9 resultados para diagnostic methods

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


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The use of atmospheric pressure plasmas for thin film deposition on thermo-sensitive materials is currently one of the main challenges of the plasma scientific community. Despite the growing interest in this field, the existing knowledge gap between gas-phase reaction mechanisms and thin film properties is still one of the most important barriers to overcome for a complete understanding of the process. In this work, thin films surface characterization techniques, combined with passive and active gas-phase diagnostic methods, were used to provide a comprehensive study of the Ar/TEOS deposition process assisted by an atmospheric pressure plasma jet. SiO2-based thin films exhibiting a well-defined chemistry, a good morphological structure and high uniformity were studied in detail by FTIR, XPS, AFM and SEM analysis. Furthermore, non-intrusive spectroscopy techniques (OES, filter imaging) and laser spectroscopic methods (Rayleigh scattering, LIF and TALIF) were employed to shed light on the complexity of gas-phase mechanisms involved in the deposition process and discuss the influence of TEOS admixture on gas temperature, electron density and spatial-temporal behaviours of active species. The poly-diagnostic approach proposed in this work opens interesting perspectives both in terms of process control and optimization of thin film performances.

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Cardiotocography (CTG) is a widespread foetal diagnostic methods. However, it lacks of objectivity and reproducibility since its dependence on observer's expertise. To overcome these limitations, more objective methods for CTG interpretation have been proposed. In particular, many developed techniques aim to assess the foetal heart rate variability (FHRV). Among them, some methodologies from nonlinear systems theory have been applied to the study of FHRV. All the techniques have proved to be helpful in specific cases. Nevertheless, none of them is more reliable than the others. Therefore, an in-depth study is necessary. The aim of this work is to deepen the FHRV analysis through the Symbolic Dynamics Analysis (SDA), a nonlinear technique already successfully employed for HRV analysis. Thanks to its simplicity of interpretation, it could be a useful tool for clinicians. We performed a literature study involving about 200 references on HRV and FHRV analysis; approximately 100 works were focused on non-linear techniques. Then, in order to compare linear and non-linear methods, we carried out a multiparametric study. 580 antepartum recordings of healthy fetuses were examined. Signals were processed using an updated software for CTG analysis and a new developed software for generating simulated CTG traces. Finally, statistical tests and regression analyses were carried out for estimating relationships among extracted indexes and other clinical information. Results confirm that none of the employed techniques is more reliable than the others. Moreover, in agreement with the literature, each analysis should take into account two relevant parameters, the foetal status and the week of gestation. Regarding the SDA, results show its promising capabilities in FHRV analysis. It allows recognizing foetal status, gestation week and global variability of FHR signals, even better than other methods. Nevertheless, further studies, which should involve even pathological cases, are necessary to establish its reliability.

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Brain functioning relies on the interaction of several neural populations connected through complex connectivity networks, enabling the transmission and integration of information. Recent advances in neuroimaging techniques, such as electroencephalography (EEG), have deepened our understanding of the reciprocal roles played by brain regions during cognitive processes. The underlying idea of this PhD research is that EEG-related functional connectivity (FC) changes in the brain may incorporate important neuromarkers of behavior and cognition, as well as brain disorders, even at subclinical levels. However, a complete understanding of the reliability of the wide range of existing connectivity estimation techniques is still lacking. The first part of this work addresses this limitation by employing Neural Mass Models (NMMs), which simulate EEG activity and offer a unique tool to study interconnected networks of brain regions in controlled conditions. NMMs were employed to test FC estimators like Transfer Entropy and Granger Causality in linear and nonlinear conditions. Results revealed that connectivity estimates reflect information transmission between brain regions, a quantity that can be significantly different from the connectivity strength, and that Granger causality outperforms the other estimators. A second objective of this thesis was to assess brain connectivity and network changes on EEG data reconstructed at the cortical level. Functional brain connectivity has been estimated through Granger Causality, in both temporal and spectral domains, with the following goals: a) detect task-dependent functional connectivity network changes, focusing on internal-external attention competition and fear conditioning and reversal; b) identify resting-state network alterations in a subclinical population with high autistic traits. Connectivity-based neuromarkers, compared to the canonical EEG analysis, can provide deeper insights into brain mechanisms and may drive future diagnostic methods and therapeutic interventions. However, further methodological studies are required to fully understand the accuracy and information captured by FC estimates, especially concerning nonlinear phenomena.

