Fake news and misinformation have been increasingly used to manipulate popular opinion and influence political processes. To better understand fake news, how they are propagated, and how to counter their effect, it is necessary to first identify them. Recently, approaches have been proposed to automatically classify articles as fake based on their content. An important challenge for these approaches comes from the dynamic nature of news: as new political events are covered, topics and discourse constantly change and thus, a classifier trained using content from articles published at a given time is likely to become ineffective in the future. To address this challenge, we propose a topic-agnostic (TAG) classification strategy that uses linguistic and web-markup features to identify fake news pages. We report experimental results using multiple data sets which show that our approach attains high accuracy in the identification of fake news, even as topics evolve over time.

Changes in microRNA (miRNA) expression may lead to cancer development and/or contribute to its progression; however, their role in uterine sarcomas is poorly understood. Uterine sarcomas (US) belong to a rare class of heterogeneous tumors, representing about 1% of all gynecologic neoplasms. This study aimed to assess the expression profile of 84 cancer-related miRNAs and to evaluate their correlation with clinical pathological features. Eighty-two formalin-fixed paraffin-embedded (FFPE) samples were selected. In leiomyosarcoma (LMS), there was an association of lower cancer-specific survival (CSS) with the downregulation of miR-125a-5p and miR-10a-5p, and the upregulation of miR-196a-5p and miR-34c-5p. In carcinosarcoma (CS), lower CSS was associated with the upregulation of miR-184, and the downregulation of let-7b-5p and miR-124. In endometrial stromal sarcomas (ESS), the upregulation of miR-373-3p, miR-372-3p, and let-7b-5p, and the down-expression of let-7f-5p, miR-23-3p, and let-7b-5p were associated with lower CSS. Only miR-138-5p upregulation was associated with higher survival rates. miR-335-5p, miR-301a-3p, and miR-210-3p were more highly expressed in patients with tumor metastasis and relapse. miR-138-5p, miR-146b-5p, and miR-218-5p expression were associated with higher disease-free survival (DFS) in treated patients. These miRNAs represent potential prediction markers for prognosis and treatment response in these tumors.

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