High-Speed Laser Processing of Thin Single and Multi-Layer Films

Theoretical models are developed for the continuous-wave and pulsed laser incision and cut of thin single and multi-layer films. A one-dimensional steady-state model establishes the theoretical foundations of the problem by combining a power-balance integral with heat flow in the direction of laser motion. In this approach, classical modelling methods for laser processing are extended by introducing multi-layer optical absorption and thermal properties. The calculation domain is consequently divided in correspondence with the progressive removal of individual layers. A second, time-domain numerical model for the short-pulse laser ablation of metals accounts for changes in optical and thermal properties during a single laser pulse. With sufficient fluence, the target surface is heated towards its critical temperature and homogeneous boiling or "phase explosion" takes place. Improvements are seen over previous works with the more accurate calculation of optical absorption and shielding of the incident beam by the ablation products. A third, general time-domain numerical laser processing model combines ablation depth and energy absorption data from the short-pulse model with two-dimensional heat flow in an arbitrary multi-layer structure. Layer removal is the result of both progressive short-pulse ablation and classical vaporisation due to long-term heating of the sample. At low velocity, pulsed laser exposure of multi-layer films comprising aluminium-plastic and aluminium-paper are found to be characterised by short-pulse ablation of the metallic layer and vaporisation or degradation of the others due to thermal conduction from the former. At high velocity, all layers of the two films are ultimately removed by vaporisation or degradation as the average beam power is increased to achieve a complete cut. The transition velocity between the two characteristic removal types is shown to be a function of the pulse repetition rate. An experimental investigation validates the simulation results and provides new laser processing data for some typical packaging materials.

The inhibition of aerobic glycolysis as a therapeutic approach to improve cancer chemotherapy

The aim of the research project discussed in this thesis was to study the inhibition of aerobic glycolysis, that is the metabolic pathway exploited by cancer cells for the ATP generation. This observation has led to the evaluation of glycolytic inhibitors as potential anticancer agents. Lactate dehydrogenase (LDH) is the only enzyme whose inhibition should allow a blocking of aerobic glycolysis of tumor cells without damaging the normal cells which, in conditions of normal functional activity and sufficient oxygen supply, do not need this enzyme. In preliminar experiments we demonstrated that oxamic acid and tartronic acid, two LDH competitive inhibitors, impaired aerobic glycolysis and replication of cells from human hepatocellular carcinoma. Therefore, we proposed that the depletion of ATP levels in neoplastic cells, could improved the chemotherapeutic index of associated anticancer drugs; in particular, it was studied the association of oxamic acid and multi-targeted kinase inhibitors. A synergistic effect in combination with sorafenib was observed, and we demonstrated that this was related to the capacity of sorafenib to hinder the oxidative phosphorylation, so that cells were more dependent to aerobic glycolysis. These results linked to LDH blockage encouraged us to search for LDH inhibitors more powerful than oxamic acid; thus, in collaboration with the Department of Pharmaceutical Sciences of Bologna University we identified a new molecule, galloflavin, able to inhibit both A and B isoforms of LDH enzyme. The effects of galloflavin were studied on different human cancer cell lines (hepatocellular carcinoma, breast cancer, Burkitt’s lymphoma). Although exhibiting different power on the tested cell lines, galloflavin was constantly found to inhibit lactate and ATP production and to induce cell death, mainly in the form of apoptosis. Finally, as LDH-A is able to bind single stranded DNA, thus stimulating cell transcription, galloflavin effects were also studied on this other LDH function.

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models

The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.

Study of PI3K/Akt signaling pathway as potential molecular target for T-cell acute lymphoblastic leukemia (T-ALL) treatment: pan-inhibition of PI3K catalitic isoforms as better therapeutic approach

