Neurodegenerative diseases: molecular mechanisms and new strategies for neuroprotection

The term neurodegeneration defines numerous conditions that modify neuron’s normal functions in the human brain where is possible to observe a progressive and consistent neuronal loss. The mechanisms involved in neurodegenerative chronic and acute diseases evolution are not completely understood yet, however they share common characteristics such as misfolded proteins, oxidative stress, inflammation, excitotoxicity, and neuronal loss. Many studies have shown the frequency to develop neurodegenerative chronic diseases several years after an acute brain injury. In addition, many patients show, after a traumatic brain injury, motor and cognitive manifestations that are close to which are observed in neurodegenerative chronic patients. For this reason it is evident how is fundamental the concept of neuroprotection as a way to modulate the neurodegenerative processes evolution. Neuroinflammation, oxidative stress and the apoptotic process may be functional targets where operate to this end. Taking into account these considerations, the aim of the present study is to identify potential common pathogenetic pathways in neurodegenerative diseases using an integrated approach of preclinical studies. The goal is to delineate therapeutic strategies for the prevention of neuroinflammation, neurodegeneration and dysfunctions associated to Parkinson’s disease (PD) and cerebral ischemia. In the present study we used a murine model of PD treated with an isothiocyanate, 6-MSITC, able to quench ROS formation, restore the antioxidant GSH system, slow down the apoptotic neuronal death and counteract motor dysfunction induced by 6-OHDA. In the second study we utilized a transgenic mouse model knockout for CD36 receptor to investigate the inflammation involvement in a long term study of MCAo, which shows a better outcome after the damage induced. In conclusion, results in this study allow underlying the connection among these pathologies, and the importance of a neuroprotective strategy able to restore neurons activity where current drugs therapies have shown palliative but not healing abilities.

New knowledge, diagnostic and control tools to limit the impact of viral nervous necrosis (VNN) in the Mediterranean aquaculture sector

The role of aquaculture in satisfying the global seafood demand is essential. The expansion of the aquaculture sector and the intensification of its activities have enhanced the circulation of infectious agents. Among these, the nervous necrosis virus (NNV) represents the most widespread in the Mediterranean basin. The NNV is responsible for a severe neuropathological condition named viral nervous necrosis (VNN), impacting hugely on fish farms due to the serious disease-associated losses. Therefore, it is fundamental to develop new strategies to limit the impact of VNN in this area, interconnecting several aspects of disease management, diagnosis and prevention. This PhD thesis project, focusing on aquatic animals’ health, deals with these topics. The first two chapters expand the knowledge on VNN epidemiology and distribution, showing the possibility of interspecies transmission, persistent infections and a potential carrier role for invertebrates. The third study expands the horizon of VNN diagnosis, by developing a quick and affordable multiplex RT-PCR able to detect and simultaneously discriminate between NNV variants, reducing considerably the time and costs of genotyping. The fourth study, with the development of a fluorescent in situ hybridization technique and its application to aquatic vertebrates and invertebrates’ tissues, contributes to expand the knowledge on NNV distribution at cellular level, localizing also the replication site of the virus. Finally, the last study dealing with an in vitro evaluation of the NNV susceptibility to a commercial biocide, stress the importance to implement proper disinfectant procedures in fish farms to prevent virus spread and disease outbreaks.

