6 resultados para Selection tool

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


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This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

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In the last decade, the reverse vaccinology approach shifted the paradigm of vaccine discovery from conventional culture-based methods to high-throughput genome-based approaches for the development of recombinant protein-based vaccines against pathogenic bacteria. Besides reaching its main goal of identifying new vaccine candidates, this new procedure produced also a huge amount of molecular knowledge related to them. In the present work, we explored this knowledge in a species-independent way and we performed a systematic in silico molecular analysis of more than 100 protective antigens, looking at their sequence similarity, domain composition and protein architecture in order to identify possible common molecular features. This meta-analysis revealed that, beside a low sequence similarity, most of the known bacterial protective antigens shared structural/functional Pfam domains as well as specific protein architectures. Based on this, we formulated the hypothesis that the occurrence of these molecular signatures can be predictive of possible protective properties of other proteins in different bacterial species. We tested this hypothesis in Streptococcus agalactiae and identified four new protective antigens. Moreover, in order to provide a second proof of the concept for our approach, we used Staphyloccus aureus as a second pathogen and identified five new protective antigens. This new knowledge-driven selection process, named MetaVaccinology, represents the first in silico vaccine discovery tool based on conserved and predictive molecular and structural features of bacterial protective antigens and not dependent upon the prediction of their sub-cellular localization.

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Bone metastases are responsible for different clinical complications defined as skeletal-related events (SREs) such as pathologic fractures, spinal cord compression, hypercalcaemia, bone marrow infiltration and severe bone pain requiring palliative radiotherapy. The general aim of these three years research period was to improve the management of patients with bone metastases through two different approaches of translational research. Firstly in vitro preclinical tests were conducted on breast cancer cells and on indirect co-colture of cancer cells and osteoclasts to evaluate bone targeted therapy singly and in combination with conventional chemotherapy. The study suggests that zoledronic acid has an antitumor activity in breast cancer cell lines. Its mechanism of action involves the decrease of RAS and RHO, as in osteoclasts. Repeated treatment enhances antitumor activity compared to non-repeated treatment. Furthermore the combination Zoledronic Acid + Cisplatin induced a high antitumoral activity in the two triple-negative lines MDA-MB-231 and BRC-230. The p21, pMAPK and m-TOR pathways were regulated by this combined treatment, particularly at lower Cisplatin doses. A co-colture system to test the activity of bone-targeted molecules on monocytes-breast conditioned by breast cancer cells was also developed. Another important criticism of the treatment of breast cancer patients, is the selection of patients who will benefit of bone targeted therapy in the adjuvant setting. A retrospective case-control study on breast cancer patients to find new predictive markers of bone metastases in the primary tumors was performed. Eight markers were evaluated and TFF1 and CXCR4 were found to discriminate between patients with relapse to bone respect to patients with no evidence of disease. In particular TFF1 was the most accurate marker reaching a sensitivity of 63% and a specificity of 79%. This marker could be a useful tool for clinicians to select patients who could benefit for bone targeted therapy in adjuvant setting.

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A servo-controlled automatic machine can perform tasks that involve synchronized actuation of a significant number of servo-axes, namely one degree-of-freedom (DoF) electromechanical actuators. Each servo-axis comprises a servo-motor, a mechanical transmission and an end-effector, and is responsible for generating the desired motion profile and providing the power required to achieve the overall task. The design of a such a machine must involve a detailed study from a mechatronic viewpoint, due to its electric and mechanical nature. The first objective of this thesis is the development of an overarching electromechanical model for a servo-axis. Every loss source is taken into account, be it mechanical or electrical. The mechanical transmission is modeled by means of a sequence of lumped-parameter blocks. The electric model of the motor and the inverter takes into account winding losses, iron losses and controller switching losses. No experimental characterizations are needed to implement the electric model, since the parameters are inferred from the data available in commercial catalogs. With the global model at disposal, a second objective of this work is to perform the optimization analysis, in particular, the selection of the motor-reducer unit. The optimal transmission ratios that minimize several objective functions are found. An optimization process is carried out and repeated for each candidate motor. Then, we present a novel method where the discrete set of available motor is extended to a continuous domain, by fitting manufacturer data. The problem becomes a two-dimensional nonlinear optimization subject to nonlinear constraints, and the solution gives the optimal choice for the motor-reducer system. The presented electromechanical model, along with the implementation of optimization algorithms, forms a complete and powerful simulation tool for servo-controlled automatic machines. The tool allows for determining a wide range of electric and mechanical parameters and the behavior of the system in different operating conditions.

