The Influence of Baseline Metabolic Rate and Exercise Training on Cardio-Respiratory Dynamics

Speeding the VO2 kinetics results in a reduction of the O2 deficit. Two factors might determine VO2 kinetics: oxygen delivery to muscle (Tschakovsky and Hughson 1999) and a muscle 'metabolic inertia' (Grassi et al. 1996). Therefore, in study 1 we investigated VO2 kinetics and cardiovascular system adaptations during step exercise transitions in different regions of the moderate domain. In study 2 we investigated muscle oxygenation and cardio-pulmonary adaptations during step exercise tests before, after and over a period of training. Study 1 methods: Seven subjects (26 ± 8 yr; 176 ± 5 cm; 69 ± 6 kg) performed 4 types of step transition from rest (0-50W; 0-100W) or elevate baseline (25-75W; 25-125W). GET and VO2max were assessed before testing. O2 uptake and were measured during testing. Study 2 methods: 10 subjects (25 ± 4 yr; 175 ± 9 cm; 71 ± 12 kg) performed a step transition test (0 to 100 W) before, after and during 4 weeks of endurance training (ET). VO2max and GET were assessed before and after of ET (40 minutes, 3 times a week, 60% O2max). VO2 uptake, Q and deoxyheamoglobin were measured during testing. Study 1 results: VO2 τ and the functional gain were slower in the upper regions of the moderate domain. Q increased more abruptly during rest to work condition. Q τ was faster than VO2 τ for each exercise step. Study 2 results: VO2 τ became faster after ET (25%) and particularly after 1 training session (4%). Q kinetics changed after 4 training sessions nevertheless it was always faster than VO2 τ. An attenuation in ∆[HHb] /∆VO2 was detectible. Conclusion: these investigations suggest that muscle fibres recruitment exerts a influence on the VO2 response within the moderate domain either during different forms of step transition or following ET.

Data surveillance for infectious diseases: models, complex networks and machine learning

In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.

Knowledge Flows and Networks: the Interplay between Local and Global Linkages within Bangalore IT Cluster

This doctoral work gains deeper insight into the dynamics of knowledge flows within and across clusters, unfolding their features, directions and strategic implications. Alliances, networks and personnel mobility are acknowledged as the three main channels of inter-firm knowledge flows, thus offering three heterogeneous measures to analyze the phenomenon. The interplay between the three channels and the richness of available research methods, has allowed for the elaboration of three different papers and perspectives. The common empirical setting is the IT cluster in Bangalore, for its distinguished features as a high-tech cluster and for its steady yearly two-digit growth around the service-based business model. The first paper deploys both a firm-level and a tie-level analysis, exploring the cases of 4 domestic companies and of 2 MNCs active the cluster, according to a cluster-based perspective. The distinction between business-domain knowledge and technical knowledge emerges from the qualitative evidence, further confirmed by quantitative analyses at tie-level. At firm-level, the specialization degree seems to be influencing the kind of knowledge shared, while at tie-level both the frequency of interaction and the governance mode prove to determine differences in the distribution of knowledge flows. The second paper zooms out and considers the inter-firm networks; particularly focusing on the role of cluster boundary, internal and external networks are analyzed, in their size, long-term orientation and exploration degree. The research method is purely qualitative and allows for the observation of the evolving strategic role of internal network: from exploitation-based to exploration-based. Moreover, a causal pattern is emphasized, linking the evolution and features of the external network to the evolution and features of internal network. The final paper addresses the softer and more micro-level side of knowledge flows: personnel mobility. A social capital perspective is here developed, which considers both employees’ acquisition and employees’ loss as building inter-firm ties, thus enhancing company’s overall social capital. Negative binomial regression analyses at dyad-level test the significant impact of cluster affiliation (cluster firms vs non-cluster firms), industry affiliation (IT firms vs non-IT fims) and foreign affiliation (MNCs vs domestic firms) in shaping the uneven distribution of personnel mobility, and thus of knowledge flows, among companies.

Molecular and functional characterization of the chemotactic genes in the PCBs-degrader Pseudomonas pseudoalcaligenes KF707

