Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.

Advanced modelling of time domain electromagnetic data with updated hydrogeological interpretations

Several countries have acquired, over the past decades, large amounts of area covering Airborne Electromagnetic data. Contribution of airborne geophysics has dramatically increased for both groundwater resource mapping and management proving how those systems are appropriate for large-scale and efficient groundwater surveying. We start with processing and inversion of two AEM dataset from two different systems collected over the Spiritwood Valley Aquifer area, Manitoba, Canada respectively, the AeroTEM III (commissioned by the Geological Survey of Canada in 2010) and the “Full waveform VTEM” dataset, collected and tested over the same survey area, during the fall 2011. We demonstrate that in the presence of multiple datasets, either AEM and ground data, due processing, inversion, post-processing, data integration and data calibration is the proper approach capable of providing reliable and consistent resistivity models. Our approach can be of interest to many end users, ranging from Geological Surveys, Universities to Private Companies, which are often proprietary of large geophysical databases to be interpreted for geological and\or hydrogeological purposes. In this study we deeply investigate the role of integration of several complimentary types of geophysical data collected over the same survey area. We show that data integration can improve inversions, reduce ambiguity and deliver high resolution results. We further attempt to use the final, most reliable output resistivity models as a solid basis for building a knowledge-driven 3D geological voxel-based model. A voxel approach allows a quantitative understanding of the hydrogeological setting of the area, and it can be further used to estimate the aquifers volumes (i.e. potential amount of groundwater resources) as well as hydrogeological flow model prediction. In addition, we investigated the impact of an AEM dataset towards hydrogeological mapping and 3D hydrogeological modeling, comparing it to having only a ground based TEM dataset and\or to having only boreholes data.

Applications of metrological techniques for clinical implementation of dosimetry and radiobiology in molecular radiotherapy

Molecular radiotherapy (MRT) is a fast developing and promising treatment for metastasised neuroendocrine tumours. Efficacy of MRT is based on the capability to selectively "deliver" radiation to tumour cells, minimizing administered dose to normal tissues. Outcome of MRT depends on the individual patient characteristics. For that reason, personalized treatment planning is important to improve outcomes of therapy. Dosimetry plays a key role in this setting, as it is the main physical quantity related to radiation effects on cells. Dosimetry in MRT consists in a complex series of procedures ranging from imaging quantification to dose calculation. This doctoral thesis focused on several aspects concerning the clinical implementation of absorbed dose calculations in MRT. Accuracy of SPECT/CT quantification was assessed in order to determine the optimal reconstruction parameters. A model of PVE correction was developed in order to improve the activity quantification in small volume, such us lesions in clinical patterns. Advanced dosimetric methods were compared with the aim of defining the most accurate modality, applicable in clinical routine. Also, for the first time on a large number of clinical cases, the overall uncertainty of tumour dose calculation was assessed. As part of the MRTDosimetry project, protocols for calibration of SPECT/CT systems and implementation of dosimetry were drawn up in order to provide standard guidelines to the clinics offering MRT. To estimate the risk of experiencing radio-toxicity side effects and the chance of inducing damage on neoplastic cells is crucial for patient selection and treatment planning. In this thesis, the NTCP and TCP models were derived based on clinical data as help to clinicians to decide the pharmaceutical dosage in relation to the therapy control and the limitation of damage to healthy tissues. Moreover, a model for tumour response prediction based on Machine Learning analysis was developed.