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The prognostic value of ABC transporters in Ewing sarcoma is still poorly explored and controversial. We described for the first time the impact of various ABCs on Ewing sarcoma prognosis by assessment of their gene expression in two independent cohorts of patients. Unexpected associations with favourable outcomes were observed for two ABCs of the A-subfamily, ABCA6 and ABCA7, whereas no associations with the canonical multidrug ABC transporters were identified. The ABCs of the A-subfamily are involved in cholesterol/phospholipids transportation and efflux from cells. Our clinical data support the drug-efflux independent contribution to cancer progression of the ABCAs, which has been confirmed in PDX-derived cell lines. The impact of these ABCA transporters on tumor progression seems to be mediated by lowering intracellular cholesterol, supporting the role of these proteins in lipid transport. In addition, the gene expression of ABCA6 and ABCA7 is regulated by transcription factors which control lipid metabolism: ABCA6 was induced by the binding of FoxO1/FoxO3a to its promoter and repressed by IGF1R/Akt signaling, whereas the expression of ABCA7 was regulated by p53. The data point to ABCA6 and ABCA7 as potential prognostic markers in Ewing sarcoma and suggest the IGF1/ABCA/lipid axis as an intriguing therapeutic target. Agonist monoclonal antibodies towards ABCA6/7 or inhibitors of cholesterol biosynthesis, such as statins or aminobiphoshonates, may be investigated as therapeutic options in combination with chemotherapy. Considering that no monoclonal antibodies selectively targeting extracellular domains of ABCA6/7 are available, the second part of the project has been dedicated to the generation of human antibody phage-display libraries as tools for selecting monoclonal antibodies. A novel synthetic human antibody phage-display library has been designed, cloned and characterized. The library takes advantages of the high variability of a designed naïve repertoire to be a useful tool for isolating antibodies towards all potential antigens, including the ABCAs.

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Dairy industries are asked to be increasingly competitive and efficient. Despite the increasing trend in milk yield and protein content during the last decade genetic selection, milk coagulation ability has diminished and even if the absolute amount of cheese produced has increased, the relative cheese yield from a set amount of milk, has decreased. As casein content and variants, along with milk clotting properties (MCP) are determined to a large extent at DNA level, genetic selection and embryo transfer can provide efficacious tools to reverse this trend and achieve improvements. The aim of the proposed research was to determine how rapidly and to what extent milk coagulation properties could be improved by using embryo transfer (ET) as a tool to increase the frequency of k-casein BB genotype cattle and reducing A and E variants in an Italian Holstein herd with a low prevalence of the favourable genotype. In the effort to optimize superovulation protocols and results, synchronization of wave emergence was performed through manual transrectal ablation of the largest (dominant) ovarian follicle on days 7 or 8 of the cycle (estrus = day 0); different drugs and dosage for the superstimulation protocol were experimented trying to overcome the negative effects of stress and the perturbance of LH secretion in superovulated highly producing lactating cows and the use of SexedULTRA™ sex-sorted semen, for artificial insemination of superovulated cows was reported for the first time. The selection program carried out in this research, gave evidence and gathered empirical data of feasible genetic improvements in cheesemaking ability of milk by means of k-casein BB selection. In conclusion, in this project, selection of k-casein BB genotype markedly enhanced cheese-making properties of milk, providing an impetus to include milk coagulation traits in genetic selection and breeding programs for dairy cattle.