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Expert Systems with Applications ; : 118063, 2022.
Article in English | ScienceDirect | ID: covidwho-1926438


Social networks have taken an irreplaceable role in our lives. They are used daily by millions of people to communicate and inform themselves. This success has also led to a lot of irrelevant content and even misinformation on social media. In this paper, we propose a user-centred framework to reduce the amount of irrelevant content in social networks to support further stages of data mining processes. The system also helps in the reduction of misinformation in social networks, since it selects credible and reputable users. The system is based on the belief that if a user is credible then their content will be credible. Our proposal uses word embeddings in a first stage, to create a set of interesting users according to their expertise. After that, in a later stage, it employs social network metrics to further narrow down the relevant users according to their credibility in the network. To validate the framework, it has been tested with two real Big Data problems on Twitter. One related to COVID-19 tweets and the other to last United States elections on 3rd November. Both are problems in which finding relevant content may be difficult due to the large amount of data published during the last years. The proposed framework, called NOFACE, reduces the number of irrelevant users posting about the topic, taking only those that have a higher credibility, and thus giving interesting information about the selected topic. This entails a reduction of irrelevant information, mitigating therefore the presence of misinformation on a posterior data mining method application, improving the obtained results, as it is illustrated in the mentioned two topics using clustering, association rules and LDA techniques.

Toxics ; 8(3)2020 Jun 28.
Article in English | MEDLINE | ID: covidwho-1224244


Recently, there has been an outbreak associated with the use of e-cigarette or vaping products, associated lung injury (EVALI). The primary components of vaping products, vitamin E acetate (VEA) and medium-chain triglycerides (MCT), may be responsible for acute lung toxicity. Currently, little information is available on the physiological and biological effects of exposure to these products. We hypothesized that these e-cig vape cartridges and their constituents (VEA and MCT) induce pulmonary toxicity, mediated by oxidative damage and inflammatory responses, leading to acute lung injury. We studied the potential mechanisms of e-cig vape cartridge aerosol induced inflammatory response by evaluating the generation of reactive oxygen species by MCT, VEA, and cartridges and their effects on the inflammatory state of pulmonary epithelium and immune cells both in vitro and in vivo. Cells exposed to these aerosols generated reactive oxygen species, caused cytotoxicity, induced epithelial barrier dysfunction, and elicited an inflammatory response. Using a murine model, the parameters of acute toxicity to aerosol inhalation were assessed. Infiltration of neutrophils and lymphocytes was accompanied by significant increases in IL-6, eotaxin, and G-CSF in the bronchoalveolar lavage fluid (BALF). In mouse plasma, eicosanoid inflammatory mediators, leukotrienes, were significantly increased. Plasma from e-cig users also showed increased levels of hydroxyeicosatetraenoic acid (HETEs) and various eicosanoids. Exposure to e-cig vape cartridge aerosols showed the most significant effects and toxicity compared to MCT and VEA. In addition, we determined SARS-CoV-2 related proteins and found no impact associated with aerosol exposures from these tested cartridges. Overall, this study demonstrates acute exposure to specific e-cig vape cartridges induces in vitro cytotoxicity, barrier dysfunction, and inflammation and in vivo mouse exposure induces acute inflammation with elevated proinflammatory markers in the pathogenesis of EVALI.