5 resultados para Candida albicans morphology and interaction with Pseudomonas aeruginosa

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The surface properties of minerals have important implications in geology, environment, industry and biotechnology and for certain aspects in the research on the origin of life. This research project aims to widen the knowledge on the nanoscale surface properties of chlorite and phlogopite by means of advanced methodologies, and also to investigate the interaction of fundamental biomolecules, such as nucleotides, RNA, DNA and amino acid glycine with the surface of the selected phyllosilicates. Multiple advanced and complex experimental approaches based on scanning probe microscopy and spatially resolved spectroscopy were used and in some cases specifically developed. The results demonstrate that chlorite exposes at the surface atomically flat terraces with 0.5 nm steps typically generated by the fragmentation of the octahedral sheet of the interlayer (brucitic-type). This fragmentation at the nanoscale generates a high anisotropy and inhomogeneity with surface type and isomorphous cationic substitutions determining variations of the effective surface potential difference, ranging between 50-100 mV and 400-500 mV, when measured in air, between the TOT surface and the interlayer brucitic sheet. The surface potential was ascribed to be the driving force of the observed high affinity of the surface with the fundamental biomolecules, like single molecules of nucleotides, DNA, RNA and amino acids. Phlogopite was also observed to present an extended atomically flat surface, featuring negative surface potential values of some hundreds of millivolts and no significant local variations. Phlogopite surface was sometimes observed to present curvature features that may be ascribed to local substitutions of the interlayer cations or the presence of a crystal lattice mismatch or structural defects, such as stacking faults or dislocation loops. Surface chemistry was found similar to the bulk. The study of the interaction with nucleotides and glycine revealed a lower affinity with respect to the brucite-like surface of chlorite.

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Oceans play a key role in the climate system, being the largest heat sinks on Earth. Part of the energy balance of ocean circulation is driven by the Near-inertial internal waves (NIWs). Strong NIWs are observed during a multi-platform, multi-disciplinary and multi-scale campaign led by the NATO-STO CMRE in autumn 2017 in the Ligurian Sea (northwestern Mediterranean Sea). The objectives of this work are as follows: characterise the studied area at different scales; study the NIWs generation and their propagation; estimate the NIWs properties; study the interaction between NIWs and mesoscale structures. This work provides, to the author’s knowledge, the first characterization of NIWs in the Mediterranean Sea. The near-surface NIWs observed at the fixed moorings are locally generated by wind bursts while the deeper waves originate in other regions and arrive at the moorings several days later. Most of the observed NIWs energy propagates downward with a mean vertical group velocity of (2.2±0.3) ⋅10-4 m s-1. On average, the NIWs have an amplitude of 0.13 m s-1 and mean horizontal and vertical wavelengths of 43±25 km and 125±35 m, while shorter wavelengths are observed at the near-coastal mooring, 36±2 km and 33±2 m, respectively. Most of the observed NIWs are blue shifted and reach a value 9% higher than the local inertial frequency. Only two observed NIWs are characterised by a redshift (up to 3% lower than the local inertial frequency). In support of the in situ observations, a high resolution numerical model is implemented using NEMO (Madec et al., 2019). Results show that anticyclones (cyclones) shift the frequency of NIWs to lower (higher) frequencies with respect to the local inertial frequency. Anticyclones facilitate the downward propagation of NIW energy, while cyclones dampen it. Absence of NIWs energy within an anticyclone is also investigated.