Mapping new non-genetic dependencies in malignant pleural mesothelioma

Malignant Pleural Mesothelioma (MPM) is a very aggressive cancer whose incidence is growing worldwide. MPM escapes the classical models of carcinogenesis and lacks a distinctive genetic fingerprint, keeping obscure the molecular events that lead to tumorigenesis. This severely impacts on the limited therapeutic options and on the lack of specific biomarkers, concurring to make MPM one of the deadliest cancers. Here we combined a functional genome-wide loss of function CRISPR/Cas9 screening with patients’ transcriptomic and clinical data, to identify genes essential for MPM progression. Besides, we explored the role of non-coding RNAs to MPM progression by analysing gene expression profiles and clinical data from the MESO-TCGA dataset. We identified TRIM28 and the lncRNA LINC00941 as new vulnerabilities of MPM, associated with disease aggressiveness and bad outcome of patients. TRIM28 is a multi-domain protein involved in many processes, including transcription regulation. We showed that TRIM28 silencing impairs MPM cells’ growth and clonogenicity by blocking cells in mitosis. RNA-seq profiling showed that TRIM28 loss abolished the expression of major mitotic players. Our data suggest that TRIM28 is part of the B-MYB/FOXM1-MuvB complex that specifically drives the activation of mitotic genes, keeping the time of mitosis. In parallel, we found LINC00941 as strongly associated with reduced survival probability in MPM patients. LINC00941 KD profoundly reduced MPM cells’ growth, migration and invasion. This is accompanied by changes in morphology, cytoskeleton organization and cell-cell adhesion properties. RNA-seq profiling showed that LINC00941 KD impacts crucial functions of MPM, including HIF1α signalling. Collectively these data provided new insights into MPM biology and demonstrated that the integration of functional screening with patients’ clinical data is a powerful tool to highlight new non-genetic cancer dependencies that associate to a bad outcome in vivo, paving the way to new MPM-oriented targeted strategies and prognostic tools to improve patients risk-based stratification.

Quantitative susceptibility mapping as biomarker of neurodegeneration: methodological models and clinical applications

Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance technique that can quantify in vivo biomarkers of pathology, such as alteration in iron and myelin concentration. It allows for the comparison of magnetic susceptibility properties within and between different subject groups. In this thesis, QSM acquisition and processing pipeline are discussed, together with clinical and methodological applications of QSM to neurodegeneration. In designing the studies, significant emphasis was placed on results reproducibility and interpretability. The first project focuses on the investigation of cortical regions in amyotrophic lateral sclerosis. By examining various histogram susceptibility properties, a pattern of increased iron content was revealed in patients with amyotrophic lateral sclerosis compared to controls and other neurodegenerative disorders. Moreover, there was a correlation between susceptibility and upper motor neuron impairment, particularly in patients experiencing rapid disease progression. Similarly, in the second application, QSM was used to examine cortical and sub-cortical areas in individuals with myotonic dystrophy type 1. The thalamus and brainstem were identified as structures of interest, with relevant correlations with clinical and laboratory data such as neurological evaluation and sleep records. In the third project, a robust pipeline for assessing radiomic susceptibility-based features reliability was implemented within a cohort of patients with multiple sclerosis and healthy controls. Lastly, a deep learning super-resolution model was applied to QSM images of healthy controls. The employed model demonstrated excellent generalization abilities and outperformed traditional up-sampling methods, without requiring a customized re-training. Across the three disorders investigated, it was evident that QSM is capable of distinguishing between patient groups and healthy controls while establishing correlations between imaging measurements and clinical data. These studies lay the foundation for future research, with the ultimate goal of achieving earlier and less invasive diagnoses of neurodegenerative disorders within the context of personalized medicine.