Class I phosphatidylinositol 3-kinases (PI3Ks) are heterodimeric lipid kinases consisting of a regulatory subunit and one of four catalytic subunits (p110α, p110β, p110γ or p110δ). p110γ/p110δ PI3Ks are highly enriched in leukocytes. In general, PI3Ks regulate a variety of cellular processes including cell proliferation, survival and metabolism, by generating the second messenger phosphatidylinositol-3,4,5-trisphosphate (PtdIns(3,4,5)P3). Their activity is tightly regulated by the phosphatase and tensin homolog (PTEN) lipid phosphatase. PI3Ks are widely implicated in human cancers, and in particular are upregulated in T-cell acute lymphoblastic leukemia (T-ALL), mainly due to loss of PTEN function. These observations lend compelling weight to the application of PI3K inhibitors in the therapy of T-ALL. At present different compounds which target single or multiple PI3K isoforms have entered clinical trials. In the present research, it has been analyzed the therapeutic potential of the pan-PI3K inhibitor BKM120, an orally bioavailable 2,6-dimorpholino pyrimidine derivative, which has entered clinical trials for solid tumors, on both T-ALL cell lines and patient samples. BKM120 treatment resulted in cell cycle arrest and apoptosis, being cytotoxic to a panel of T-ALL cell lines and patient T-lymphoblasts. Remarkably, BKM120 synergized with chemotherapeutic agents currently used for treating T-ALL patients. BKM120 efficacy was confirmed in in vivo studies to a subcutaneous xenotransplant model of human T-ALL. Because it is still unclear which agents among isoform-specific or pan inhibitors can achieve the greater efficacy, further analyses have been conducted to investigate the effects of PI3K inhibition, in order to elucidate the mechanisms responsible for the proliferative impairment of T-ALL. Overall, these results indicated that BKM120 may be an efficient treatment for T-ALLs that have aberrant up-regulation of the PI3K signaling pathway and strongly support clinical application of pan-class I PI3K rather than single-isoform inhibitors in T-ALL treatment.

Secondary Microseisms Characterization and Green’s Function Extraction at the Larderello-Travale Geothermal Field (Italy)

Over the past ten years, the cross-correlation of long-time series of ambient seismic noise (ASN) has been widely adopted to extract the surface-wave part of the Green’s Functions (GF). This stochastic procedure relies on the assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed to the sea-wave climate. Consequently, marked directional properties may be observed, which call for accurate investigation about location and temporal evolution of the ASN-sources before attempting any GF retrieval. Within this general context, this thesis is aimed at a thorough investigation about feasibility and robustness of the noise-based methods toward the imaging of complex geological structures at the local (∼10-50km) scale. The study focused on the analysis of an extended (11 months) seismological data set collected at the Larderello-Travale geothermal field (Italy), an area for which the underground geological structures are well-constrained thanks to decades of geothermal exploration. Focusing on the secondary microseism band (SM;f>0.1Hz), I first investigate the spectral features and the kinematic properties of the noise wavefield using beamforming analysis, highlighting a marked variability with time and frequency. For the 0.1-0.3Hz frequency band and during Spring- Summer-time, the SMs waves propagate with high apparent velocities and from well-defined directions, likely associated with ocean-storms in the south- ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back- azimuths is more scattered, thus indicating that this frequency-band is the most appropriate for the application of stochastic techniques. For this latter frequency interval, I tested two correlation-based methods, acting in the time (NCF) and frequency (modified-SPAC) domains, respectively yielding esti- mates of the group- and phase-velocity dispersions. Velocity data provided by the two methods are markedly discordant; comparison with independent geological and geophysical constraints suggests that NCF results are more robust and reliable.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Variability of lung function predicts loss of asthma control following withdrawal of inhaled corticosteroid treatment

BACKGROUND One aspect of a multidimensional approach to understanding asthma as a complex dynamic disease is to study how lung function varies with time. Variability measures of lung function have been shown to predict response to beta(2)-agonist treatment. An investigation was conducted to determine whether mean, coefficient of variation (CV) or autocorrelation, a measure of short-term memory, of peak expiratory flow (PEF) could predict loss of asthma control following withdrawal of regular inhaled corticosteroid (ICS) treatment, using data from a previous study. METHODS 87 adult patients with mild to moderate asthma who had been taking ICS at a constant dose for at least 6 months were monitored for 2-4 weeks. ICS was then withdrawn and monitoring continued until loss of control occurred as per predefined criteria. Twice-daily PEF was recorded during monitoring. Associations between loss of control and mean, CV and autocorrelation of morning PEF within 2 weeks pre- and post-ICS withdrawal were assessed using Cox regression analysis. Predictive utility was assessed using receiver operator characteristics. RESULTS 53 out of 87 patients had sufficient PEF data over the required analysis period. The mean (389 vs 370 l/min, p<0.0001) and CV (4.5% vs 5.6%, p=0.007) but not autocorrelation of PEF changed significantly from prewithdrawal to postwithdrawal in subjects who subsequently lost control, and were unaltered in those who did not. These changes were related to time to loss of control. CV was the most consistent predictor, with similar sensitivity and sensitivity to exhaled nitric oxide. CONCLUSION A simple, easy to obtain variability measure of daily lung function such as the CV may predict loss of asthma control within the first 2 weeks of ICS withdrawal.