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Despite extensive research and introduction of innovative therapy, lung cancer prognosis remains poor, with a five years survival of only 17%. The success of pharmacological treatment is often impaired by drug resistance. Thus, the characterization of response mechanisms to anti-cancer compounds and of the molecular mechanisms supporting lung cancer aggressiveness are crucial for patient’s management. In the first part of this thesis, we characterized the molecular mechanism behind resistance of lung cancer cells to the Inhibitors of the Bromodomain and Extraterminal domain containing Proteins (BETi). Through a CRISPR/Cas9 screening we identified three Hippo Pathway members, LATS2, TAOK1 and NF2 as genes implicated in susceptibility to BETi. These genes confer sensitivity to BETi inhibiting TAZ activity. Conversely, TAZ overexpression increases resistance to BETi. We also displayed that BETi downregulate both YAP, TAZ and TEADs expression in several cancer cell lines, implying a novel BETi-dependent cytotoxic mechanism. In the second part of this work, we attempted to characterize the crosstalk between the TAZ gene and its cognate antisense long-non coding RNA (lncRNA) TAZ-AS202 in lung tumorigenesis. As for TAZ downregulation, TAZ-AS202 silencing impairs NSCLC cells proliferation, migration and invasion, suggesting a pro-tumorigenic function for this lncRNA during lung tumorigenesis. TAZ-AS202 regulates TAZ target genes without altering TAZ expression or localization. This finding implies an uncovered functional cooperation between TAZ and TAZ-AS202. Moreover, we found that the EPH-ephrin signaling receptor EPHB2 is a downstream effector affected by both TAZ and TAZ-AS202 silencing. EPHB2 downregulation significantly attenuates cells proliferation, migration and invasion, suggesting that, at least in part, TAZ-AS202 and TAZ pro-oncogenic activity depends on EPH-ephrin signaling final deregulation. Finally, we started to dissect the mechanism underlying the TAZ-AS202 regulatory activity on EPHB2 in lung cancer, which may involve the existence of an intermediate transcription factor and is the object of our ongoing research.

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Safe collaboration between a robot and human operator forms a critical requirement for deploying a robotic system into a manufacturing and testing environment. In this dissertation, the safety requirement for is developed and implemented for the navigation system of the mobile manipulators. A methodology for human-robot co-existence through a 3d scene analysis is also investigated. The proposed approach exploits the advance in computing capability by relying on graphic processing units (GPU’s) for volumetric predictive human-robot contact checking. Apart from guaranteeing safety of operators, human-robot collaboration is also fundamental when cooperative activities are required, as in appliance test automation floor. To achieve this, a generalized hierarchical task controller scheme for collision avoidance is developed. This allows the robotic arm to safely approach and inspect the interior of the appliance without collision during the testing procedure. The unpredictable presence of the operators also forms dynamic obstacle that changes very fast, thereby requiring a quick reaction from the robot side. In this aspect, a GPU-accelarated distance field is computed to speed up reaction time to avoid collision between human operator and the robot. An automated appliance testing also involves robotized laundry loading and unloading during life cycle testing. This task involves Laundry detection, grasp pose estimation and manipulation in a container, inside the drum and during recovery grasping. A wrinkle and blob detection algorithms for grasp pose estimation are developed and grasp poses are calculated along the wrinkle and blobs to efficiently perform grasping task. By ranking the estimated laundry grasp poses according to a predefined cost function, the robotic arm attempt to grasp poses that are more comfortable from the robot kinematic side as well as collision free on the appliance side. This is achieved through appliance detection and full-model registration and collision free trajectory execution using online collision avoidance.

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The advent of omic data production has opened many new perspectives in the quest for modelling complexity in biophysical systems. With the capability of characterizing a complex organism through the patterns of its molecular states, observed at different levels through various omics, a new paradigm of investigation is arising. In this thesis, we investigate the links between perturbations of the human organism, described as the ensemble of crosstalk of its molecular states, and health. Machine learning plays a key role within this picture, both in omic data analysis and model building. We propose and discuss different frameworks developed by the author using machine learning for data reduction, integration, projection on latent features, pattern analysis, classification and clustering of omic data, with a focus on 1H NMR metabolomic spectral data. The aim is to link different levels of omic observations of molecular states, from nanoscale to macroscale, to study perturbations such as diseases and diet interpreted as changes in molecular patterns. The first part of this work focuses on the fingerprinting of diseases, linking cellular and systemic metabolomics with genomic to asses and predict the downstream of perturbations all the way down to the enzymatic network. The second part is a set of frameworks and models, developed with 1H NMR metabolomic at its core, to study the exposure of the human organism to diet and food intake in its full complexity, from epidemiological data analysis to molecular characterization of food structure.