Molecular Systematics and Traits Evolution in Phasmatodea Leach, 1815 (Hexapoda; Insecta)

Phasmatodea Leach, 1815 (Hexapoda; Insecta) is a polyneopteran order which counts approximately 3000 described species, often known for their remarkable forms of mimicry. In this thesis, I provide a comprehensive systematic framework which includes over 180 species never considered in a phylogenetic framework: the latter can facilitate a better understanding of the processes underlying phasmids evolutionary history. The clade represents in fact an incredible testing ground to study trait evolution and its striking disparity of reproductive strategies and wing morphologies have been of great interest to the evolutionary biology community. Phasmids wings represent one of the first and most notable rejection of Dollo’s law and they played a central role in initiating a long- standing debate on the irreversibility of complex traits loss. Macroevolutionary analyses presented here confirm that wings evolution in phasmids is a reversible process even when possible biases - such as systematic uncertainty and trait-dependent diversification rates - are considered. These findings remark how complex traits can evolve in a dynamic, reversible manner and imply that their molecular groundplan can be preserved despite its phenotypical absence. This concept has been further tested with phylogenetic and transcriptomic approaches in two phasmids parthenogenetic lineages and a bisexual congeneric of the European Bacillus species complex. Leveraging a gene co-expression network approach, male gonad associated genes were retrieved in the bisexual species and then their modifications in the parthenogens were charachterized. Pleiotropy appears to constrain gene modifications associated to male reproductive structures after their loss in parthenogens, so that the lost trait molecular groundplan can be largely preserved in both transcription patterns and sequence evolution. Overall, the results presented in this thesis contribute to shape our understanding of the interplay between the phenotypic and molecular levels in trait evolution.

Longitudinal evolution of cognitive functions in patients with multiple system atrophy: a prospective study

Introduction and Background: Multiple system atrophy (MSA) is a sporadic, adult-onset, progressive neurodegenerative disease characterized clinically by parkinsonism, cerebellar ataxia, and autonomic failure. We investigated cognitive functions longitudinally in a group of probable MSA patients, matching data with sleep parameters. Patients and Methods: 10 patients (7m/3f) underwent a detailed interview, a general and neurological examination, laboratory exams, MRI scans, a cardiovascular reflexes study, a battery of neuropsychological tests, and video-polysomnographic recording (VPSG). Patients were revaluated (T1) a mean of 16±5 (range: 12-28) months after the initial evaluation (T0). At T1, the neuropsychological assessment and VPSG were repeated. Results: The mean patient age was 57.8±6.4 years (range: 47-64) with a mean age at disease onset of 53.2±7.1 years (range: 43-61) and symptoms duration at T0 of 60±48 months (range: 12-144). At T0, 7 patients showed no cognitive deficits while 3 patients showed isolated cognitive deficits. At T1, 1 patient worsened developing multiple cognitive deficits from a normal condition. At T0 and T1, sleep efficiency was reduced, REM latency increased, NREM sleep stages 1-2 slightly increased. Comparisons between T1 and T0 showed a significant worsening in two tests of attention and no significant differences of VPSG parameters. No correlation was found between neuropsychological results and VPSG findings or RBD duration. Discussion and Conclusions: The majority of our patients do not show any cognitive deficits at T0 and T1, while isolated cognitive deficits are present in the remaining patients. Attention is the cognitive function which significantly worsened. Our data confirm the previous findings concerning the prevalence, type and the evolution of cognitive deficits in MSA. Regarding the developing of a condition of dementia, our data did not show a clear-cut diagnosis of dementia. We confirm a mild alteration of sleep structure. RBD duration does not correlate with neuropsychological findings.

From core rigidities to dynamic capabilities: the role of external knowledge. A multiple case study