Profilo molecolare dei linfomi post-trapianto

Fifty-two cases of monomorphic post-transplant lymphoproliferative disorders (M-PTLD), developed in patients undergone solid organ or bone marrow transplantation, were studied by the application of the tissue micro-array (TMA) technology. They included 50 cases of diffuse large B-cell lymphomas (DLBCL) and 2 Burkitt lymphomas (BL). In order to evaluate the immune-profile a large panel of antibodies was applied including several new markers (Cyclin D2, Cyclin D3, p27, PKC-β, FOXP-1 and Survivin) identified as negative prognostic factors in DLBCL of the immunocompetent patient. Out of 50 DLBCL, 23 cases (46%) had an Activated B Cell (ABC) phenotype, 8 (16%) a Germinal Centre B-cell (GCB) phenotype, and 11 (22%) an Unclassified (UC) phenotype. In 8 cases (16%) the subtype was not demonstrable due to sub-optimal preservation or loss of the tissue core. FISH analysis detected BCL2 gene amplification and MYC rearrangement. EBV was identified in 32 cases (64%) performing immunohistochemistry (LMP-1) and in situ hybridization (EBER). Clinical data and follow-up were available in all cases of malignant lymphomas but one. Thirty-two patients died for progression of disease or complications related to transplant (bleeding, bacterial infections, and multi-organ failure); 17 patients are actually alive and disease-free. M-PTLD are aggressive lymphomas characterized by very poor outcome. The neoplastic process is stimulated by a prolonged immunosuppressive status which is capable to induce alterations of the immune system and allow EBV reactivation in previously infected patients. Indeed EBV infection seems to be the most significant risk factor to predict the development of a PTLD while age, sex, site of involvement and type of transplant do not have significant correlation. Furthermore DLBCL arisen in a setting of immunodeficiency share phenotypic and molecular features with DLBCL of the immunocompetent patient. In particular, the former shows a high incidence of BCL2 gene amplification and this aberration typically correlates with “non-GCB” phenotype. Also M-PTLD do express prognostic markers (PKC-β, cyclin D2, FOXP-1, and Survivin): notably, in our study, PKC-β and FOXP-1 were frequently expressed and they were predictive of a shorter overall survival even in lymphomas recognized to have a good prognosis (GCB-type). Given the fact that such molecules are detectable at the time of the diagnosis, we postulate whether a “tailored” or more specific therapy might be applied in the management of the immune-compromised patient.

Evaluation of fluid transport processes in dental enamel. Methods to assess the relevance of enamel permeability in caries prevention and etching treatments.