New chemical modalities for leishmaniasis drug discovery

Leishmaniasis is one of the major parasitic diseases among neglected tropical diseases with a high rate of morbidity and mortality. Human migration and climate change have spread the disease from limited endemic areas all over the world, also reaching regions in Southern Europe, and causing significant health and economic burden. The currently available treatments are far from ideal due to host toxicity, elevated cost, and increasing rates of drug resistance. Safer and more effective drugs are thus urgently required. Nevertheless, the identification of new chemical entities for leishmaniasis has proven to be incredibly hard and exacerbated by the scarcity of well-validated targets. Trypanothione reductase (TR) represents one robustly validated target in Leishmania that fulfils most of the requirements for a good drug target. However, due to the large and featureless active site, TR is considered extremely challenging and almost undruggable by small molecules. This scenario advocates the development of new chemical entities by unlocking new modalities for leishmaniasis drug discovery. The classical toolbox for drug discovery has enormously expanded in the last decade, and medicinal chemists can now strategize across a variety of new chemical modalities and a vast chemical space, to efficiently modulate challenging targets and provide effective treatments. Beyond others, Targeted p Protein Degradation (TPD) is an emerging strategy that uses small molecules to hijack endogenous proteolysis systems to degrade disease-relevant proteins and thus reduce their abundance in the cell. Based on these considerations, this thesis aimed to develop new strategies for leishmaniasis drug discovery while embracing novel chemical modalities and navigating the chemical space by chasing unprecedented chemotypes. This has been achieved by four complementary projects. We believe that these next-generation chemical modalities for leishmaniasis will play an important role in what was previously thought to be a drug discovery landscape dominated by small molecules.

Computational methods for genome screening

Motivation An actual issue of great interest, both under a theoretical and an applicative perspective, is the analysis of biological sequences for disclosing the information that they encode. The development of new technologies for genome sequencing in the last years, opened new fundamental problems since huge amounts of biological data still deserve an interpretation. Indeed, the sequencing is only the first step of the genome annotation process that consists in the assignment of biological information to each sequence. Hence given the large amount of available data, in silico methods became useful and necessary in order to extract relevant information from sequences. The availability of data from Genome Projects gave rise to new strategies for tackling the basic problems of computational biology such as the determination of the tridimensional structures of proteins, their biological function and their reciprocal interactions. Results The aim of this work has been the implementation of predictive methods that allow the extraction of information on the properties of genomes and proteins starting from the nucleotide and aminoacidic sequences, by taking advantage of the information provided by the comparison of the genome sequences from different species. In the first part of the work a comprehensive large scale genome comparison of 599 organisms is described. 2,6 million of sequences coming from 551 prokaryotic and 48 eukaryotic genomes were aligned and clustered on the basis of their sequence identity. This procedure led to the identification of classes of proteins that are peculiar to the different groups of organisms. Moreover the adopted similarity threshold produced clusters that are homogeneous on the structural point of view and that can be used for structural annotation of uncharacterized sequences. The second part of the work focuses on the characterization of thermostable proteins and on the development of tools able to predict the thermostability of a protein starting from its sequence. By means of Principal Component Analysis the codon composition of a non redundant database comprising 116 prokaryotic genomes has been analyzed and it has been showed that a cross genomic approach can allow the extraction of common determinants of thermostability at the genome level, leading to an overall accuracy in discriminating thermophilic coding sequences equal to 95%. This result outperform those obtained in previous studies. Moreover, we investigated the effect of multiple mutations on protein thermostability. This issue is of great importance in the field of protein engineering, since thermostable proteins are generally more suitable than their mesostable counterparts in technological applications. A Support Vector Machine based method has been trained to predict if a set of mutations can enhance the thermostability of a given protein sequence. The developed predictor achieves 88% accuracy.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Studio di caratteri correlati a stress idrico in una collezione di cultivar di frumento duro (Triticum durum Desf.)

