression. Their tight regulation is essential for development, whereas their deregulation is involved in cancer pathogenesis. Nevertheless, many of the molecular mechanisms controlling these processes are still unknown. Hence, the main aim of this thesis is to elucidate novel regulatory mechanisms that affect splicing and translation in stem and cancer cells.An emerging layer of regulation is represented by RNA modifications, evolutionarily conserved hallmarks of coding and non-coding RNA. Indeed, small nuclear RNA (snRNA) and ribosomal RNA (rRNA), the RNA components of the spliceosome and ribosome, are decorated with pseudouridines (Ψ) and 2’-O-methyl groups (2’OMe) within key functional regions. These modifications are introduced by RNA-dependent small ribonucleoproteins (snoRNPs), guided by snoRNAs and scaRNAs. In Paper I I identified the role of the SCARNA15-guided U2 snRNA-Ψ in driving alternative splicing events affecting the pivotal tumor suppressor p53 and redox homeostasis in cancer cells. In Paper II I unraveled the importance of the rRNA pseudouridylation machinery for the homeostasis of the hematopoietic system and the reconstitution capacity of HSCs in vivo. In Paper III I discovered a developmentally regulated 28S rRNA-2’OMe guided by SNORD123. The loss of this modification affected hESCs differentiation and caused translation defects perturbing the resistance to A-site specific antibiotics in fibroblasts. In Paper IV I highlighted a novel interplay between splicing and translation. Here, I uncovered a translationally regulated splicing factor, SF3A3, upon oncogenic stress which affects splicing of genes contributing to mitochondrial homeostasis and metabolism and that influences tumorigenesis of MYC-driven breast cancer.In sum, this doctoral thesis explores novel post-transcriptional regulatory mechanisms, especially involving RNA modification modulation and dysregulation, with the aim to broaden the knowledge on stem and cancer cells functioning and to contribute to the discovery of future clinical implications

The use of the Iowa physical science aptitude test in the prediction of success in the school of Engineering and Architecture of Kansas State College

Call number: LD2668 .T4 1952 B43Master of Scienc

A new approach to the analysis of electromagnetic FEM simulations results at electric field singularities

A new methodology to the analysis of the results of Finite-Element Modeling (FEM) simulations at electric field singularities is proposed. The method, that can be easily applied in the post-processing phase of the electromagnetic FEM analysis workflow, is based on the weighted averaging of the calculated electric field magnitude within small volumes including the singularity point under investigation. In the paper, the proposed approach is applied to the electrical stress analysis of a high-voltage device modeled by means of a commercial electromagnetic FEM tool. In comparison to the conventional metric of the maximum field evaluation usually adopted for the analysis of electrical stress in insulators, our approach features several advantages: (i) the outcome of the analysis is independent of the numerical grid refinement at the singularity, thus allowing direct comparison of calculated electric field with the material dielectric strength; (ii) the method is robust against slight modifications of the geometrical shape of the singularity; (iii) on the other hand, for a given shape, the analysis outcome responds to significant variations of the singularity size or, in other words, of its sharpness; (iv) in the analysis of high-voltage devices, the approach can be applied for the estimation of the discharge volumes corresponding to different singularity types of different device geometries. In the paper, the new methodology is explained in details and is applied to simple but significant case studies