This thesis evaluated in vivo and in vitro enamel permeability in different physiological and clinical conditions by means of SEM inspection of replicas of enamel surface obtained from polyvinyl siloxane impressions subsequently later cast in polyether impression ma-terial. This technique, not invasive and risk-free, allows the evaluation of fluid outflow from enamel surface and is able to detect the presence of small quantities of fluid, visu-alized as droplets. Fluid outflow on enamel surface represents enamel permeability. This property has a paramount importance in enamel physiolgy and pathology although its ef-fective role in adhesion, caries pathogenesis and prevention today is still not fully under-stood. The aim of the studies proposed was to evaluate enamel permeability changes in differ-ent conditions and to correlate the findings with the actual knowledge about enamel physiology, caries pathogenesis, fluoride and etchinhg treatments. To obtain confirmed data the replica technique has been supported by others specific techniques such as Ra-man and IR spectroscopy and EDX analysis. The first study carried out visualized fluid movement through dental enamel in vivo con-firmed that enamel is a permeable substrate and demonstrated that age and enamel per-meability are closely related. Examined samples from subjects of different ages showed a decreasing number and size of droplets with increasing age: freshly erupted permanent teeth showed many droplets covering the entire enamel surface. Droplets in permanent teeth were prominent along enamel perikymata. These results obtained through SEM inspection of replicas allowed innovative remarks in enamel physiology. An analogous testing has been developed for evaluation of enamel permeability in primary enamel. The results of this second study showed that primary enamel revealed a substantive permeability with droplets covering the entire enamel sur-face without any specific localization accordingly with histological features, without changes during aging signs of post-eruptive maturation. These results confirmed clinical data that showed a higher caries susceptibility for primary enamel and suggested a strong relationship between this one and enamel permeability. Topical fluoride application represents the gold standard for caries prevention although the mechanism of cariostatic effect of fluoride still needs to be clarified. The effects of topical fluoride application on enamel permeability were evaluated. Particularly two dif-ferent treatments (NaF and APF), with different pH, were examined. The major product of topical fluoride application was the deposition of CaF2-like globules. Replicas inspec-tion before and after both treatments at different times intervals and after specific addi-tional clinical interventions showed that such globule formed in vivo could be removed by professional toothbrushing, sonically and chemically by KOH. The results obtained in relation to enamel permeability showed that fluoride treatments temporarily reduced enamel water permeability when CaF2-like globules were removed. The in vivo perma-nence of decreased enamel permeability after CaF2 globules removal has been demon-strated for 1 h for NaF treated teeth and for at least 7 days for APF treated teeth. Important clinical consideration moved from these results. In fact the caries-preventing action of fluoride application may be due, in part, to its ability to decrease enamel water permeability and CaF2 like-globules seem to be indirectly involved in enamel protection over time maintaining low permeability. Others results obtained by metallographic microscope and SEM/EDX analyses of or-thodontic resins fluoride releasing and not demonstrated the relevance of topical fluo-ride application in decreasing the demineralization marks and modifying the chemical composition of the enamel in the treated area. These data obtained in both the experiments confirmed the efficacy of fluoride in caries prevention and contribute to clarify its mechanism of action. Adhesive dentistry is the gold standard for caries treatment and tooth rehabilitation and is founded on important chemical and physical principles involving both enamel and dentine substrates. Particularly acid etching of dental enamel enamel has usually employed in bonding pro-cedures increasing microscopic roughness. Different acids have been tested in the litera-ture suggesting several etching procedures. The acid-induced structural transformations in enamel after different etching treatments by means of Raman and IR spectroscopy analysis were evaluated and these findings were correlated with enamel permeability. Conventional etching with 37% phosphoric acid gel (H3PO4) for 30 s and etching with 15 % HCl for 120 s were investigated. Raman and IR spectroscopy showed that the treatment with both hydrochloric and phosphoric acids induced a decrease in the carbonate content of the enamel apatite. At the same time, both acids induced the formation of HPO42- ions. After H3PO4 treatment the bands due to the organic component of enamel decreased in intensity, while in-creased after HCl treatment. Replicas of H3PO4 treated enamel showed a strongly reduced permeability while replicas of HCl 15% treated samples showed a maintained permeability. A decrease of the enamel organic component, as resulted after H3PO4 treatment, involves a decrease in enamel permeability, while the increase of the organic matter (achieved by HCl treat-ment) still maintains enamel permeability. These results suggested a correlation between the amount of the organic matter, enamel permeability and caries. The results of the different studies carried out in this thesis contributed to clarify and improve the knowledge about enamel properties with important rebounds in theoretical and clinical aspects of Dentistry.

Development of original analytical methods for the therapeutic drug monitoring of CNS druges: Antipsychotics, Antidepressants and Anxiolytics-hypnotics

