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The need to deal with the inherent uncertainty in real-world relational or networked data leads to the proposal of new probabilistic models, such as probabilistic graphs. Every edge in a probabilistic graph is associated with a probability whose value represents the likelihood of its existence, or the strength of the relation between the entities it connects. The aim of this paper is to propose two machine learning techniques for the link classification problem in relational data exploiting the probabilistic graph representation. Both the proposed methods will exploit a language-constrained reachability method to infer the probability of possible hidden relationships that may exists between two nodes in a probabilistic graph. Each hidden relationships between two nodes may be viewed as a feature (or a factor), and its corresponding probability as its weight, while an observed relationship is considered as a positive instance for its corresponding link label. Given a training set of observed links, the first learning approach is to use a propositionalization technique adopting a L2-regularized Logistic Regression to learn a model able to predict unobserved link labels. Since in some cases the edges’ probability may be not known in advance or they could not be precisely defined for a classification task, the second xposed approach is to exploit the inference method and to use a mean squared technique to learn the edges’ probabilities. Both the proposed methods have been evaluated on real world data sets and the corresponding results proved their validity.

Background The present study reports the results of a survey jointly carried out by three Italian respiratory scientific associations (AIMAR, AIPO, SIMeR) together with an important Federation of elderly patients (FederAnziani) during the National Conference of Italian Court for Health Right held in Rimini from November 29 th to December 1 st , 2013. The survey, based on a spirometric examination preceded by a questionnaire on respiratory health, was conducted on elderly people coming from all Italian regions to attend the Conference. Methods Nine hundred forty-nine subjects (574 females and 375 males), mean age 66.2 ± 10.1 years, were interviewed and performed spirometric examination. There were 137 smokers (14.4 %). Mean value of Body Mass Index (BMI) was significantly higher in males (27.6 ± 6.6) than in females (26.3 ± 4.3). Results 17.1 % ( N  = 143) of the studied subjects reported to be suffering from respiratory disease and the prevalent illnesses were asthma (31.5 %) and COPD/emphysema (24.5 %), but only 3.3 % of the whole surveyed group was able to identify COPD as a pulmonary disease, however without knowing its characteristics, while these were known by 0.5 % of the interviewed subjects only. A high number of subjects, 22 % of whom were smokers, declared chronic sputum production. 10.2 % of the study group showed an obstructive defect at spirometry when the criterium of lower limit of the normal (LLN) was considered, whereas it was 12.4 % if the fixed limit of 0.70 was chosen. 64 % of the obstructed people thought they did not have any respiratory disease. Conclusions The results of this survey, able to spread the knowledge of respiratory diseases and spirometry in a wide sample of subjects for the most part scarcely aware of them, emphasize the need for a greater divulgation of respiratory issues among the general population.

Background: The present study reports the results of a survey jointly carried out by three Italian respiratory scientific associations (AIMAR, AIPO, SIMeR) together with an important Federation of elderly patients (FederAnziani) during the National Conference of Italian Court for Health Right held in Rimini from November 29th to December 1st, 2013. The survey, based on a spirometric examination preceded by a questionnaire on respiratory health, was conducted on elderly people coming from all Italian regions to attend the Conference. Methods: Nine hundred forty-nine subjects (574 females and 375 males), mean age 66.2 ± 10.1 years, were interviewed and performed spirometric examination. There were 137 smokers (14.4 %). Mean value of Body Mass Index (BMI) was significantly higher in males (27.6 ± 6.6) than in females (26.3 ± 4.3). Results: 17.1 % (N = 143) of the studied subjects reported to be suffering from respiratory disease and the prevalent illnesses were asthma (31.5 %) and COPD/emphysema (24.5 %), but only 3.3 % of the whole surveyed group was able to identify COPD as a pulmonary disease, however without knowing its characteristics, while these were known by 0.5 % of the interviewed subjects only. A high number of subjects, 22 % of whom were smokers, declared chronic sputum production. 10.2 % of the study group showed an obstructive defect at spirometry when the criterium of lower limit of the normal (LLN) was considered, whereas it was 12.4 % if the fixed limit of 0.70 was chosen. 64 % of the obstructed people thought they did not have any respiratory disease. Conclusions: The results of this survey, able to spread the knowledge of respiratory diseases and spirometry in a wide sample of subjects for the most part scarcely aware of them, emphasize the need for a greater divulgation of respiratory issues among the general population.

Background Non-communicable diseases (NCDs) kill 40 million people each year. The management of chronic respiratory NCDs such as chronic obstructive pulmonary disease (COPD) is particularly critical in Italy, where they are widespread and represent a heavy burden on healthcare resources. It is thus important to redefine the role and responsibility of respiratory specialists and their scientific societies, together with that of the whole healthcare system, in order to create a sustainable management of COPD, which could become a model for other chronic respiratory conditions. Methods These issues were divided into four main topics (Training, Organization, Responsibilities, and Sustainability) and discussed at a Consensus Conference promoted by the Research Center of the Italian Respiratory Society held in Rome, Italy, 3–4 November 2016. Results and conclusions Regarding training, important inadequacies emerged regarding specialist training - both the duration of practical training courses and teaching about chronic diseases like COPD. A better integration between university and teaching hospitals would improve the quality of specialization. A better organizational integration between hospital and specialists/general practitioners (GPs) in the local community is essential to improve the diagnostic and therapeutic pathways for chronic respiratory patients. Improving the care pathways is the joint responsibility of respiratory specialists, GPs, patients and their caregivers, and the healthcare system. The sustainability of the entire system depends on a better organization of the diagnostic-therapeutic pathways, in which also other stakeholders such as pharmacists and pharmaceutical companies can play an important role.