Il Lemma di Milnor-Švarc e le sue implicazioni geometriche e topologiche

Questa tesi ha come argomento principale il Lemma di Milnor-Švarc, un risultato fondamentale riguardante la teoria geometrica dei gruppi. Riassumendo brevemente, tale teorema afferma quanto segue. Dato un gruppo che agisce su di uno spazio metrico, se opportune ipotesi sono verificate, risulta possibile affermare che il gruppo sia finitamente generato e lo spazio metrico sia quasi-isometrico a tale gruppo. In particolare, lo scopo della tesi sarà proprio quello di chiarire il significato del concetto di quasi-isometria e di spiegare in maniera puntuale quali siano le ipotesi del teorema ed il perché queste siano necessarie, nonché mostrare alcune delle principali conseguenze del Lemma di Milnor-Švarc. Sfruttando la versione topologica del Lemma di Milnor-Švarc, saremo in grado di mostrare che se (M, g) è una varietà Riemanniana piatta, ovvero se il suo rivestimento universale è isometrico ad R^n, allora il gruppo fondamentale di M è quasi-isometrico allo spazio Euclideo. In particolare, saremo in grado di osservare che le superfici di genere g maggiore o uguale a 2 non possono essere piatte. Nella parte preliminare di questa tesi spiegheremo cosa si intende per grafo di Cayley di un gruppo finitamente generato, richiameremo brevemente i risultati fondamentali riguardanti la teoria dei rivestimenti e mostreremo alcuni risultati di geometria Riemanniana. Il secondo capitolo della tesi è totalmente incentrato sulla presentazione della "coarse geometry", spaziando tra i concetti di quasi-isometria, di metrica indotta su un grafo di Cayley arrivando, infine, alla crescita dei gruppi finitamente generati. Nel terzo capitolo verrà enunciato e dimostrato il Lemma di Milnor-Švarc nella sua versione quasi-geometrica. Nel quarto, ed ultimo, capitolo verranno presentate la sua versione topologica ed alcune rilevanti conseguenze ad essa associate

Self-Aware Thermal Management for High-Performance Computing Processors

Editor's note: Thermal management in high-performance multicore platforms has become exceedingly complex due to variable workloads, thermal heterogeneity, and long, thermal transients. This article addresses these complexities by sophisticated analysis of noisy thermal sensor readings, dynamic learning to adapt to the peculiarities of the hardware and the applications, and a dynamic optimization strategy. - Axel Jantsch, TU Wien - Nikil Dutt, University of California at Irvine

Continuous Learning of HPC Infrastructure Models using Big Data Analytics and In-Memory processing Tools

open4siThis work was supported, in parts, by the FP7 ERC Advance project MULTITHERMAN (g.a. 291125), by the EU H2020 FETHPC project ANTAREX (g.a. 67623) and by the EU H2020 FETHPC project Exanode (g.a. 671578).Exascale computing represents the next leap in the HPC race. Reaching this level of performance is subject to several engineering challenges such as energy consumption, equipment-cooling, reliability and massive parallelism. Model-based optimization is an essential tool in the design process and control of energy efficient, reliable and thermally constrained systems. However, in the Exascale domain, model learning techniques tailored to the specific supercomputer require real measurements and must therefore handle and analyze a massive amount of data coming from the HPC monitoring infrastructure. This becomes rapidly a 'big data' scale problem. The common approach where measurements are first stored in large databases and then processed is no more affordable due to the increasingly storage costs and lack of real-time support. Nowadays instead, cloud-based machine learning techniques aim to build on-line models using real-time approaches such as 'stream processing' and 'in-memory' computing, that avoid storage costs and enable fastdata processing. Moreover, the fast delivery and adaptation of the models to the quick data variations, make the decision stage of the optimization loop more effective and reliable. In this paper we leverage scalable, lightweight and flexible IoT technologies, such as the MQTT protocol, to build a highly scalable HPC monitoring infrastructure able to handle the massive sensor data produced by next-gen HPC components. We then show how state-of-the art tools for big data computing and analysis, such as Apache Spark, can be used to manage the huge amount of data delivered by the monitoring layer and to build adaptive models in real-time using on-line machine learning techniques.openBeneventi, Francesco; Bartolini, Andrea; Cavazzoni, Carlo; Benini, LucaBeneventi, Francesco; Bartolini, Andrea; Cavazzoni, Carlo; Benini, Luc