Great strides have been made in the last few years in the pharmacological treatment of neuropsychiatric disorders, with the introduction into the therapy of several new and more efficient agents, which have improved the quality of life of many patients. Despite these advances, a large percentage of patients is still considered “non-responder” to the therapy, not drawing any benefits from it. Moreover, these patients have a peculiar therapeutic profile, due to the very frequent application of polypharmacy, attempting to obtain satisfactory remission of the multiple aspects of psychiatric syndromes. Therapy is heavily individualised and switching from one therapeutic agent to another is quite frequent. One of the main problems of this situation is the possibility of unwanted or unexpected pharmacological interactions, which can occur both during polypharmacy and during switching. Simultaneous administration of psychiatric drugs can easily lead to interactions if one of the administered compounds influences the metabolism of the others. Impaired CYP450 function due to inhibition of the enzyme is frequent. Other metabolic pathways, such as glucuronidation, can also be influenced. The Therapeutic Drug Monitoring (TDM) of psychotropic drugs is an important tool for treatment personalisation and optimisation. It deals with the determination of parent drugs and metabolites plasma levels, in order to monitor them over time and to compare these findings with clinical data. This allows establishing chemical-clinical correlations (such as those between administered dose and therapeutic and side effects), which are essential to obtain the maximum therapeutic efficacy, while minimising side and toxic effects. It is evident the importance of developing sensitive and selective analytical methods for the determination of the administered drugs and their main metabolites, in order to obtain reliable data that can correctly support clinical decisions. During the three years of Ph.D. program, some analytical methods based on HPLC have been developed, validated and successfully applied to the TDM of psychiatric patients undergoing treatment with drugs belonging to following classes: antipsychotics, antidepressants and anxiolytic-hypnotics. The biological matrices which have been processed were: blood, plasma, serum, saliva, urine, hair and rat brain. Among antipsychotics, both atypical and classical agents have been considered, such as haloperidol, chlorpromazine, clotiapine, loxapine, risperidone (and 9-hydroxyrisperidone), clozapine (as well as N-desmethylclozapine and clozapine N-oxide) and quetiapine. While the need for an accurate TDM of schizophrenic patients is being increasingly recognized by psychiatrists, only in the last few years the same attention is being paid to the TDM of depressed patients. This is leading to the acknowledgment that depression pharmacotherapy can greatly benefit from the accurate application of TDM. For this reason, the research activity has also been focused on first and second-generation antidepressant agents, like triciclic antidepressants, trazodone and m-chlorophenylpiperazine (m-cpp), paroxetine and its three main metabolites, venlafaxine and its active metabolite, and the most recent antidepressant introduced into the market, duloxetine. Among anxiolytics-hypnotics, benzodiazepines are very often involved in the pharmacotherapy of depression for the relief of anxious components; for this reason, it is useful to monitor these drugs, especially in cases of polypharmacy. The results obtained during these three years of Ph.D. program are reliable and the developed HPLC methods are suitable for the qualitative and quantitative determination of CNS drugs in biological fluids for TDM purposes.

Genetic and environmental factors associated with the risk of cognitive decline and dementia

AD is the most common age related neurodegenerative disease in the industrialized world. Clinically AD is defined as a progressing decline of cognitive functions. Neuropathologically, AD is characterized by the aggregation of b-amyloid (Ab) peptide in the form of extracellular senile plaques, and hyperphosphorlylated tau protein in the form of intracellular neurofibrillary tangles. These neuropathological hallmarks are often accompanied by abundant microvascular damage and pronounced inflammation of the affected brain regions. In this thesis we investigated several aspects of AD focusing on the genetic aspect. We confirmed that Alpha 1 antichymotrypsin (ACT), an acute phase protein, was associated to AD subjects, being plasma levels higher in AD cases than controls. In addition, in a GWA study we demonstrated that two different gene, Clusterin and CR1 were strongly associated to AD. A single gene association not explain such a complex disease like AD. The goal should be to created a network of genetic, phenotypic and clinical data associated to AD. We used a new algorithm, the ANNs, aimed to map variables and search for connectivity among variables. We found specific variables associated to AD like cholesterol levels, the presence of variation in HMGCR enzyme and the age. Other factors such as the BMI, the amount of HDL and blood folate levels were also associated with AD. Pathogen infections, above all viral infections, have been previously associated to AD. The hypothesis suggests that virus and in particular herpes virus could enter the brain when an individual becomes older, perhaps because of a decline in the immune system. Our new hypothesis is that the presence of SNPs in our GWA gene study results in a genetic signature that might affect individual brain susceptibility to infection by herpes virus family during aging.

Statistical methods for analysis and processing of medical ultrasound: applications to segmentation and restoration

In this thesis two major topics inherent with medical ultrasound images are addressed: deconvolution and segmentation. In the first case a deconvolution algorithm is described allowing statistically consistent maximum a posteriori estimates of the tissue reflectivity to be restored. These estimates are proven to provide a reliable source of information for achieving an accurate characterization of biological tissues through the ultrasound echo. The second topic involves the definition of a semi automatic algorithm for myocardium segmentation in 2D echocardiographic images. The results show that the proposed method can reduce inter- and intra observer variability in myocardial contours delineation and is feasible and accurate even on clinical data.