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Human Papillomavirus (HPV) is the cause of cervical cancers (among these, adenocarcinoma, AdCa) and is associated to a subgroup of oropharyngeal carcinomas (OPSCCs). Even if the risk for cancer development is linked to the infection by some viral genotypes, mainly HPV16 and 18, viral DNA alone seems not to be sufficient for diagnosis. Moreover, the role of the virus in OPSCCs has not been totally clarified yet. In the first part of the thesis, the performances concerning viral genotyping in clinical cervical samples of a new pyrosequencing-based test and a well-known hybridization-based assay have been compared. Similar results between the methods have been obtained. However, the former showed advantages in detecting intratype variants, higher specificity and a broader spectrum of detectable HPV types. The second part deals with the evaluation of virological markers (genotyping, viral oncoproteins expression, viral load, physical state and CpG methylation of HPV16 genome) in the diagnosis/prognosis of cervical AdCa and HPV-associated OPSCCs. HPV16 has been confirmed the most prevalent genotype in both the populations. Interestingly, the mean methylation frequency of viral DNA at the early promoter showed the tendency to be associated to invasion for cervical AdCa and to a worse prognosis for OPSCCs, suggesting a promising role as diagnostic/prognostic biomarker. The experiments of the third part were performed at the DKFZ in Heidelberg (Germany) and dealt with the analysis of the response to IFN-k transfection in HPV16-positive cervical cancer and head&neck carcinoma cell lines to evaluate its potential role as new treatment. After 24h, we observed increased IFN-b expression which lead to the up-regulation of genes involved in the antigens presentation pathway (MHC class I and immunoproteasome) and antiviral response as well, in particular in cervical cancer cell lines. This fact suggested also the presence of different HPV-mediated carcinogenic pathways between the two anatomical districts.

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The safety systems of nuclear power plants rely on low-voltage power, instrumentation and control cables. Inside the containment area, cables operate in harsh environments, characterized by relatively high temperature and gamma-irradiation. As these cables are related to fundamental safety systems, they must be able to withstand unexpected accident conditions and, therefore, their condition assessment is of utmost importance as plants age and lifetime extensions are required. Nowadays, the integrity and functionality of these cables are monitored mainly through destructive test which requires specific laboratory. The investigation of electrical aging markers which can provide information about the state of the cable by non-destructive testing methods would improve significantly the present diagnostic techniques. This work has been made within the framework of the ADVANCE (Aging Diagnostic and Prognostics of Low-Voltage I\&C Cables) project, a FP7 European program. This Ph.D. thesis aims at studying the impact of aging on cable electrical parameters, in order to understand the evolution of the electrical properties associated with cable degradation. The identification of suitable aging markers requires the comparison of the electrical property variation with the physical/chemical degradation mechanisms of polymers for different insulating materials and compositions. The feasibility of non-destructive electrical condition monitoring techniques as potential substitutes for destructive methods will be finally discussed studying the correlation between electrical and mechanical properties. In this work, the electrical properties of cable insulators are monitored and characterized mainly by dielectric spectroscopy, polarization/depolarization current analysis and space charge distribution. Among these techniques, dielectric spectroscopy showed the most promising results; by means of dielectric spectroscopy it is possible to identify the frequency range where the properties are more sensitive to aging. In particular, the imaginary part of permittivity at high frequency, which is related to oxidation, has been identified as the most suitable aging marker based on electrical quantities.

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Environmental decay in porous masonry materials, such as brick and mortar, is a widespread problem concerning both new and historic masonry structures. The decay mechanisms are quite complex dependng upon several interconnected parameters and from the interaction with the specific micro-climate. Materials undergo aesthetical and substantial changes in character but while many studies have been carried out, the mechanical aspect has been largely understudied while it bears true importance from the structural viewpoint. A quantitative assessment of the masonry material degradation and how it affects the load-bearing capacity of masonry structures appears missing. The research work carried out, limiting the attention to brick masonry addresses this issue through an experimental laboratory approach via different integrated testing procedures, both non-destructive and mechanical, together with monitoring methods. Attention was focused on transport of moisture and salts and on the damaging effects caused by the crystallization of two different salts, sodium chloride and sodium sulphate. Many series of masonry specimens, very different in size and purposes were used to track the damage process since its beginning and to monitor its evolution over a number of years Athe same time suitable testing techniques, non-destructive, mini-invasive, analytical, of monitoring, were validated for these purposes. The specimens were exposed to different aggressive agents (in terms of type of salt, of brine concentration, of artificial vs. open-air natural ageing, …), tested by different means (qualitative vs. quantitative, non destructive vs. mechanical testing, punctual vs. wide areas, …), and had different size (1-, 2-, 3-header thick walls, full-scale walls vs. small size specimens, brick columns and triplets vs. small walls, masonry specimens vs. single units of brick and mortar prisms, …). Different advanced testing methods and novel monitoring techniques were applied in an integrated holistic approach, for quantitative assessment of masonry health state.