L’agricoltura si trova ad affrontare una diminuzione della disponibilità d’acqua ed una crescente domanda della produzione di cereali per scopi alimentari. Sono perciò necessarie strategie di coltivazione innovative per migliorare la produttività e nuovi genotipi migliorati nell'efficienza dell’uso delle risorse in condizioni di siccità. Questi rappresentano gli obietti principali del progetto “DROPS” (Drought tolerant yielding Plants) all’interno del quale ha avuto luogo il mio progetto di Dottorato. La mia attività di ricerca è stata svolta come segue: 1. Caratterizzazione molecolare di un panel di188 accessioni di frumento duro con marcatori SSR e DaRT; 2. Esperimenti in serra su 100 accessioni del panel per valutare la Water-Use Efficiency (WUE) in sei repliche secondo un Alpha Lattice design; 3. Prove sul campo, effettuate secondo un Alpha Lattice design, in due stagioni di crescita: a. 2010/11, valutazione di 100 accessioni presso l’Azienda sperimentale dell'Università di Cadriano (BO); b. 2011/12, valutazione del panel completo in 3 ambienti, con due diversi regimi irrigui In entrambi gli anni, abbiamo valutato caratteri agronomici correlati con il ciclo di sviluppo, la resa di granella e sue componenti, nonché diversi fattori ambientali e del suolo. Per quanto riguarda WUE, abbiamo trovato differenze altamente significative tra accessioni; inoltre, cinque accessioni hanno mostrato elevati valori di WUE e cinque accessioni valori molto bassi di WUE in tutte e sei le repliche. Gli esperimenti di campo nelle stagioni 2011 e 2012 hanno evidenziato differenze altamente significative tra le accessioni del panel per la maggior parte dei caratteri analizzati, confermando inoltre che il panel di fiorisce entro una settimana. L'esperimento del secondo anno ci ha permesso osservare un significativa interazione Genotipo X Ambiente. Questi risultati saranno integrati con ulteriori analisi QTL, per identificare regioni cromosomiche coinvolte nel controllo genetico dei caratteri di interesse e verificare la stabilità dei QTL in diversi ambienti.

Farming and processing stategies for improving poultry meat quality

The purpose of the PhD research was the identification of new strategies of farming and processing, with the aim to improve the nutritional and technological characteristics of poultry meat. Part of the PhD research was focused on evaluation of alternative farming systems, with the aim to increase animal welfare and to improve the meat quality and sensorial characteristics in broiler chickens. It was also assessed the use of innovative ingredients for marination of poultry meat (sodium bicarbonate and natural antioxidants) The research was developed by studying the following aspects: - Meat quality characteristics, oxidative stability and sensorial traits of chicken meat obtained from two different farming systems: free range vs conventional; - Meat quality traits of frozen chicken breast pre-salted using increasing concentrations of sodium chloride; - Use of sodium bicarbonate in comparison with sodium trypolyphosphate for marination of broiler breast meat and phase; - Marination with thyme and orange essential oils mixture to improve chicken meat quality traits, susceptibility to lipid oxidation and sensory traits. The following meat quality traits analyseswere performed: Colour, pH, water holding capacity by conventional (gravimetric methods, pressure application, centrifugation and cooking) and innovative methods (low-field NMR and DSC analysis) ability to absorb marinade soloutions, texture (shear force using different probes and texture profile analysis), proximate analysis (moisture, proteins, lipids, ash content, collagen, fatty acid), susceptibility to lipid oxidation (determinations of reactive substances with thiobarbituric acid and peroxide value), sensorial analysis (triangle test and consumer test).

The elderly health status and its correlation with ageing biomarkers: the European Project Mark-Age

According to the latest statistics projections formulated by Eurostat, the proportion of elderly EU-27’s population aged over 65 years old is predicted to increase from 17.5 % in 2011 to 29.5 % by 2060. This "population explosion" makes extremely important to identify the different genetic and molecular mechanisms which underpin the morbidity and mortality along with new strategies able to counteract or slow down its progress. In this scenario fits the European Project MARK-AGE whose aim was to identify a robust set of biomarkers of human ageing able to discriminate between chronological and biological ageing and to derive a model for healthy ageing through the analysis of three populations from different European countries, supposed to be characterized by different ageing rate: 1. Subjects representing the “Normal” or “Physiological” aging. 2. Subjects representing the “successful” or “decelerate” aging 3. Subjects representing the “accelerated” aging. The aim of this work was to recruit and characterize volunteers, to perform an accurate analysis of the health status of elderly recruited subjects (60-79 years) verifying any possible dissimilarity in their aging trajectories, to identify a set of robust ageing biomarkers and investigate possible correlations between ageing biomarkers and health status of recruited volunteers. The model proposed by MARK-AGE Project regarding different ageing trajectories has been confirmed and several ageing biomarkers have been identified.

