Reliability and consistency affect the integration of visual depth cues

Abstract Originalsprache (englisch) Visual perception relies on a two-dimensional projection of the viewed scene on the retinas of both eyes. Thus, visual depth has to be reconstructed from a number of different cues that are subsequently integrated to obtain robust depth percepts. Existing models of sensory integration are mainly based on the reliabilities of individual cues and disregard potential cue interactions. In the current study, an extended Bayesian model is proposed that takes into account both cue reliability and consistency. Four experiments were carried out to test this model's predictions. Observers had to judge visual displays of hemi-cylinders with an elliptical cross section, which were constructed to allow for an orthogonal variation of several competing depth cues. In Experiment 1 and 2, observers estimated the cylinder's depth as defined by shading, texture, and motion gradients. The degree of consistency among these cues was systematically varied. It turned out that the extended Bayesian model provided a better fit to the empirical data compared to the traditional model which disregards covariations among cues. To circumvent the potentially problematic assessment of single-cue reliabilities, Experiment 3 used a multiple-observation task, which allowed for estimating perceptual weights from multiple-cue stimuli. Using the same multiple-observation task, the integration of stereoscopic disparity, shading, and texture gradients was examined in Experiment 4. It turned out that less reliable cues were downweighted in the combined percept. Moreover, a specific influence of cue consistency was revealed. Shading and disparity seemed to be processed interactively while other cue combinations could be well described by additive integration rules. These results suggest that cue combination in visual depth perception is highly flexible and depends on single-cue properties as well as on interrelations among cues. The extension of the traditional cue combination model is defended in terms of the necessity for robust perception in ecologically valid environments and the current findings are discussed in the light of emerging computational theories and neuroscientific approaches.

Specific enzymatic cleavage and payload release from peptide-based hybrid nanocapsules

Within this thesis, new approaches for the concepts of peptide-polymer conjugates and peptide-based hybrid nanomaterials are investigated. In the first part, the synthesis of a triblock polymer-peptide-polymer is carried out following a typical peptide coupling reaction, both in solution and on solid-phase. The peptide sequence is chosen, so that it is cleaved by an enzyme preparation of trypsin. End-functionalized polystyrene is used as a model hydrophobic polymer and coupled to the peptide sequence. The results show successful coupling reactions in both methods, while the solid phase method produced a more defined product. Suspensions, consisting of peptide-polymer conjugates particles, are prepared in water by ultrasonication. In contact with the enzyme, the peptide constituting the conjugated particles is cleaved. This demonstrates the enzymatic cleavage in heterophase of enzymatic sequence bond to hydrophobic polymers, and is of great interest for the encapsulation and delivery of hydrophobic molecules.rnA second approach is the preparation of peptide-based hybrid nanocapsules. This is achieved by interfacial polyaddition in inverse miniemulsion with the peptide sequence functionalized with additional amino acids. A method suitable to the use of a peptide sequence for interfacial polyaddition was developed. It is shown that, the polarity of the dispersed phase influences the structures prepared, from particle-like to polymeric shell with a liquid core.rnThe peptide sequence is equipped with a FRET pair (more exactly, an internally-quenched fluorescent system) which allows the real-time monitoring of the enzymatic cleavage of the recognition site. This system shows the successful cleavage of the peptide-based nanocapsules when trypsin preparation is added to the suspensions. A water-soluble fluorescent polymer is efficiently entrapped and its possible use as marker for the capsules is highlighted. Furthermore, a small water-soluble fluorescent dye (SR-101) is successfully encapsulated and the encapsulation efficiency as a function of the functionality of the peptide and the amount of comonomer equivalent (toluene diisocyanate) is studied. The dye is encapsulated at such a high concentration, that self-quenching occurs. Thus, the release of the encapsulated dye triggered by the enzymatic cleavage of the peptide results in a fluorescence recovery of the dye. The fluorescence recovery of the FRET pair in the peptide and of the encapsulated dye correlate well.rnFinally, nanocapsules based on a hepsin-cleavable peptide sequence are prepared. Hepsin is an enzyme, which is highly upregulated in prostate cancer cells. The cleavage of the nanocapsules is investigated with healthy and “cancerous” (hepsin-expressing) cell cultures. The degradation, followed via fluorescence recovery of the FRET system, is faster for the suspensions introduced in the hepsin expressing cell cultures.rnIn summary, this work tackles the domain of responsive nanomaterials for drug delivery from a new perspective. It presents the adaptation of the miniemulsion process for hybrid peptide-based materials, and their successful use in preparing specific enzyme-responsive nanoparticles, with hydrophilic payload release properties.rn