Although bacteria represent the simplest form of life on Earth, they have a great impact on all living beings. For example the degrader bacterium Pseudomonas pseudoalcaligenes KF707 is used in bioremediation procedures for the recovery of polluted sites. Indeed, KF707 strain is know for its ability to degrade biphenyl and polychlorinated biphenyls - to which is chemotactically attracted - and to tolerate the oxydative stress due to toxic metal oxyanions such as tellurite and selenite. Moreover, in bioremediation processes, target compounds can be easily accessible to KF707 through biofilm formation. All these considerations suggest that KF707 is such a unique microorganism and this Thesis work has been focused on determining the molecular nature of some of the peculiar physiological traits of this strain. The genome project provided a large set of informations: putative genes involved in the degradation of aromatic and toxic compounds and associated to stress response were identified. Notably, multiple chemotactic operons and cheA genes were also found. Deleted mutants in the cheA genes were constructed and their role in motility, chemotaxis and biofilm formation were assessed and compared to those previously attributed to a cheA1 gene in a KF707 mutant constructed by a mini-Tn5 transposon insertion and which was impaired in motility and biofilm development. The results of this present Thesis work, taken together, were interpreted to suggest that in Pseudomonas pseudoalcaligenes KF707 strain, multiple factors are involved in these networks and they might play different roles depending on the environmental conditions. The ability of KF707 strain to produce signal molecules possibly involved in cell-to-cell communication, was also investigated: lack of a lux-like QS system - which is conversely widely present in Gram negative bacteria – keeps open the question about the actual molecular nature of KF707 quorum sensing mechanism.

Role of Reactive Oxygen Species in signalling and oxidative stress

Results reported in this Thesis contribute to the comprehension of the complicated world of “redox biology”. ROS regulate signalling pathways both in physiological responses and in pathogenesis and progression of diseases. In cancer cells, the increase in ROS generation from metabolic abnormalities and oncogenic signalling may trigger a redox adaptation response, leading to an up-regulation of antioxidant capacity in order to maintain the ROS level below the toxic threshold. Thus, cancer cells would be more dependent on the antioxidant system and more vulnerable to further oxidative stress induced by exogenous ROS-generating agents or compounds that inhibit the antioxidant system. Results here reported indicate that the development of new drugs targeting specific Nox isoforms, responsible for intracellular ROS generation, or AQP isoforms, involved in the transport of extracellular H2O2 toward intracellular targets, might be an interesting novel anti-leukaemia strategy. Furthermore, also the use of CSD peptide, which simulate the VEGFR-2 segregation into caveolae in the inactive form, might be a strategy to stop the cellular response to VEGF signalling. As above stated, in the understanding of the redox biology, it is also important to identify and distinguish the molecular effectors that maintain normal biological and physiological responses, such as agents that stimulate our adaptation systems and elevate our endogenous antioxidant defences or other protective systems. Data here reported indicate that the nutraceutical compound sulforaphane and the Klotho protein are able to stimulate the HO-1 and Prx-1 expression, as well as the GSH levels, confirming their antioxidant and protective role. Finally, results here reported demonstrated that Stevia extracts are involved in insulin regulated glucose metabolism, suggesting that the use of these compounds goes beyond their sweetening power and may also offer therapeutic benefits hence improving the quality of life.

Coupling instrumentation and methodology in the search for traces of life on the early Earth and Mars

Evaluating the nature of the earliest, often controversial, traces of life in the geological record (dating to the Palaeoarchaean, up to ~3.5 billion years before the present) is of fundamental relevance for placing constraints on the potential that life emerged on Mars at approximately the same time (the Noachian period). In their earliest histories, the two planets shared many palaeoenvironmental similarities, before the surface of Mars rapidly became inhospitable to life as we know it. Multi-scalar, multi-modal analyses of fossiliferous rocks from the Barberton greenstone belt of South Africa and the East Pilbara terrane of Western Australia are a window onto primitive prokaryotic ecoystems. Complementary petrographic, morphological, (bio)geochemical and nanostructural analyses of chert horizons and the carbonaceous material within using a wide range of techniques – including optical microscopy, SEM-EDS, Raman spectroscopy, PIXE, µCT, laser ablation ICP-MS, high-resolution TEM-based analytical techniques and secondary ion mass spectrometry – can characterise, at scales from macroscopic to nanoscopic, the fossilised biomes of the earliest Earth. These approaches enable the definition of the palaeoenvironments, and potentially metabolic networks, preserved in ancient rocks. Modifying these protocols is necessary for Martian exploration using rovers, since the range and power of space instrumentation is significantly reduced relative to terrestrial laboratories. Understanding the crucial observations possible using highly complementary rover-based payloads is therefore critical in scientific protocols aiming to detect traces of life on Mars.

