Multicentre study for a robust protocol in single-voxel spectroscopy: quantification of MRS signals by time-domain fitting algorithms

Magnetic Resonance Spectroscopy (MRS) is an advanced clinical and research application which guarantees a specific biochemical and metabolic characterization of tissues by the detection and quantification of key metabolites for diagnosis and disease staging. The "Associazione Italiana di Fisica Medica (AIFM)" has promoted the activity of the "Interconfronto di spettroscopia in RM" working group. The purpose of the study is to compare and analyze results obtained by perfoming MRS on scanners of different manufacturing in order to compile a robust protocol for spectroscopic examinations in clinical routines. This thesis takes part into this project by using the GE Signa HDxt 1.5 T at the Pavillion no. 11 of the S.Orsola-Malpighi hospital in Bologna. The spectral analyses have been performed with the jMRUI package, which includes a wide range of preprocessing and quantification algorithms for signal analysis in the time domain. After the quality assurance on the scanner with standard and innovative methods, both spectra with and without suppression of the water peak have been acquired on the GE test phantom. The comparison of the ratios of the metabolite amplitudes over Creatine computed by the workstation software, which works on the frequencies, and jMRUI shows good agreement, suggesting that quantifications in both domains may lead to consistent results. The characterization of an in-house phantom provided by the working group has achieved its goal of assessing the solution content and the metabolite concentrations with good accuracy. The goodness of the experimental procedure and data analysis has been demonstrated by the correct estimation of the T2 of water, the observed biexponential relaxation curve of Creatine and the correct TE value at which the modulation by J coupling causes the Lactate doublet to be inverted in the spectrum. The work of this thesis has demonstrated that it is possible to perform measurements and establish protocols for data analysis, based on the physical principles of NMR, which are able to provide robust values for the spectral parameters of clinical use.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Strumenti e framework per lo sviluppo di linguaggi di programmazione e linguaggi domain-specific in java

La tesi ha lo scopo di indagare le tecnologie disponibili per la realizzazione di linguaggi di programmazione e linguaggi domain specific in ambiente Java. In particolare, vengono proposti e analizzati tre strumenti presenti sul mercato: JavaCC, ANTLR e Xtext. Al termine dell’elaborato, il lettore dovrebbe avere un’idea generale dei principali meccanismi e sistemi utilizzati (come lexer, parser, AST, parse trees, etc.), oltre che del funzionamento dei tre tools presentati. Inoltre, si vogliono individuare vantaggi e svantaggi di ciascuno strumento attraverso un’analisi delle funzionalità offerte, così da fornire un giudizio critico per la scelta e la valutazione dei sistemi da utilizzare.

The lectin-like domain of tumor necrosis factor improves lung function after rat lung transplantation--potential role for a reduction in reactive oxygen species generation

To test the hypothesis that the lectin-like domain of tumor necrosis factor, mimicked by the TIP peptide, can improve lung function after unilateral orthotopic lung isotransplantation. Because of a lack of a specific treatment for ischemia reperfusion-mediated lung injury, accompanied by a disrupted barrier integrity and a dysfunctional alveolar liquid clearance, alternative therapies restoring these parameters after lung transplantation are required.

Reproducibility of retinal thickness measurements in patients with age-related macular degeneration using 3D Fourier-domain optical coherence tomography (OCT) (Topcon 3D-OCT 1000)

Conventional time-domain optical coherence tomography (OCT) has become an important tool for following dry or exudative age-related macular degeneration (AMD). Fourier-domain three-dimensional (3D) OCT was recently introduced. This study tested the reproducibility of 3D-OCT retinal thickness measurements in patients with dry and exudative AMD.

Small dense particles in the retina observable by spectral-domain optical coherence tomography in age-related macular degeneration

To observe detailed changes in neurosensory retinal structure after anti-VEGF upload in age-related macular degeneration (AMD), by using spectral domain optical coherence tomography (SD-OCT).