Production and Characterization of New Baeyer-Villiger Monooxygenases

The Baeyer-Villiger reaction is a very important oxidative reaction in organic synthesis that leads to the production of optically pure esters and lactones from ketones. It is typically performed by peroxyacids, oxydative reagents that are toxic, hazardous and lacking selectivity. By using "green chemistry", it is possible to perform the same reaction using "bio-catalyzers", enzymes named Baeyer-Villiger monoxygenases (BVMOs), a group of avin dependent monooxygenases, that use NAD(P)H and molecular oxygen in order to catalyze chemo-, regio-, and enantio-selective oxidative reactions. BVMOs have been identied in a large number of bacteria and fungi but only a restricted number of them is available in recombinant form. In order to discover novel BVMOs, new sources of enzymes will become important. Using bioinformatics tools, we have identied and selected ve new putative type I BVMOs from dierent organisms: Oryza sativa (Os; plant), Physcomitrella patens (Pp; moss), Cyanidioschyzon merolae (Cm; red alga), Trichodesmium erythraeum (Te; cyanobacterium), Haloterrigena turkmenica (Ht; archeabacterium). In particular, basing on most updated literature, the photosynthetic eukaryotes Oryza, Physcomitrella and Cyanidioschyzon would result very uncommon sources for BVMOs. The cloning and expression strategy used was the same for all the ve putative sequences. The very low solubility of the expressed proteins was the real bottleneck of the work. To overcome the solubility problem many strategies have been performed lowering the inducer concentration, the growth temperature and using chaperones. Adding on the culture an excess of ribo avin, the precursor of the FAD, results successful to obtain soluble avoproteins from Physcomitrella patens and Cyanidioschyzon merolae, showing the importance of the avin cofactor in the folding process. A biocatalytic characterisation of both expressed proteins was made at the Molecular Enzymology group of the Groningen Biomolecular Science and Biotechnology Institute (GBB), University of Groningen (The Netheralnds) headed by Prof. Dr. M.W. Fraaije, a main expert in avoenzymes and particularly in Baeyer-Villiger monooxygenses. Once veried their Baeyer-Villiger monooxyge-3 nase activity a condition optimization (pH, temperature and stability) has been performed; then the two proteins were tested to investigate their substrate speci-city. A steady-state study was carried out in order to obtain kinetics parameters and many conversions were made to determine their selectivity prole. The work presented led to discover new type I BVMOs enlarging the possibility to nd out novel and promising biocatalysts for oxidative reactions

Comunicazione visuale del cambiamento climatico su Instagram

Introduzione: Ci piacciono le immagini. Sono la prima cosa in assoluto che abbiamo visto [. . . ]. Danno forma ai nostri ricordi del mondo. Lo stesso accade nella scienza. Alcune immagini hanno definito i nostri passi in avanti nella comprensione dell\u2019universo; altre si sono dimostrate talmente efficaci nel comunicare la natura della realt\ue0 da essere diventate parte del processo del pensiero stesso, come i numeri o le lettere dell\u2019alfabeto. Altre ancora, altrettanto influenti, sono cos\uec familiari da passare inosservate nel procedimento scientifico, come parti del vocabolario della scienza di cui ci serviamo senza pensarci. L\u2019astrofisico e cosmologo John Barrow definisce la rappresentazione visuale della scienza come una "rivoluzione", e basta poco per accorgersi di quanto questa affermazione sia veritiera. Le immagini, un termine generale per definire fotografie, video e simulazioni digitali, non solo sono entrate a far parte della pratica della scienza, ma anche della sua comunicazione. Le immagini sono da sempre uno strumento potente, capace di smuovere gli animi e plasmare la percezione delle persone rispetto a un argomento. Basti pensare a una delle pi\uf9 iconiche fotografie di sempre, Earthrise, l\u2019immagine della Terra vista dalla Luna, scattata dall\u2019Apollo 8 nel 1968. Questa fotografia ha avuto un impatto cos\uec potente nel sensibilizzare le persone sulla fragilit\ue0 e unicit\ue0 del pianeta Terra, che si \ue8 posta come una delle radici del moderno movimento ambientalista..