Classificazione di oggetti in immagini attraverso il modello Bag of Visual Words

Generic object recognition is an important function of the human visual system and everybody finds it highly useful in their everyday life. For an artificial vision system it is a really hard, complex and challenging task because instances of the same object category can generate very different images, depending of different variables such as illumination conditions, the pose of an object, the viewpoint of the camera, partial occlusions, and unrelated background clutter. The purpose of this thesis is to develop a system that is able to classify objects in 2D images based on the context, and identify to which category the object belongs to. Given an image, the system can classify it and decide the correct categorie of the object. Furthermore the objective of this thesis is also to test the performance and the precision of different supervised Machine Learning algorithms in this specific task of object image categorization. Through different experiments the implemented application reveals good categorization performances despite the difficulty of the problem. However this project is open to future improvement; it is possible to implement new algorithms that has not been invented yet or using other techniques to extract features to make the system more reliable. This application can be installed inside an embedded system and after trained (performed outside the system), so it can become able to classify objects in a real-time. The information given from a 3D stereocamera, developed inside the department of Computer Engineering of the University of Bologna, can be used to improve the accuracy of the classification task. The idea is to segment a single object in a scene using the depth given from a stereocamera and in this way make the classification more accurate.

Natural compounds Camptothecin and Triptolide: highly specific enzyme inhibitors and tools to dissect transcriptional functions

With this work I elucidated new and unexpected mechanisms of two strong and highly specific transcription inhibitors: Triptolide and Campthotecin. Triptolide (TPL) is a diterpene epoxide derived from the Chinese plant Trypterigium Wilfoordii Hook F. TPL inhibits the ATPase activity of XPB, a subunit of the general transcription factor TFIIH. In this thesis I found that degradation of Rbp1 (the largest subunit of RNA Polymerase II) caused by TPL treatments, is preceded by an hyperphosphorylation event at serine 5 of the carboxy-terminal domain (CTD) of Rbp1. This event is concomitant with a block of RNA Polymerase II at promoters of active genes. The enzyme responsible for Ser5 hyperphosphorylation event is CDK7. Notably, CDK7 downregulation rescued both Ser5 hyperphosphorylation and Rbp1 degradation triggered by TPL. Camptothecin (CPT), derived from the plant Camptotheca acuminata, specifically inhibits topoisomerase 1 (Top1). We first found that CPT induced antisense transcription at divergent CpG islands promoter. Interestingly, by immunofluorescence experiments, CPT was found to induce a burst of R loop structures (DNA/RNA hybrids) at nucleoli and mitochondria. We then decided to investigate the role of Top1 in R loop homeostasis through a short interfering RNA approach (RNAi). Using DNA/RNA immunoprecipitation techniques coupled to NGS I found that Top1 depletion induces an increase of R loops at a genome-wide level. We found that such increase occurs on the entire gene body. At a subset of loci R loops resulted particularly stressed after Top1 depletion: some of these genes showed the formation of new R loops structures, whereas other loci showed a reduction of R loops. Interestingly we found that new peaks usually appear at tandem or divergent genes in the entire gene body, while losses of R loop peaks seems to be a feature specific of 3’ end regions of convergent genes.

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.

Functional characterization of the placenta specific protein PLAC1 and its use for cancer immunotherapy