Non-communicable diseases (NCDs) kill 40 million people each year. The management of chronic respiratory NCDs such as chronic obstructive pulmonary disease (COPD) is particularly critical in Italy, where they are widespread and represent a heavy burden on healthcare resources. It is thus important to redefine the role and responsibility of respiratory specialists and their scientific societies, together with that of the whole healthcare system, in order to create a sustainable management of COPD, which could become a model for other chronic respiratory conditions. These issues were divided into four main topics (Training, Organization, Responsibilities, and Sustainability) and discussed at a Consensus Conference promoted by the Research Center of the Italian Respiratory Society held in Rome, Italy, 3-4 November 2016. Regarding training, important inadequacies emerged regarding specialist training - both the duration of practical training courses and teaching about chronic diseases like COPD. A better integration between university and teaching hospitals would improve the quality of specialization. A better organizational integration between hospital and specialists/general practitioners (GPs) in the local community is essential to improve the diagnostic and therapeutic pathways for chronic respiratory patients. Improving the care pathways is the joint responsibility of respiratory specialists, GPs, patients and their caregivers, and the healthcare system. The sustainability of the entire system depends on a better organization of the diagnostic-therapeutic pathways, in which also other stakeholders such as pharmacists and pharmaceutical companies can play an important role.

The probabilistic graphs framework models the uncertainty inherent in real-world domains by means of probabilistic edges whose value quantifies the likelihood of the edge existence or the strength of the link it represents. The goal of this paper is to provide a learning method to compute the most likely relationship between two nodes in a framework based on probabilistic graphs. In particular, given a probabilistic graph we adopted the language-constraint reachability method to compute the probability of possible interconnections that may exists between two nodes. Each of these connections may be viewed as feature, or a factor, between the two nodes and the corresponding probability as its weight. Each observed link is considered as a positive instance for its corresponding link label. Given the training set of observed links a L2-regularized Logistic Regression has been adopted to learn a model able to predict unobserved link labels. The experiments on a real world collaborative filtering problem proved that the proposed approach achieves better results than that obtained adopting classical methods.

Core Ideas Genotyping‐by‐sequencing analysis in cultivated chickpea generated 3187 high‐quality single nucleotide polymorphisms. Analysis of genetic diversity supports the identification of three subpopulations. Accessions traditionally grown in Italy form a clearly distinct genetic cluster. We identified genomic regions putatively resulting from directional selection. Our findings are of interest for chickpea conservation genetics and breeding. The accurate description of plant biodiversity is of utmost importance to efficiently address efforts in conservation genetics and breeding. Herein, we report the successful application of a genotyping‐by‐sequencing (GBS) approach in chickpea (Cicer arietinum L.), resulting in the characterization of a cultivated germplasm collection with 3187 high‐quality single nucleotide polymorphism (SNP) markers. Genetic structure inference, principal component analysis, and hierarchical clustering all indicated the identification of a genetic cluster corresponding to black‐seeded genotypes traditionally cultivated in Southern Italy. Remarkably, this cluster was clearly distinct at both genetic and phenotypic levels from germplasm groups reflecting commercial chickpea classification into desi and kabuli seed types. Fixation index estimates for individual polymorphisms pointed out loci and genomic regions that might be of significance for the diversification of agronomic and commercial traits. Overall, our findings provide information on genetic relationships within cultivated chickpea and highlight a gene pool of great interest for the scientific community and chickpea breeding, which is limited by the low genetic diversity available in the primary gene pool.

Background Obstructive sleep apnea is a common disorder characterized by multiple pathogenetic roots. Continuous positive airway pressure (CPAP) is almost always prescribed as the first-line treatment to all patients regardless of the heterogeneous pathophysiology, because it mechanically splints the airways open and reduces the collapsibility of the upper airway. Despite its high efficacy, CPAP is burdened by poor adherence and compliance rates. In this pilot study, we treated OSA patients with composite approaches different than CPAP, tailoring the therapeutic choice on OSA phenotypic traits. Methods We used the CPAP dial down technique to assess phenotypic traits in eight OSA patients with BMI<35. According to these traits, patients received personalized therapies for 2-week period, after which we ran a second polygraphy to compare apnea-hypopnea index (AHI) before and after therapy. Results Two weeks of combined behavioral and pharmacological therapy induced a significant reduction in mean AHI, which dropped from 26 ± 15 at baseline to 9 ± 7 post-treatment ( p  = 0.01). Furthermore, there was a significant reduction in mean ODI ( p  = 0.03) and subjective sleepiness ( p  = 0.01) documented by Epworth Sleepiness Scale (ESS) from baseline to post-treatment recordings. Conclusions Treating OSA patients with a personalized combination of pharmacological and behavioral therapies according to phenotypic traits leads to a significant improvement in AHI, ODI, and subjective sleepiness.

Extra virgin olive oil (EVOO) has elevated commercial value due to its health appeal, desirable characteristics and quantitatively limited production, and thus it has become an object of intentional adulteration. As EVOOs on the market might consist of a blend of olive varieties or sometimes even of a mixture of oils from different botanical species, an array of DNA-fingerprinting methods have been developed to check the varietal composition of the blend. Starting from a comparison between publicly available DNA extraction protocols, we set up a timely, low-cost, reproducible and effective DNA isolation protocol, which allows an adequate amount of DNA to be recovered even from commercial filtered EVOOs. Then, in order to verify the effectiveness of the DNA extraction protocol herein proposed, we applied PCR-based fingerprinting methods starting from the DNA extracted from three EVOO samples of unknown composition. In particular, genomic regions harboring nine simple sequence repeats (SSRs) and eight genotyping-by-sequencing-derived single nucleotide polymorphism (SNP) markers were amplified for authentication and traceability of the three EVOO samples. The whole investigation strategy herein described might favor producers in terms of higher revenues and consumers in terms of price transparency and food safety.