This study focuses on the processes of change that firms undertake to overcome conditions of organizational rigidity and develop new dynamic capabilities, thanks to the contribution of external knowledge. When external contingencies highlight firms’ core rigidities, external actors can intervene in change projects, providing new competences to firms’ managers. Knowledge transfer and organizational learning processes can lead to the development of new dynamic capabilities. Existing literature does not completely explain how these processes develop and how external knowledge providers, as management consultants, influence them. Dynamic capabilities literature has become very rich in the last years; however, the models that explain how dynamic capabilities evolve are not particularly investigated. Adopting a qualitative approach, this research proposes four relevant case studies in which external actors introduce new knowledge within organizations, activating processes of change. Each case study consists of a management consulting project. Data are collected through in-depth interviews with consultants and managers. A large amount of documents supports evidences from interviews. A narrative approach is adopted to account for change processes and a synthetic approach is proposed to compare case studies along relevant dimensions. This study presents a model of capabilities evolution, supported by empirical evidence, to explain how external knowledge intervenes in capabilities evolution processes: first, external actors solve gaps between environmental demands and firms’ capabilities, changing organizational structures and routines; second, a knowledge transfer between consultants and managers leads to the creation of new ordinary capabilities; third, managers can develop new dynamic capabilities through a deliberate learning process that internalizes new tacit knowledge from consultants. After the end of the consulting project, two elements can influence the deliberate learning process: new external contingencies and changes in the perceptions about external actors.

The impact of intraclonal heterogeneity on the outcomes of Multiple Myeloma patients treated with new drugs

Understanding the biology of Multiple Myeloma (MM) is of primary importance in the struggle to achieve a cure for this yet incurable neoplasm. A better knowledge of the mechanism underlying the development of MM can guide us in the development of new treatment strategies. Studies both on solid and haematological tumours have shown that cancer comprises a collection of related but subtly different clones, a feature that has been termed “intra-clonal heterogeneity”. This intra-clonal heterogeneity is likely, from a “Darwinian” natural selection perspective, to be the essential substrate for cancer evolution, disease progression and relapse. In this context the critical mechanism for tumour progression is competition between individual clones (and cancer stem cells) for the same microenvironmental “niche”, combined with the process of adaptation and natural selection. The Darwinian behavioural characteristics of cancer stem cells are applicable to MM. The knowledge that intra-clonal heterogeneity is an important feature of tumours’ biology has changed our way to addressing cancer, now considered as a composite mixture of clones and not as a linear evolving disease. In this variable therapeutic landscape it is important for clinicians and researchers to consider the impact that evolutionary biology and intra-clonal heterogeneity have on the treatment of myeloma and the emergence of treatment resistance. It is clear that if we want to effectively cure myeloma it is of primarily importance to understand disease biology and evolution. Only by doing so will we be able to effectively use all of the new tools we have at our disposal to cure myeloma and to use treatment in the most effective way possible. The aim of the present research project was to investigate at different levels the presence of intra-clonal heterogeneity in MM patients, and to evaluate the impact of treatment on clonal evolution and on patients’ outcomes.

An efficient Jeans modelling of axisymmetric galaxies with multiple stellar components

Dynamical models of stellar systems represent a powerful tool to study their internal structure and dynamics, to interpret the observed morphological and kinematical fields, and also to support numerical simulations of their evolution. We present a method especially designed to build axisymmetric Jeans models of galaxies, assumed as stationary and collisionless stellar systems. The aim is the development of a rigorous and flexible modelling procedure of multicomponent galaxies, composed of different stellar and dark matter distributions, and a central supermassive black hole. The stellar components, in particular, are intended to represent different galaxy structures, such as discs, bulges, halos, and can then have different structural (density profile, flattening, mass, scale-length), dynamical (rotation, velocity dispersion anisotropy), and population (age, metallicity, initial mass function, mass-to-light ratio) properties. The theoretical framework supporting the modelling procedure is presented, with the introduction of a suitable nomenclature, and its numerical implementation is discussed, with particular reference to the numerical code JASMINE2, developed for this purpose. We propose an approach for efficiently scaling the contributions in mass, luminosity, and rotational support, of the different matter components, allowing for fast and flexible explorations of the model parameter space. We also offer different methods of the computation of the gravitational potentials associated of the density components, especially convenient for their easier numerical tractability. A few galaxy models are studied, showing internal, and projected, structural and dynamical properties of multicomponent galaxies, with a focus on axisymmetric early-type galaxies with complex kinematical morphologies. The application of galaxy models to the study of initial conditions for hydro-dynamical and $N$-body simulations of galaxy evolution is also addressed, allowing in particular to investigate the large number of interesting combinations of the parameters which determine the structure and dynamics of complex multicomponent stellar systems.