Summary Antibody-based cancer therapies have been successfully introduced into the clinic and have emerged as the most promising therapeutics in oncology. The limiting factor regarding the development of therapeutical antibody vaccines is the identification of tumor-associated antigens. PLAC1, the placenta-specific protein 1, was categorized for the first time by the group of Prof. Sahin as such a tumor-specific antigen. Within this work PLAC1 was characterized using a variety of biochemical methods. The protein expression profile, the cellular localization, the conformational state and especially the interacting partners of PLAC1 and its functionality in cancer were analyzed. Analysis of the protein expression profile of PLAC1 in normal human tissue confirms the published RT-PCR data. Except for placenta no PLAC1 expression was detectable in any other normal human tissue. Beyond, an increased PLAC1 expression was detected in several cancer cell lines derived of trophoblastic, breast and pancreatic lineage emphasizing its properties as tumor-specific antigen. rnThe cellular localization of PLAC1 revealed that PLAC1 contains a functional signal peptide which conducts the propeptide to the endoplasmic reticulum (ER) and results in the secretion of PLAC1 by the secretory pathway. Although PLAC1 did not exhibit a distinct transmembrane domain, no unbound protein was detectable in the cell culture supernatant of overexpressing cells. But by selective isolation of different cellular compartments PLAC1 was clearly enriched within the membrane fraction. Using size exclusion chromatography PLAC1 was characterized as a highly aggregating protein that forms a network of high molecular multimers, consisting of a mixture of non-covalent as well as covalent interactions. Those interactions were formed by PLAC1 with itself and probably other cellular components and proteins. Consequently, PLAC1 localize outside the cell, where it is associated to the membrane forming a stable extracellular coat-like structure.rnThe first mechanistic hint how PLAC1 promote cancer cell proliferation was achieved identifying the fibroblast growth factor FGF7 as a specific interacting partner of PLAC1. Moreover, it was clearly shown that PLAC1 as well as FGF7 bind to heparin, a glycosaminoglycan of the ECM that is also involved in FGF-signaling. The participation of PLAC1 within this pathway was approved after co-localizing PLAC1, FGF7 and the FGF7 specific receptor (FGFR2IIIb) and identifying the formation of a trimeric complex (PLAC1, FGF7 and the specific receptor FGFR2IIIb). Especially this trimeric complex revealed the role of PLAC1. Binding of PLAC1 together with FGF7 leads to the activation of the intracellular tyrosine kinase of the FGFR2IIIb-receptor and mediate the direct phosphorylation of the AKT-kinase. In the absence of PLAC1, no FGF7 mediated phosphorylation of AKT was observed. Consequently the function of PLAC1 was clarified: PLAC1 acts as a co-factor by stimulating proliferation by of the FGF7-FGFR2 signaling pathway.rnAll together, these novel biochemical findings underline that the placenta specific protein PLAC1 could be a new target for cancer immunotherapy, especially considering its potential applicability for antibody therapy in tumor patients.

Estrazione terminologica automatica: sistemi a confronto

In any terminological study, candidate term extraction is a very time-consuming task. Corpus analysis tools have automatized some processes allowing the detection of relevant data within the texts, facilitating term candidate selection as well. Nevertheless, these tools are (normally) not specific for terminology research; therefore, the units which are automatically extracted need manual evaluation. Over the last few years some software products have been specifically developed for automatic term extraction. They are based on corpus analysis, but use linguistic and statistical information to filter data more precisely. As a result, the time needed for manual evaluation is reduced. In this framework, we tried to understand if and how these new tools can really be an advantage. In order to develop our project, we simulated a terminology study: we chose a domain (i.e. legal framework for medicinal products for human use) and compiled a corpus from which we extracted terms and phraseologisms using AntConc, a corpus analysis tool. Afterwards, we compared our list with the lists extracted automatically from three different tools (TermoStat Web, TaaS e Sketch Engine) in order to evaluate their performance. In the first chapter we describe some principles relating to terminology and phraseology in language for special purposes and show the advantages offered by corpus linguistics. In the second chapter we illustrate some of the main concepts of the domain selected, as well as some of the main features of legal texts. In the third chapter we describe automatic term extraction and the main criteria to evaluate it; moreover, we introduce the term-extraction tools used for this project. In the fourth chapter we describe our research method and, in the fifth chapter, we show our results and draw some preliminary conclusions on the performance and usefulness of term-extraction tools.

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.

La comunicazione aziendale tra redazione e traduzione: Il caso di ipack srl.

This dissertation is the result of my participation in the Language Toolkit project, a recent collaboration between the Chamber of Commerce of Forlì and the School of Foreign Languages and Literatures, Interpreting and Translation at the University of Bologna, which aims to make students meet with the companies of our territory, in this case Ipack, based in Mercato Saraceno (FC). My dissertation is a specialized translation work from Italian into English of two documents that were entrusted to me: the declaration of compliance of Ipack’s products and a summary of the quality manual. They are two high technical texts and, therefore, the translation task required a preliminary phase of research on the topics and on the terminology of this specific domain. The dissertation consists of five chapters. The first chapter briefly introduces the company with which I collaborated for my dissertation project and provides an overview of business communication and a brief classification of Ipack’s communication tools. The second chapter covers the background topics, namely food packaging and quality management systems within companies. The third chapter concerns the analysis of the two texts, describing the intra-textual and extra-textual aspects, as well as the morphosyntaxical and lexical features. The fourth chapter is dedicated to the revision work on one of the two texts, the one about quality procedures. In the commentary following my review, I explain the methodology and the strategies that I used and I also provide some extended examples of the main changes applied to the original text, with respect to both content and linguistic features. Finally, the fifth chapter focuses on the translation of the texts followed by a commentary that explains the work methodology, resources and my translation choices, accompanied by practical examples.