Crystal Engineering of bright luminescent copper iodide clusters with phosphorus and nitrogen-based ligands

Copper(I) halide clusters are recently considered as good candidate for optoelectronic devices such as OLEDs . Although the copper halide clusters, in particular copper iodide, are very well known since the beginning of the 20th century, only in the late ‘70s the interest on these compounds grew dramatically due their particular photophysical behaviour. These complexes are characterized by a dual triplet emission bands, named Cluster Centred (3CC) and Halogen-to-Ligand charge transfer (3XLCT), the intensities of which are strictly related with the temperature. The CC transition, due to the presence of a metallophylic interactions, is prevalent at ambient temperature while the XLCT transition, located preferentially on the ligand part, became more prominent at low temperature. Since these pioneering works, it was easy to understand the photophysical properties of this compounds became more interesting in solid-state respect to solution with an improvement in emission efficiency. In this work we aim to characterize in SS organocopper(I)iodide compounds to valuate the correlation between the molecular crystal structure and the photophysical properties. It is also considered to hike new strategies to synthesize CuI complexes from the wet reactions to the more green solvent free methods. The advantages in using these strategies are evident but, obtain a single crystal suitable for SCXRD analysis from these batches is quite impossible. The structure solution still remains the key point in this research so we tackle this problem solving the structure by X-ray powder diffraction data. When the sample was fully characterized we moved to design and development of the associated OLED-device. Since copper iodide complexes are often insoluble in organic solvents, the high vacuum deposition technique is preferred. A new non-conventional deposition process have also been proposed to avoid the low complex stability in this practice with an in-situ complex formation in a layer-by layer deposition route.

The role of bifidobacteria in newborn health and the intestinal microbial balance

Gut microbial acquisition during the early stage of life is an extremely important event since it affects the health status of the host. In this contest the healthy properties of the genus Bifidobacterium have a central function in newborns. The aim of this thesis was to explore the dynamics of the gut microbial colonization in newborns and to suggest possible strategies to maintain or restore a correct balance of gut bacterial population in infants. The first step of this work was to review the most recent studies on the use of probiotics and prebiotics in infants. Secondly, in order to prevent or treat intestinal disorders that may affect newborns, the capability of selected Bifidobacterium strains to reduce the amount of Enterobacteriaceae and against the infant pathogen Streptococcus agalactiae was evaluated in vitro. Furthermore, the ability of several commercial fibers to stimulate selectively the growth of bifidobacterial strains was checked. Finally, the gut microbial composition in the early stage of life in response to the intrapartum antibiotic prophylaxis (IAP) against group B Streptococcus was studied using q-PCR, DGGE and next generation sequencing. The results globally showed that Bifidobacterium breve B632 strain is the best candidate for the use in a synbiotic product coupled to a mixture of two selected prebiotic fibers (galactooligosaccharides and fructooligosaccharides) for gastrointestinal disorders in infants. Moreover, the early gut microbial composition was affected by IAP treatment with infants showing lower counts of Bifidobacterium spp. and Bacteroides spp. coupled to a decrement of biodiversity of bacteria, compared to control infants. These studies have shown that IAP could affect the early intestinal balance in infants and they have paved the way to the definition of new strategies alternative to antibiotic treatment to control GBS infection in pregnant women.

