Perceptions and satisfaction with dental healthcare: a case study

This paper presents the main results of a survey carried out by a  network of dental surgeries, with the aim of investigating patients' feelings about dental cures and their overall satisfaction with the supplied service. Information was collected by means of a questionnaire filled in by a sample of 885 patients. The most remarkable outcomes are relative to patient segmentation and patient satisfaction

Role revolution: towards a new meaning of positions in basketball

Most team sports are characterized by positions to which the players in a team are assigned. The goal of this classification is to attribute specific responsibilities during a game. Moreover, the same classification drives the buying and selling of players according to team managers and coaches strategies. The existing positions - often defined a long time ago - tend to reflect traditional points of view about the game and sometimes they are no longer well-suited to the new concepts arisen with the evolution of the way of playing.   This paper focuses on basketball and aims at describing new roles of players during the game, by means of the analysis of players' performance statistics with data mining and machine learning tools. In detail, self-organizing maps and fuzzy clustering procedures are adopted in tandem to define groups of players with similar way of playing. The results show that, when considering the modern basketball players' statistics, classical positions are not able to fully represent their way of playing, and a new set of 5 roles emerges as a meaningful classification of players' characteristics

A Conditional Value-at-Risk Based Portfolio Selection With Dynamic Tail Dependence Clustering

In this paper we propose a portfolio selection procedure specifically designed to protect investments during financial crisis periods. To this aim, we focus attention on the lower tails of the returns distributions and use a combination of statistical tools able to take into account the joint behavior of stocks in event of high losses. In detail, we propose to firstly cluster time series of stock returns on the basis of their lower tail dependence coefficients, estimated with copula functions, and secondly to use the obtained clustering solution to build an optimal minimum CVaR portfolio. In addition, the procedure is defined in a time-varying context, in order to model the possible contagion between stocks when volatility increases. This results in a dynamic portfolio selection procedure, which is shown to be able to outperform classical strategies

A Conditional Value-at-Risk Based Portfolio Selection With Dynamic Tail Dependence Clustering

In this paper we propose a portfolio selection procedure specifically designed to protect investments during financial crisis periods. To this aim, we focus attention on the lower tails of the returns distributions and use a combination of statistical tools able to take into account the joint behavior of stocks in event of high losses. In detail, we propose to firstly cluster time series of stock returns on the basis of their lower tail dependence coefficients, estimated with copula functions, and secondly to use the obtained clustering solution to build an optimal minimum CVaR portfolio. In addition, the procedure is defined in a time-varying context, in order to model the possible contagion between stocks when volatility increases. This results in a dynamic portfolio selection procedure, which is shown to be able to outperform classical strategies

Role revolution: towards a new meaning of positions in basketball

Most team sports are characterized by positions to which the players in a team are assigned. The goal of this classification is to attribute specific responsibilities during a game. Moreover, the same classification drives the buying and selling of players according to team managers and coaches strategies. The existing positions - often defined a long time ago - tend to reflect traditional points of view about the game and sometimes they are no longer well-suited to the new concepts arisen with the evolution of the way of playing.   This paper focuses on basketball and aims at describing new roles of players during the game, by means of the analysis of players' performance statistics with data mining and machine learning tools. In detail, self-organizing maps and fuzzy clustering procedures are adopted in tandem to define groups of players with similar way of playing. The results show that, when considering the modern basketball players' statistics, classical positions are not able to fully represent their way of playing, and a new set of 5 roles emerges as a meaningful classification of players' characteristics

Drug conjugation to hyaluronan widens therapeutic indications for ovarian cancer

Management of ovarian cancer still requires improvements in therapeutic options. A drug delivery strategy was tested that allows specific targeting of tumor cells in combination with a controlled release of a cytotoxic molecule. To this aim, the efficacy of a loco-regional intraperitoneal treatment with a bioconjugate (ONCOFID-S) derived by chemical linking of SN-38, the active metabolite of irinotecan (CPT-11), to hyaluronan was assessed in a mouse model of ovarian carcinomatosis. In vitro, the bioconjugate selectively interacted with ovarian cancer cells through the CD44 receptor, disclosed a dose-dependent tumor growth inhibition efficacy comparable to that of free SN-38 drug, and inhibited Topoisomerase I function leading to apoptosis by a mechanism involving caspase-3 and -7 activation and PARP cleavage. In vivo, the intraperitoneal administration of ONCOFID-S in tumor-bearing mice did not induce inflammation, and evidenced an improved therapeutic efficacy compared with CPT-11. In conclusion, SN-38 conjugation to hyaluronan significantly improved the profile of in vivo tolerability and widened the field of application of irinotecan. Therefore, this approach can be envisaged as a promising therapeutic strategy for loco-regional treatment of ovarian cancer

Dissecting the effect of soil on plant phenology and berry transcriptional plasticity in two Italian grapevine varieties (Vitis vinifera L.)

Grapevine embodies a fascinating species as regards phenotypic plasticity and genotype-per-environment interactions. The terroir, namely the set of agri-environmental factors to which a variety is subjected, can influence the phenotype at the physiological, molecular, and biochemical level, representing an important phenomenon connected to the typicality of productions. We investigated the determinants of plasticity by conducting a field-experiment where all terroir variables, except soil, were kept as constant as possible. We isolated the effect of soils collected from different areas, on phenology, physiology, and transcriptional responses of skin and flesh of a red and a white variety of great economic value: Corvina and Glera. Molecular results, together with physio-phenological parameters, suggest a specific effect of soil on grapevine plastic response, highlighting a higher transcriptional plasticity of Glera in respect to Corvina and a marked response of skin compared to flesh. Using a novel statistical approach, we identified clusters of plastic genes subjected to the specific influence of soil. These findings could represent an issue of applicative value, posing the basis for targeted agricultural practices to enhance the desired characteristics for any soil/cultivar combination, to improve vineyards management for a better resource usage and to valorize vineyards uniqueness maximizing the terroir-effect

Towards the definition of a detailed transcriptomic map of berry development

The progress of the grapevine genomics and the development of high-throughput technologies for gene expression analysis stimulated the investigation of the physical, biochemical and physiological changes of grape berry growth and maturation at transcriptomic level. The molecular information generated in the last decade is however still fragmented since it relies upon detailed analysis of few stages and thus lacks continuity over grape development. To identify the molecular events associated with berry development at a higher temporal resolution and define a transcriptomic map, we performed RNA-seq analysis of berry samples collected every week from fruit-set to maturity in Pinot noir and Cabernet Sauvignon for three consecutive years, resulting in 219 samples. Using the most variable portion of the transcriptome, we built a preliminary transcriptomic model of berry development based on the Cabernet Sauvignon samples. The Pinot noir samples were then aligned onto this preliminary ripening map to investigate its performance in describing the development of another grape variety. A further step for testing the model was the projection of RNA-seq samples of fruit development of five red-skin Italian cultivars. For all these surveys, the transcriptomic route allowed a precise definition of the progression of berry development during both formation and ripening phases