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1.
  • Gomes, CPC, et al. (author)
  • Catalyzing Transcriptomics Research in Cardiovascular Disease: The CardioRNA COST Action CA17129
  • 2019
  • In: Non-coding RNA. - : MDPI AG. - 2311-553X. ; 5:2
  • Journal article (peer-reviewed)abstract
    • Cardiovascular disease (CVD) remains the leading cause of death worldwide and, despite continuous advances, better diagnostic and prognostic tools, as well as therapy, are needed. The human transcriptome, which is the set of all RNA produced in a cell, is much more complex than previously thought and the lack of dialogue between researchers and industrials and consensus on guidelines to generate data make it harder to compare and reproduce results. This European Cooperation in Science and Technology (COST) Action aims to accelerate the understanding of transcriptomics in CVD and further the translation of experimental data into usable applications to improve personalized medicine in this field by creating an interdisciplinary network. It aims to provide opportunities for collaboration between stakeholders from complementary backgrounds, allowing the functions of different RNAs and their interactions to be more rapidly deciphered in the cardiovascular context for translation into the clinic, thus fostering personalized medicine and meeting a current public health challenge. Thus, this Action will advance studies on cardiovascular transcriptomics, generate innovative projects, and consolidate the leadership of European research groups in the field.COST (European Cooperation in Science and Technology) is a funding organization for research and innovation networks (www.cost.eu).
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2.
  • Mishra, Kankadeb, 1981, et al. (author)
  • Understanding Long Noncoding RNA and Chromatin Interactions: What We Know So Far
  • 2019
  • In: Non-Coding Rna. - : MDPI AG. - 2311-553X. ; 5:4
  • Journal article (peer-reviewed)abstract
    • With the evolution of technologies that deal with global detection of RNAs to probing of lncRNA-chromatin interactions and lncRNA-chromatin structure regulation, we have been updated with a comprehensive repertoire of chromatin interacting lncRNAs, their genome-wide chromatin binding regions and mode of action. Evidence from these new technologies emphasize that chromatin targeting of lncRNAs is a prominent mechanism and that these chromatin targeted lncRNAs exert their functionality by fine tuning chromatin architecture resulting in an altered transcriptional readout. Currently, there are no unifying principles that define chromatin association of lncRNAs, however, evidence from a few chromatin-associated lncRNAs show presence of a short common sequence for chromatin targeting. In this article, we review how technological advancements contributed in characterizing chromatin associated lncRNAs, and discuss the potential mechanisms by which chromatin associated lncRNAs execute their functions.
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3.
  • Salgado-Somoza, Antonio, et al. (author)
  • Non-coding RNAs to aid in neurological prognosis after cardiac arrest
  • 2018
  • In: Non-coding RNA. - : MDPI AG. - 2311-553X. ; 4:4
  • Research review (peer-reviewed)abstract
    • Cardiovascular disease in general, and sudden cardiac death in particular, have an enormous socio-economic burden worldwide. Despite significant efforts to improve cardiopulmonary resuscitation, survival rates remain low. Moreover, patients who survive to hospital discharge have a high risk of developing severe physical or neurological symptoms. Being able to predict outcomes after resuscitation from cardiac arrest would make it possible to tailor healthcare approaches, thereby maximising efforts for those who would mostly benefit from aggressive therapy. However, the identification of patients at risk of poor recovery after cardiac arrest is still a challenging task which could be facilitated by novel biomarkers. Recent investigations have recognised the potential of non-coding RNAs to aid in outcome prediction after cardiac arrest. In this review, we summarize recent discoveries and propose a handful of novel perspectives for the use of non-coding RNAs to predict outcome after cardiac arrest, discussing their use for precision medicine.
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