Abstract

SCRIB is a polarity regulator known to be abnormally expressed in cancer at the protein level. Here we report that, in breast cancer, an additional and hidden dimension of deregulations exists: an unexpected SCRIB exon usage pattern appears to mark a more malignant tumor phenotype and significantly correlates with survival. Conserved exons encoding the leucine-rich repeats tend to be overexpressed while others are underused. Mechanistic studies revealed that the underused exons encode part of the protein necessary for interaction with Vimentin and Numa1, a protein which is required for proper positioning of the mitotic spindle. Thus, the inclusion/exclusion of specific SCRIB exons is a mechanistic hallmark of breast cancer, which could potentially be exploited to develop more efficient diagnostics and therapies.

Abstract

The use of Twitter by newspapers is widespread and is a way to keep readers informed in real time. In this article, we analyze the discourse of the messages released by the ten main general information newspapers in Spain and the reactions they provoked on the social network. The objective is to analyze whether the emotional discourse of the news in each newspaper caused greater dissemination among and attention from users, as well as to determine the emotions and feelings expressed by them. To do so, news about important events such as court judgements, street riots, and general elections was followed between October and November 2019. A total of 124,897 tweets collected using machine-learning techniques were analyzed by the application of algorithms which allowed the determination of emotions and valences of feelings. We carried out statistical studies and produced graphs showing the dependence between emotional variables and positive or negative sentimental valence. The results showed that, in general, newspapers do not use an excessive amount of emotional speech with the aim of impacting their public. However, differences were found among the newspapers in terms of trying to encourage reader loyalty. The reaction of the users was more linked to the informative facts themselves and the emotions they provoked than to the type of emotional and/or polarized discourse. The day-to-day information determines to a large extent what is consumed by Twitter users, in which changing modes of speech are observed depending on the editorial line of each newspaper.

Abstract

Twitter is one of several social networks with the highest numbers of users in Spain. In spite of this, how are communicative relationships developed in the digital environment among influencers who have emerged on the Internet? These personalities have a stronger influence on children and young people than traditional celebrities. The aim of this work is to study the communicative interaction generated on the profiles of Spanish influencers with the most followers on Twitter, based on the number of content items generated and the responses they receive from users. The polarity and sentiment conveyed by these communications have also been analysed. By processing publications in real time using machine learning based on sentiment analysis, 48,878 tweets and retweets from five influencers were studied over a period of 40 days. The results show that the publications reached nearly 200 million followers, and despite being fourth in terms of the number of followers, @IbaiLlanos is the influencer who leads the conversations on Twitter with the highest number of tweets, retweets, and audience share. Among the most popular topics, sporting events stand out. This study has also confirmed that the most frequently stated emotion is surprise, and that positive messages prevail over those that are negative and neutral with regard to polarity. Nevertheless, the linear regression data has verified that the main trend is toward publishing negative messages, with a lower statistical correlation, which is a behaviour that might possibly be duplicated on other social networks.