Homoleptic and Heteroleptic Metal Carbonyl Clusters and Nanoclusters

This Thesis aims at presenting the general results achieved during my PhD, that was focused on the study and characterisation of new homoleptic and heteroleptic metal carbonyl clusters. From a dimensional point of view, the nuclearity of such species ranges from 2 to 44 metal atoms. Lower nuclearity compounds may be viewed as polymetallic complexes, whereas higher nuclearity species can reach the nanocluster size, by resembling to ultrasmall nanoparticles (USNPs). Initially, my research was focused on the investigation of small MCCs stabilised by N-Heterocyclic carbene (NHCs) ligands. At this regard, a general strategy for the synthesis of mono-anionic [Fe(CO)4(MNHC)]− and neutral Fe(CO)4(MNHC)2, Co(CO)4(MNHC) (M = Cu, Ag, Au; NHC = IMes, IPr) species has been developed. Furthermore, during this investigation, neutral trimetallic Fe(CO)4(MNHC)(M’NHC) (M, M’ = Cu, Ag, Au; M ≠ M'; NHC = IPr) and neutral heteroleptic Fe(CO)4(MNHC)(MNHC’) (M = Au; NHC = IMes, IPr) compounds have been isolated. Thermal treatment turned out to be an efficient method for the growth of the dimension of MCCs. Indeed, species of the type [M3Fe3(CO)12]3– and [M4Fe4(CO)16]4– (M = Ag, Au) as well as larger clusters were formed during the thermal treatment of the new Fe-M (M = Ag, Cu, Au) carbonyl compounds. These species inspired the investigation of promising reaction paths for the synthesis of Fe-M (M = Ag, Cu, Au) carbonyl compounds devoid of ancillary ligands and alloy MCCs, such as the heterometallic [MxM’5-xFe4(CO)16]3− (M, M' = Cu, Ag, Au; M ≠ M'; x = 0-5) carbonyl clusters. The second part of this Thesis regards high nuclearity MCCs. In particular, new strategies for the growth of platinum carbonyl clusters involving, for instance, the employment of bidentate phosphines are described, as well as the syntheses and the thermal decomposition of new Ni-M (Pd, Pt) carbonyl clusters.

Small molecules exploiting emerging therapeutic opportunities for breast cancer treatment

Among the different types of breast cancer (BC), the estrogen receptor positive (ER+) subtype, which requires estrogens for its growth and proliferation, is the most common, while triple negative BC, characterized by the absence of ER, progesterone receptor and human epidermal growth factor receptor 2, often leads to poor prognosis. First-line therapies for the treatment of ER+ BC act either by suppressing estrogen production, through the inhibition of aromatase (AR) enzyme, or by blocking estrogen prooncogenic activity, via the modulation/degradation of ERs. The serious side effects and the intrinsic or acquired resistance phenomena that arise with prolonged use of these drugs limit their therapeutic application, stimulating the search for new strategies to face this disease. In this context, the development of dual acting aromatase inhibitors, able to target both the orthosteric and the recently identified allosteric pockets of AR could be an opportunity to fight ER+ BC. Another promising strategy could be the development of multitarget compounds, targeting both AR and ERs. In this scenario, here we designed and synthesized two series of new xanthones or more flexible benzophenones as potential dual acting aromatase inhibitors. Moreover, inspired from tamoxifen metabolites and a literature compound endowed with activity on both AR and ER, different structurally related series of potential multitarget compounds were developed. The biological results showed that some of the new molecules were promising candidates for further development. It was recently observed that the lately discovered histamine H4 receptor is expressed in human breast tissue, displaying a key role in biological processes mediated by histamine such as cell proliferation, senescence, and apoptosis in malignant cells, representing a potential target in triple negative BC. Thus, a broad series of methyl quinazoline sulfonamides, carrying different functional groups on the sulfonamide moiety, were designed and synthesized as potential H4 receptor ligands.

Unbalanced R-loops and micronuclei induced by DNA topoisomerase I poisons in cancer cells

Topoisomerase I (Top1) poisons are among the most clinically-effective drugs used for colon, ovary and lung cancers. Unpublished data from our lab have recently revealed that the structurally-unrelated Top1 poisons, Camptothecin (CPT) and Indimitecan (LMP776), induce the formation of micronuclei (MNi) in human cancer cells. In addition, MNi trigger an innate immune gene response by stimulating the cGAS/STING pathway. As the mechanisms of MNi formation are not fully determined, our aim is here to establish how MNi form after Top1 poisoning. Using immunofluorescence assays and EdU labelling of nascent DNAs, our results show that, after 24 hours of recovery, a short treatment with sub-cytotoxic doses of Top1 poisons induces the formation of MNi that do not contain newly synthetized (EdU+) DNA. We also saw that Top1 poisons delay replication machinery reducing EdU incorporation and produce significant levels of the damage markers γH2AX and p53BP1 in S-phase cells but not in G1 and G2/M cells. The results also show that MNi formation is dependent on R-loops, as RNaseH1 overexpression markedly reduces Top1 induced MNi. Genome-wide mapping of R-loops by DRIP-seq technique revealed that R-loop levels are both decreased and increased by CPT. In particular, increased R-loops are mainly found at active genes and always overlapped with Top1cc sites. We also found that increased R-loops overlap with lamina-associated chromatin domains while decreased R-loops correlate with replication origin sites. Overall, our data are consistent with the formation of MNi due to R-loop increase and under-replication at specific regions caused by Top1 poisons. These results will eventually help in developing new strategies for effective personalized interventions by using Top1-targeted compounds as immuno-modulators in cancer patients.