Hydrodynamic simulations of multiple stellar populations in globular clusters

The presence of multiple stellar populations in globular clusters (GCs) is now well accepted, however, very little is known regarding their origin. In this Thesis, I study how multiple populations formed and evolved by means of customized 3D numerical simulations, in light of the most recent data from spectroscopic and photometric observations of Local and high-redshift Universe. Numerical simulations are the perfect tool to interpret these data: hydrodynamic simulations are suited to study the early phases of GCs formation, to follow in great detail the gas behavior, while N-body codes permit tracing the stellar component. First, we study the formation of second-generation stars in a rotating massive GC. We assume that second-generation stars are formed out of asymptotic giant branch stars (AGBs) ejecta, diluted by external pristine gas. We find that, for low pristine gas density, stars mainly formed out of AGBs ejecta rotate faster than stars formed out of more diluted gas, in qualitative agreement with current observations. Then, assuming a similar setup, we explored whether Type Ia supernovae affect the second- generation star formation and their chemical composition. We show that the evolution depends on the density of the infalling gas, but, in general, an iron spread is developed, which may explain the spread observed in some massive GCs. Finally, we focused on the long-term evolution of a GC, composed of two populations and orbiting the Milky Way disk. We have derived that, for an extended first population and a low-mass second one, the cluster loses almost 98 percent of its initial first population mass and the GC mass can be as much as 20 times less after a Hubble time. Under these conditions, the derived fraction of second-population stars reproduces the observed value, which is one of the strongest constraints of GC mass loss.

New indicators of star cluster dynamical evolution

This thesis presents a study of globular clusters (GCs), based on analysis of Monte Carlo simulations of globular clusters (GCs) with the aim to define new empirical parameters measurable from observations and able to trace the different phases of their dynamical evolution history. During their long term dynamical evolution, due to mass segregation and and dynamical friction, massive stars transfer kinetic energy to lower-mass objects, causing them to sink toward the cluster center. This continuous transfer of kinetic energy from the core to the outskirts triggers the runaway contraction of the core, known as "core collapse" (CC), followed by episodes of expansion and contraction called gravothermal oscillations. Clearly, such an internal dynamical evolution corresponds to significant variations also of the structure of the system. Determining the dynamical age of a cluster can be challenging as it depends on various internal and external properties. The traditional classification of GCs as CC or post-CC systems relies on detecting a steep power-law cusp in the central density profile, which may not always be reliable due to post-CC oscillations or other processes. In this thesis, based on the normalized cumulative radial distribution (nCRD) within a fraction of the half-mass radius is analyzed, and three diagnostics (A5, P5, and S2.5) are defined. These diagnostics show sensitivity to dynamical evolution and can distinguish pre-CC clusters from post-CC clusters.The analysis performed using multiple simulations with different initial conditions, including varying binary fractions and the presence of dark remnants showed the time variations of the diagnostics follow distinct patterns depending on the binary fraction and the retention or ejection of black holes. This analysis is extended to a larger set of simulations matching the observed properties of Galactic GCs, and the parameters show a potential to distinguish the dynamical stages of the observed clusters as well.

Grant-free protocols for massive multiple access

In next generation Internet-of-Things, the overhead introduced by grant-based multiple access protocols may engulf the access network as a consequence of the proliferation of connected devices. Grant-free access protocols are therefore gaining an increasing interest to support massive multiple access. In addition to scalability requirements, new demands have emerged for massive multiple access, including latency and reliability. The challenges envisaged for future wireless communication networks, particularly in the context of massive access, include: i) a very large population size of low power devices transmitting short packets; ii) an ever-increasing scalability requirement; iii) a mild fixed maximum latency requirement; iv) a non-trivial requirement on reliability. To this aim, we suggest the joint utilization of grant-free access protocols, massive MIMO at the base station side, framed schemes to let the contention start and end within a frame, and succesive interference cancellation techniques at the base station side. In essence, this approach is encapsulated in the concept of coded random access with massive MIMO processing. These schemes can be explored from various angles, spanning the protocol stack from the physical (PHY) to the medium access control (MAC) layer. In this thesis, we delve into both of these layers, examining topics ranging from symbol-level signal processing to succesive interference cancellation-based scheduling strategies. In parallel with proposing new schemes, our work includes a theoretical analysis aimed at providing valuable system design guidelines. As a main theoretical outcome, we propose a novel joint PHY and MAC layer design based on density evolution on sparse graphs.