Spectral-domain optical coherence tomography use in macular diseases: a review

The introduction of spectral-domain optical coherence tomography (SD-OCT) has improved the clinical value for assessment of the eyes with macular disease. This article reviews the advances of SD-OCT for the diagnostic of various macular diseases. These include vitreomacular traction syndrome, cystoid macular edema/diabetic macular edema, epiretinal membranes, full-thickness macular holes, lamellar holes, pseudoholes, microholes, and schisis from myopia. Besides offering new insights into the pathogenesis of macular abnormalities, SD-OCT is a valuable tool for monitoring macular disease.

Coronary optical frequency domain imaging (OFDI) for in vivo evaluation of stent healing: comparison with light and electron microscopy

Coronary late stent thrombosis, a rare but devastating complication, remains an important concern in particular with the increasing use of drug-eluting stents. Notably, pathological studies have indicated that the proportion of uncovered coronary stent struts represents the best morphometric predictor of late stent thrombosis. Intracoronary optical frequency domain imaging (OFDI), a novel second-generation optical coherence tomography (OCT)-derived imaging method, may allow rapid imaging for the detection of coronary stent strut coverage with a markedly higher precision when compared with intravascular ultrasound, due to a microscopic resolution (axial approximately 10-20 microm), and at a substantially increased speed of image acquisition when compared with first-generation time-domain OCT. However, a histological validation of coronary OFDI for the evaluation of stent strut coverage in vivo is urgently needed. Hence, the present study was designed to evaluate the capacity of coronary OFDI by electron (SEM) and light microscopy (LM) analysis to detect and evaluate stent strut coverage in a porcine model.

Fast kinase domain-containing protein 3 is a mitochondrial protein essential for cellular respiration

Fas-activated serine/threonine phosphoprotein (FAST) is the founding member of the FAST kinase domain-containing protein (FASTKD) family that includes FASTKD1-5. FAST is a sensor of mitochondrial stress that modulates protein translation to promote the survival of cells exposed to adverse conditions. Mutations in FASTKD2 have been linked to a mitochondrial encephalomyopathy that is associated with reduced cytochrome c oxidase activity, an essential component of the mitochondrial electron transport chain. We have confirmed the mitochondrial localization of FASTKD2 and shown that all FASTKD family members are found in mitochondria. Although human and mouse FASTKD1-5 genes are expressed ubiquitously, some of them are most abundantly expressed in mitochondria-enriched tissues. We have found that RNA interference-mediated knockdown of FASTKD3 severely blunts basal and stress-induced mitochondrial oxygen consumption without disrupting the assembly of respiratory chain complexes. Tandem affinity purification reveals that FASTKD3 interacts with components of mitochondrial respiratory and translation machineries. Our results introduce FASTKD3 as an essential component of mitochondrial respiration that may modulate energy balance in cells exposed to adverse conditions by functionally coupling mitochondrial protein synthesis to respiration.

Effects on choroidal neovascularization after anti-VEGF Upload using intravitreal ranibizumab, as determined by spectral domain-optical coherence tomography

It is unclear whether anti-VEGF monotherapy in age-related macular degeneration (AMD) achieves morphologic CNV regression or only stops further CNV growth. In this study, spectral domain-optical coherence tomography (SD-OCT) was used to image CNV structure before and after anti-VEGF treatment.

Use of intraoperative fourier-domain anterior segment optical coherence tomography during descemet stripping endothelial keratoplasty

To evaluate the intraoperative use of handheld Fourier-domain optical coherence tomography (OCT) during Descemet stripping automated endothelial keratoplasty (DSAEK) to assess the donor-host interface.

Repeatability of nerve fiber layer thickness measurements in patients with glaucoma and without glaucoma using spectral-domain and time-domain OCT

The aim of this work is to assess the repeatability of spectral-domain-OCT (SD-OCT) retinal nerve fiber layer thickness (RNFL) thickness measurements in a non-glaucoma group and patients with glaucoma and to compare these results to conventional time-domain-OCT (TD-OCT).

Femur Specific Polyaffine Model to Regularize the Log-Domain Demons Registration

Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.