The venom composition of the parasitic wasp Chelonus inanitus resolved by combined expressed sequence tags analysis and proteomic approach

Background Parasitic wasps constitute one of the largest group of venomous animals. Although some physiological effects of their venoms are well documented, relatively little is known at the molecular level on the protein composition of these secretions. To identify the majority of the venom proteins of the endoparasitoid wasp Chelonus inanitus (Hymenoptera: Braconidae), we have randomly sequenced 2111 expressed sequence tags (ESTs) from a cDNA library of venom gland. In parallel, proteins from pure venom were separated by gel electrophoresis and individually submitted to a nano-LC-MS/MS analysis allowing comparison of peptides and ESTs sequences. Results About 60% of sequenced ESTs encoded proteins whose presence in venom was attested by mass spectrometry. Most of the remaining ESTs corresponded to gene products likely involved in the transcriptional and translational machinery of venom gland cells. In addition, a small number of transcripts were found to encode proteins that share sequence similarity with well-known venom constituents of social hymenopteran species, such as hyaluronidase-like proteins and an Allergen-5 protein. An overall number of 29 venom proteins could be identified through the combination of ESTs sequencing and proteomic analyses. The most highly redundant set of ESTs encoded a protein that shared sequence similarity with a venom protein of unknown function potentially specific of the Chelonus lineage. Venom components specific to C. inanitus included a C-type lectin domain containing protein, a chemosensory protein-like protein, a protein related to yellow-e3 and ten new proteins which shared no significant sequence similarity with known sequences. In addition, several venom proteins potentially able to interact with chitin were also identified including a chitinase, an imaginal disc growth factor-like protein and two putative mucin-like peritrophins. Conclusions The use of the combined approaches has allowed to discriminate between cellular and truly venom proteins. The venom of C. inanitus appears as a mixture of conserved venom components and of potentially lineage-specific proteins. These new molecular data enrich our knowledge on parasitoid venoms and more generally, might contribute to a better understanding of the evolution and functional diversity of venom proteins within Hymenoptera.

Cell therapies for heart function recovery: focus on myocardial tissue engineering and nanotechnologies

Cell therapies have gained increasing interest and developed in several approaches related to the treatment of damaged myocardium. The results of multiple clinical trials have already been reported, almost exclusively involving the direct injection of stem cells. It has, however, been postulated that the efficiency of injected cells could possibly be hindered by the mechanical trauma due to the injection and their low survival in the hostile environment. It has indeed been demonstrated that cell mortality due to the injection approaches 90%. Major issues still need to be resolved and bed-to-bench followup is paramount to foster clinical implementations. The tissue engineering approach thus constitutes an attractive alternative since it provides the opportunity to deliver a large number of cells that are already organized in an extracellular matrix. Recent laboratory reports confirmed the interest of this approach and already encouraged a few groups to investigate it in clinical studies. We discuss current knowledge regarding engineered tissue for myocardial repair or replacement and in particular the recent implementation of nanotechnological approaches.

Endobronchial donor pre-treatment with ventavis: is a second administration during reperfusion beneficial to optimize post-ischemic function of non-heart beating donor lungs?