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Background. Hhereditary cystic kidney diseases are a heterogeneous spectrum of disorders leading to renal failure. Clinical features and family history can help to distinguish the recessive from dominant diseases but the differential diagnosis is difficult due the phenotypic overlap. The molecular diagnosis is often the only way to characterize the different forms. A conventional molecular screening is suitable for small genes but is expensive and time-consuming for large size genes. Next Generation Sequencing (NGS) technologies enables massively parallel sequencing of nucleic acid fragments. Purpose. The first purpose was to validate a diagnostic algorithm useful to drive the genetic screening. The second aim was to validate a NGS protocol of PKHD1 gene. Methods. DNAs from 50 patients were submitted to conventional screening of NPHP1, NPHP5, UMOD, REN and HNF1B genes. 5 patients with known mutations in PKHD1 were submitted to NGS to validate the new method and a not genotyped proband with his parents were analyzed for a diagnostic application. Results. The conventional molecular screening detected 8 mutations: 1) the novel p.E48K of REN in a patient with cystic nephropathy, hyperuricemia, hyperkalemia and anemia; 2) p.R489X of NPHP5 in a patient with Senior Loken Syndrome; 3) pR295C of HNF1B in a patient with renal failure and diabetes.; 4) the NPHP1 deletion in 3 patients with medullar cysts; 5) the HNF1B deletion in a patient with medullar cysts and renal hypoplasia and in a diabetic patient with liver disease. The NGS of PKHD1 detected all known mutations and two additional variants during the validation. The diagnostic NGS analysis identified the patient’s compound heterozygosity with a maternal frameshift mutation and a paternal missense mutation besides a not transmitted paternal missense mutation. Conclusions. The results confirm the validity of our diagnostic algorithm and suggest the possibility to introduce this NGS protocol to clinical practice.

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The increase in aquaculture operations worldwide has provided new opportunities for the transmission of aquatic viruses. The occurrence of viral diseases remains a significant limiting factor in aquaculture production and for the sustainability. The ability to identify quickly the presence/absence of a pathogenic organism in fish would have significant advantages for the aquaculture systems. Several molecular methods have found successful application in fish pathology both for confirmatory diagnosis of overt diseases and for detection of asymptomatic infections. However, a lot of different variants occur among fish host species and virus strains and consequently specific methods need to be developed and optimized for each pathogen and often also for each host species. The first chapter of this PhD thesis presents a complete description of the major viruses that infect fish and provides a relevant information regarding the most common methods and emerging technologies for the molecular diagnosis of viral diseases of fish. The development and application of a real time PCR assay for the detection and quantification of lymphocystivirus was described in the second chapter. It showed to be highly sensitive, specific, reproducible and versatile for the detection and quantitation of lymphocystivirus. The use of this technique can find multiple application such as asymptomatic carrier detection or pathogenesis studies of different LCDV strains. The third chapter, a multiplex RT-PCR (mRT-PCR) assay was developed for the simultaneous detection of viral haemorrhagic septicaemia (VHS), infectious haematopoietic necrosis (IHN), infectious pancreatic necrosis (IPN) and sleeping disease (SD) in a single assay. This method was able to efficiently detect the viral RNA in tissue samples, showing the presence of single infections and co-infections in rainbow trout samples. The mRT-PCR method was revealed to be an accurate and fast method to support traditional diagnostic techniques in the diagnosis of major viral diseases of rainbow trout.

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The world of Computational Biology and Bioinformatics presently integrates many different expertise, including computer science and electronic engineering. A major aim in Data Science is the development and tuning of specific computational approaches to interpret the complexity of Biology. Molecular biologists and medical doctors heavily rely on an interdisciplinary expert capable of understanding the biological background to apply algorithms for finding optimal solutions to their problems. With this problem-solving orientation, I was involved in two basic research fields: Cancer Genomics and Enzyme Proteomics. For this reason, what I developed and implemented can be considered a general effort to help data analysis both in Cancer Genomics and in Enzyme Proteomics, focusing on enzymes which catalyse all the biochemical reactions in cells. Specifically, as to Cancer Genomics I contributed to the characterization of intratumoral immune microenvironment in gastrointestinal stromal tumours (GISTs) correlating immune cell population levels with tumour subtypes. I was involved in the setup of strategies for the evaluation and standardization of different approaches for fusion transcript detection in sarcomas that can be applied in routine diagnostic. This was part of a coordinated effort of the Sarcoma working group of "Alleanza Contro il Cancro". As to Enzyme Proteomics, I generated a derived database collecting all the human proteins and enzymes which are known to be associated to genetic disease. I curated the data search in freely available databases such as PDB, UniProt, Humsavar, Clinvar and I was responsible of searching, updating, and handling the information content, and computing statistics. I also developed a web server, BENZ, which allows researchers to annotate an enzyme sequence with the corresponding Enzyme Commission number, the important feature fully describing the catalysed reaction. More to this, I greatly contributed to the characterization of the enzyme-genetic disease association, for a better classification of the metabolic genetic diseases.