Identificazione di nuove strategie per la valutazione della malattia minima residua nel Mieloma Multiplo: la Biopsia Liquida

Il Mieloma Multiplo (MM) è una patologia neoplastica delle cellule B caratterizzata dalla proliferazione di più cloni di plasmacellule portatrici di diverse anomalie genomiche. Il MM presenta tipicamente un’eterogeneità genomica spaziale e intraclonale, che rende l’aspirato midollare "a singolo sito", attualmente utilizzato per la valutazione della malattia residua (MRD) dopo trattamento, non realmente informativo sulla taglia di malattia e sul panorama genomico della malattia. In considerazione della crescente importanza che sta assumendo la valutazione della MRD, i test per monitorarla dovrebbero essere non invasivi, affidabili e in grado di rappresentare le eterogeneità che caratterizzano il MM. Il presente studio ha permesso di dimostrare la possibilità di utilizzare la biopsia liquida, una metodica innovativa e non invasiva, per caratterizzare i pazienti con MM attivo o con MM smoldering ad alto rischio di evoluzione (HR-SMM) e per determinale l’MRD nei pazienti sottoposti a terapia di prima linea, integrando le metodiche attualmente validate. Nei pazienti arruolati nel presente studio è stato possibile identificare la frazione tumorale di DNA libero circolante (cfDNA-TF) nel sangue periferico, ed è stato possibile caratterizzare la malattia da un punto di vista qualitativo, dimostrando un’elevata concordanza del profilo genomico tra DNA libero circolante e DNA midollare (100% nei pazienti con HR-SMM e 86% nei pazienti con MM attivo). L’esecuzione seriata di biopsie liquide in corso di terapia, con un follow-up mediano di 24 mesi, ha mostrato una rapida e netta riduzione della cfDNA-TF xdalle prime fasi di terapia, con una tendenza a mantenersi mediamente sotto la soglia di sensibilità della metodica anche nelle fasi successive, indipendentemente dall’eventuale persistenza di MRD individuabile a livello midollare o mediante PET-CT. Con un follow-up più lungo probabilmente sarà possibile valutare meglio la capacità di questa metodica di affiancare o eventualmente sostituire l’aspirato midollare.

Test vector generation for the phase II ATLAS event filter trigger upgrade

In the near future, the LHC experiments will continue to be upgraded as the LHC luminosity will increase from the design 1034 to 7.5 × 1034, with the HL-LHC project, to reach 3000 × f b−1 of accumulated statistics. After the end of a period of data collection, CERN will face a long shutdown to improve overall performance by upgrading the experiments and implementing more advanced technologies and infrastructures. In particular, ATLAS will upgrade parts of the detector, the trigger, and the data acquisition system. It will also implement new strategies and algorithms for processing and transferring the data to the final storage. This PhD thesis presents a study of a new pattern recognition algorithm to be used in the trigger system, which is a software designed to provide the information necessary to select physical events from background data. The idea is to use the well-known Hough Transform mathematical formula as an algorithm for detecting particle trajectories. The effectiveness of the algorithm has already been validated in the past, independently of particle physics applications, to detect generic shapes in images. Here, a software emulation tool is proposed for the hardware implementation of the Hough Transform, to reconstruct the tracks in the ATLAS Trigger and Data Acquisition system. Until now, it has never been implemented on electronics in particle physics experiments, and as a hardware implementation it would provide overall latency benefits. A comparison between the simulated data and the physical system was performed on a Xilinx UltraScale+ FPGA device.