Biological analysis of the in-vitro effects of homologous recombination inhibition and its use in cancer treatment through synthetic lethality

Synthetic lethality represents an anticancer strategy that targets tumor specific gene defects. One of the most studied application is the use of PARP inhibitors (e.g. olaparib) in BRCA1/2-less cancer cells. In BRCA2-defective tumors, olaparib (OLA) inhibits DNA single-strand break repair, while BRCA2 mutations hamper homologous recombination (HR) repair. The simultaneous impairment of those pathways leads BRCA-less cells to death by synthetic lethality. The projects described in this thesis were aimed at extending the use of OLA in cancer cells that do not carry a mutation in BRCA2 by combining this drug with compounds that could mimic a BRCA-less environment via HR inhibition. We demonstrated the effectiveness of our “fully small-molecule induced synthetic lethality” by using two different approaches. In the direct approach (Project A), we identified a series of neo-synthesized compounds (named RAD51-BRCA2 disruptors) that mimic BRCA2 mutations by disrupting the RAD51-BRCA2 interaction and thus the HR pathway. Compound ARN 24089 inhibited HR in human pancreatic adenocarcinoma cell line and triggered synthetic lethality by synergizing with OLA. Interestingly, the observed synthetic lethality was triggered by tackling two biochemically different mechanisms: enzyme inhibition (PARP) and protein-protein disruption (RAD51-BRCA2). In the indirect approach (Project B), we inhibited HR by interfering with the cellular metabolism through inhibition of LDH activity. The obtained data suggest an LDH-mediated control on HR that can be exerted by regulating either the energy supply needed to this repair mechanism or the expression level of genes involved in DNA repair. LDH inhibition also succeeded in increasing the efficiency of OLA in BRCA-proficient cell lines. Although preliminary, these results highlight a complex relationship between metabolic reactions and the control of DNA integrity. Both the described projects proved that our “fully small-molecule-induced synthetic lethality” approach could be an innovative approach to unmet oncological needs.

Hybrid ground-aerial mesh networks for IoT monitoring applications: network design and software platform development

The Internet of Things (IoT) has grown rapidly in recent years, leading to an increased need for efficient and secure communication between connected devices. Wireless Sensor Networks (WSNs) are composed of small, low-power devices that are capable of sensing and exchanging data, and are often used in IoT applications. In addition, Mesh WSNs involve intermediate nodes forwarding data to ensure more robust communication. The integration of Unmanned Aerial Vehicles (UAVs) in Mesh WSNs has emerged as a promising solution for increasing the effectiveness of data collection, as UAVs can act as mobile relays, providing extended communication range and reducing energy consumption. However, the integration of UAVs and Mesh WSNs still poses new challenges, such as the design of efficient control and communication strategies. This thesis explores the networking capabilities of WSNs and investigates how the integration of UAVs can enhance their performance. The research focuses on three main objectives: (1) Ground Wireless Mesh Sensor Networks, (2) Aerial Wireless Mesh Sensor Networks, and (3) Ground/Aerial WMSN integration. For the first objective, we investigate the use of the Bluetooth Mesh standard for IoT monitoring in different environments. The second objective focuses on deploying aerial nodes to maximize data collection effectiveness and QoS of UAV-to-UAV links while maintaining the aerial mesh connectivity. The third objective investigates hybrid WMSN scenarios with air-to-ground communication links. One of the main contribution of the thesis consists in the design and implementation of a software framework called "Uhura", which enables the creation of Hybrid Wireless Mesh Sensor Networks and abstracts and handles multiple M2M communication stacks on both ground and aerial links. The operations of Uhura have been validated through simulations and small-scale testbeds involving ground and aerial devices.

Metabolomics to investigate the effects of treatments on food and of food consumption on health

Metabolomics has established itself as a discipline that can offer a unique point of view on how a technological treatment could impact on the charactersitics of a food. Even more, the same analytical platforms necessary for the purpose can also effectively unravel intricate interactions between such food and human health upon consumption. This PhD thesis investigates the application of metabolomics in understanding the impact of technological treatments on food and their subsequent effects on human health, utilizing 1H-NMR as the analytical platform. The study involves the development of standard operating procedures (SOPs) to ensure a fast and stable preparation of seafood samples, incorporating novel algorithms to enhance the accuracy of metabolome profiles. To gain insight on how metabolomics can allow exploring the effects of a technological treatment on a food, we performed three sets of experiments to investigate the application of metabolomics in studying the impact of high hydrostatic pressure (HHP) treatment on seafood metabolome during storage. The first experiment employs untargeted metabolomic analysis on chill-stored rose shrimp, revealing significant post-HHP treatment metabolic alterations and mechanisms. The investigation is extended to grey mullet in the second experiment, utilizing both untargeted and targeted metabolomic analyses to account for matrix-related effects. The third experiment assesses the targeted metabolome of striped prawns, showing that HHP significantly influences metabolic pathways, positively impacting freshness and taste through alterations in related metabolites. Shifting focus to the effects of food on humans, the study explores the impact of multistrain probiotics on cirrhosis patients using 1H-NMR. The platform reveals notable alterations in glutamine/glutamate metabolism, enhancing the patients' ammonia detoxification capacity. This research underscores the potential of metabolomics in uncovering intricate interactions between technological treatments, food, and human health, providing valuable insights for both the food industry and healthcare interventions.