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Abstract The technological revolution and the widespread of social media have allowed people to generate tremendous amounts of data every day. Social networks provide users with access to information. This paper aims to determine the attractiveness of various tourism sites by investigating the behaviour of users through social media. The database involves geo-tagged photos located in six cities serving as a relevant artistic and cultural hub in Italy. Photos downloaded from Flickr, a data-sharing platform. Data analysis was conducted using Mathematica and Machine Learning models approach. The results of our study show maps of the users' behaviour identify the annual trend of photographic activity in cities and highlight the effectiveness of the proposed methodology that is able to provide with place and user information. The study underline how the analysis of social data can to create a predictive model to formulate tourism scenarios. At the end, general tourism marketing strategies are discussed. Highlights • A Big Data analysis model is proposed to identifying certain areas of interest and its cultural context. • Exploitation of social media allows you to identify the dynamics associated with a tourist site. • Understand the factors that drive people to photograph an item in a specific place. [ABSTRACT FROM AUTHOR]

The Industry 4.0 revolution is bringing major transformations in the tourism systems design suitable for technologically oriented consumers. Indeed, methods and technologies introduced by Big Data, Automation, Virtual and augmented reality, Robotics and ICT well fit with the Tourism 4.0 paradigm. However, tourism students are not yet trained on techniques, issues and methods related to the Industry 4.0 framework. Hence, relying on a careful examination of the literature on tourism market trends linked to the offer of innovative technological services, we identified conceptual, methodological, technological and practical skills to be developed in an academic curriculum for Tourism Science students. Learning path were focused on: i) processes of data acquisition from social media, ii) data analysis using Machine Learning techniques and iii) data design into significant elements useful to implement communication systems in the tourism field. showed that the most of participants achieved a medium-high evaluation for the implementation of the communication systems, applying appropriately techniques and tools learned along the course. Furthermore, the high percentage of students satisfaction registered in relation to the course, revealed that students enjoyed this experience. Outcomes reflects the acquisition and the awareness of those skills that will enable students to be conscious protagonists of their role in tourism 4.0. • A lab course on techniques, issues and methods related to the I4.0 framework has been provided to Tourism Science students. • The course allowed students to get conceptual and practical skills related to Machine Learning and Big Data Analytics. • Students applied Bigdata analytics techniques to analyse tourists' behaviour and their favourite locations. • Students developed a communication system, using the collected data and Design Thinking approach. • A questionnaire has then been administered to understand students' evaluation of the lab course. [ABSTRACT FROM AUTHOR]

Abstract: Loss of heterozygosity at the FHIT locus is coincident with activation of DNA damage response checkpoint proteins; thus damage at fragile loci may trigger checkpoint activation. We examined preneoplastic lesions adjacent to non-small cell lung carcinomas for alterations to expression of Fhit and activated checkpoint proteins. Expression scores were analyzed for pair-wise associations and correlations among proteins and type of lesion. Hyperplastic and dysplastic lesions were positive for nuclear γH2AX expression; 12/20 dysplastic lesions were negative for Fhit expression. Fhit positive lesions showed expression of most checkpoint proteins examined, while Fhit negative lesions showed absence of expression of Chk1 and phosphoChk1. The results show that loss of expression of Fhit is significantly directly correlated with absence of activated Chk1 in dysplasia, and suggest a connection between loss of Fhit and modulation of checkpoint activity. [Copyright &y& Elsevier]

Rescue of embryonic lethality in MDM4-/- mice through concomitant loss of p53 has revealed a functional partnership between the two proteins. Biochemical studies have suggested that MDM4 may act as a negative regulator of p53 levels and activity. On the other hand, MDM4 overexpression has been reported to stabilize p53 levels and to counteract MDM2-degradative activity. We have investigated the functional role of MDM4 overexpression on cell behavior. In both established and primary cells cultured under stress conditions, overexpression of MDM4 significantly increased p53-dependent cell death, in correlation with enhanced induction of the endogenous p53 protein levels. This phenomenon was associated with induced p53 transcriptional activity and increased levels of the proapoptotic protein, Bax. Further, p53 stabilization was accompanied by decreased association of the protein to its negative regulator, MDM2. These findings reveal a novel role for MDM4 by demonstrating that in non-tumor cells under stress conditions it may act as a positive regulator of p53 activity, mainly by controlling p53 levels. They also indicate a major distinction between the biological consequences of MDM4 and MDM2 overexpression. [ABSTRACT FROM AUTHOR]