Timing per l'inserimento in lista dei pazienti affetti da fibrosi cistica che necessitano di trapianto polmonare: casistica di un centro regionale di riferimento

Timing of waiting list entrance for patients with cystic fibrosis in need of pulmonary transplant: the experience of a regional referral centre Objective: Evaluation of parameters that can predict a rapid decay of general conditions of patients affected by Cystic Fibrosis (CF) with no specific criteria to be candidate to pulmonary transplant. Material and methods: Fifteen patients with CF who died for complications and 8 who underwent lung transplantation in the 2000-2010 decade, were enrolled. Clinical data 2 years before the event (body max index, FEV1%, number of EV antibiotic treatments per year, colonization with Methicillin-resistant Staphylococcus aureus (MRSA), pseudomonas aeruginosa mucosus, burkholderia cepacia, pulmonary allergic aspergilosis) were compared among the 2 groups. Results: Mean FEV1% was significantly higher and mean number of antibiotic treatment was lower in deceased than in the transplanted patients (p<0.002 and p<0.001 respectively). Although in patients who died there were no including criteria to enter the transplant list 2 years before the exitus, suggestive findings such as low BMI (17.3), high incidence of hepatic pathology (33.3%), diabetes (50%), and infections with MRSA infection (25%), Pseudomonas aeruginosa (83.3%) and burkholderia cepacia (8.3%) were found with no statistical difference with transplanted patients, suggesting those patients were at risk of severe prognosis. In patients who died, females were double than males. Conclusion: While evaluating patients with CF, negative prognostic factors such as the ones investigated in this study, should be considered to select individuals with high mortality risk who need stricter therapeutical approach and follow up. Inclusion of those patients in the transplant waiting list should be taken into account.

Sviluppo di un'applicazione bioinformatica per la gestione dei dati di antibiotico sensibilità di isolati clinici

Il problema dell'antibiotico-resistenza è un problema di sanità pubblica per affrontare il quale è necessario un sistema di sorveglianza basato sulla raccolta e l'analisi dei dati epidemiologici di laboratorio. Il progetto di dottorato è consistito nello sviluppo di una applicazione web per la gestione di tali dati di antibiotico sensibilità di isolati clinici utilizzabile a livello di ospedale. Si è creata una piattaforma web associata a un database relazionale per avere un’applicazione dinamica che potesse essere aggiornata facilmente inserendo nuovi dati senza dover manualmente modificare le pagine HTML che compongono l’applicazione stessa. E’ stato utilizzato il database open-source MySQL in quanto presenta numerosi vantaggi: estremamente stabile, elevate prestazioni, supportato da una grande comunità online ed inoltre gratuito. Il contenuto dinamico dell’applicazione web deve essere generato da un linguaggio di programmazione tipo “scripting” che automatizzi operazioni di inserimento, modifica, cancellazione, visualizzazione di larghe quantità di dati. E’ stato scelto il PHP, linguaggio open-source sviluppato appositamente per la realizzazione di pagine web dinamiche, perfettamente utilizzabile con il database MySQL. E’ stata definita l’architettura del database creando le tabelle contenenti i dati e le relazioni tra di esse: le anagrafiche, i dati relativi ai campioni, microrganismi isolati e agli antibiogrammi con le categorie interpretative relative al dato antibiotico. Definite tabelle e relazioni del database è stato scritto il codice associato alle funzioni principali: inserimento manuale di antibiogrammi, importazione di antibiogrammi multipli provenienti da file esportati da strumenti automatizzati, modifica/eliminazione degli antibiogrammi precedenti inseriti nel sistema, analisi dei dati presenti nel database con tendenze e andamenti relativi alla prevalenza di specie microbiche e alla chemioresistenza degli stessi, corredate da grafici. Lo sviluppo ha incluso continui test delle funzioni via via implementate usando reali dati clinici e sono stati introdotti appositi controlli e l’introduzione di una semplice e pulita veste grafica.