BACKGROUND: Lung retrieval from non-heart-beating donors (NHBD) has been introduced into clinical practice successfully. However, because of potentially deleterious effects of warm ischemia on microvascular integrity, use of NHBD lungs is limited by short tolerable time periods before preservation. Recently, improvement of NHBD graft function was demonstrated by donor pre-treatment using aerosolized Ventavis (Schering Inc., Berlin, Germany). Currently, there is no information whether additional application of this approach in reperfusion can further optimize immediate graft function. MATERIAL AND METHODS: Asystolic pigs (n = 5/group) were ventilated for 180-min of warm ischemia (groups 1-3). In groups 2 and 3, 100 microg Ventavis were aerosolized over 30-min using an ultrasonic nebulizer (Optineb). Lungs were then retrogradely preserved with Perfadex and stored for 3-h. After left lung transplantation and contralateral lung exclusion, grafts were reperfused for 6-h. Only in group 3, another dose of 100 microg Ventavis was aerosolized during the first 30-min of reperfusion. Hemodynamics, pO2/FiO2 and dynamic compliance were monitored continuously and compared to controls. Intraalveolar edema was quantified stereologically, and extravascular-lung-water-index (EVLWI) was measured. Statistics comprised ANOVA analysis with repeated measurements. RESULTS: Dynamic compliance was significantly lower in both Ventavis groups, but additional administration did not result in further improvement. Oxygenation, pulmonary hemodynamics, EVLWI and intraalveolar edema formation were comparable between groups. CONCLUSIONS: Alveolar deposition of Ventavis in NHBD lungs before preservation significantly improves dynamic lung compliance and represents an important strategy for improvement of preservation quality and expansion of warm ischemic intervals. However, additional application of this method in early reperfusion is of no benefit.

A Note on the Asymptotic Variance of Survival Function in the Semi-Markov Model

In Malani and Neilsen (1992) we have proposed alternative estimates of survival function (for time to disease) using a simple marker that describes time to some intermediate stage in a disease process. In this paper we derive the asymptotic variance of one such proposed estimator using two different methods and compare terms of order 1/n when there is no censoring. In the absence of censoring the asymptotic variance obtained using the Greenwood type approach converges to exact variance up to terms involving 1/n. But the asymptotic variance obtained using the theory of the counting process and results from Voelkel and Crowley (1984) on semi-Markov processes has a different term of order 1/n. It is not clear to us at this point why the variance formulae using the latter approach give different results.

A graph theoretic approach to testing associations between disparate sources of functional genomic data

The last few years have seen the advent of high-throughput technologies to analyze various properties of the transcriptome and proteome of several organisms. The congruency of these different data sources, or lack thereof, can shed light on the mechanisms that govern cellular function. A central challenge for bioinformatics research is to develop a unified framework for combining the multiple sources of functional genomics information and testing associations between them, thus obtaining a robust and integrated view of the underlying biology. We present a graph theoretic approach to test the significance of the association between multiple disparate sources of functional genomics data by proposing two statistical tests, namely edge permutation and node label permutation tests. We demonstrate the use of the proposed tests by finding significant association between a Gene Ontology-derived "predictome" and data obtained from mRNA expression and phenotypic experiments for Saccharomyces cerevisiae. Moreover, we employ the graph theoretic framework to recast a surprising discrepancy presented in Giaever et al. (2002) between gene expression and knockout phenotype, using expression data from a different set of experiments.

A Pseudolikelihood Approach for Simultaneous Analysis of Array Comparative Genomic Hybridizations (aCGH)

DNA sequence copy number has been shown to be associated with cancer development and progression. Array-based Comparative Genomic Hybridization (aCGH) is a recent development that seeks to identify the copy number ratio at large numbers of markers across the genome. Due to experimental and biological variations across chromosomes and across hybridizations, current methods are limited to analyses of single chromosomes. We propose a more powerful approach that borrows strength across chromosomes and across hybridizations. We assume a Gaussian mixture model, with a hidden Markov dependence structure, and with random effects to allow for intertumoral variation, as well as intratumoral clonal variation. For ease of computation, we base estimation on a pseudolikelihood function. The method produces quantitative assessments of the likelihood of genetic alterations at each clone, along with a graphical display for simple visual interpretation. We assess the characteristics of the method through simulation studies and through analysis of a brain tumor aCGH data set. We show that the pseudolikelihood approach is superior to existing methods both in detecting small regions of copy number alteration and in accurately classifying regions of change when intratumoral clonal variation is present.

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.