Specific processing of tenascin-C by the metalloprotease meprinbeta neutralizes its inhibition of cell spreading

The metalloprotease meprin has been implicated in tissue remodelling due to its capability to degrade extracellular matrix components. Here, we investigated the susceptibility of tenascin-C to cleavage by meprinbeta and the functional properties of its proteolytic fragments. A set of monoclonal antibodies against chicken and human tenascin-C allowed the mapping of proteolytic fragments generated by meprinbeta. In chicken tenascin-C, meprinbeta processed all three major splicing variants by removal of 10kDa N-terminal and 38kDa C-terminal peptides, leaving a large central part of subunits intact. A similar cleavage pattern was found for large human tenascin-C variant where two N-terminal peptides (10 or 15kDa) and two C-terminal fragments (40 and 55kDa) were removed from the intact subunit. N-terminal sequencing revealed the exact amino acid positions of cleavage sites. In both chicken and human tenascin-C N-terminal cleavages occurred just before and/or after the heptad repeats involved in subunit oligomerization. In the human protein, an additional cleavage site was identified in the alternative fibronectin type III repeat D. Whereas all these sites are known to be attacked by several other proteases, a unique cleavage by meprinbeta was located to the 7th constant fibronectin type III repeat in both chicken and human tenascin-C, thereby removing the C-terminal domain involved in its anti-adhesive activity. In cell adhesion assays meprinbeta-digested human tenascin-C was not able to interfere with fibronectin-mediated cell spreading, confirming cleavage in the anti-adhesive domain. Whereas the expression of meprinbeta and tenascin-C does not overlap in normal colon tissue, inflamed lesions of the mucosa from patients with Crohn's disease exhibited many meprinbeta-positive leukocytes in regions where tenascin-C was strongly induced. Our data indicate that, at least under pathological conditions, meprinbeta might attack specific functional sites in tenascin-C that are important for its oligomerization and anti-adhesive activity.

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.

Gray matter volume differences specific to formal thought disorder in schizophrenia

Formal thought disorder (FTD) is one of the main symptoms of schizophrenia. To date there are no whole brain volumetric studies investigating gray matter (GM) differences specifically associated with FTD. Here, we studied 20 right-handed schizophrenia patients that differed in the severity of formal thought disorder and 20 matched healthy controls, using voxel-based morphometry (VBM). The severity of FTD was measured with the Scale for the Assessment of Thought, Language, and Communication. The severity was negatively correlated with the GM volume of the left superior temporal sulcus, the left temporal pole, the right middle orbital gyrus and the right cuneus/lingual gyrus. Structural abnormalities specific for FTD were found to be unrelated to GM differences associated with schizophrenia in general. The specific GM abnormalities within the left temporal lobe may help to explain language disturbances included in FTD.

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).

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.

The Bern psychopathology scale for the assessment of system-specific psychotic symptoms

The translation from psychiatric core symptoms to brain functions and vice versa is a largely unresolved issue. In particular, the search for disorders of single brain regions explaining classical symptoms has not yielded the expected results. Based on the assumption that the psychopathology of psychosis is related to a functional imbalance of higher-order brain systems, the authors focused on three specific candidate brain circuitries, namely the language, and limbic and motor systems. These domains are of particular interest for understanding the disastrous communication breakdown during psychotic disorders. Core symptoms of psychosis were mapped on these domains by shaping their definitions in order to match the related brain functions. The resulting psychopathological assessment scale was tested for interrater reliability and internal consistency in a group of 168 psychotic patients. The items of the scale were reliable and a principal component analysis (PCA) was best explained by a solution resembling the three candidate systems. Based on the results, the scale was optimized as an instrument to identify patient subgroups characterized by a prevailing dysfunction of one or more of these systems. In conclusion, the scale is apt to distinguish symptom domains related to the activity of defined brain systems. PCA showed a certain degree of independence of the system-specific symptom clusters within the patient group, indicating relative subgroups of psychosis. The scale is understood as a research instrument to investigate psychoses based on a system-oriented approach. Possible immediate advantages in the clinical application of the understanding of psychoses related to system-specific symptom domains are also discussed.