METTL14 is required for exercise-induced cardiac hypertrophy and protects against myocardial ischemia-reperfusion injury
Lijun Wang,Jiaqi Wang,Pujiao Yu,Jingyi Feng,Gui-e Xu,Xuan Zhao,Tianhui Wang,H. Immo Lehmann,Guoping Li,Joost P.G. Sluijter,Junjie Xiao +10 more
TL;DR: In this article , the role of RNA m 6 A in exercise training and exercise-induced physiological cardiac hypertrophy remains largely unknown, but it is known that METTL14 is downregulated by exercise.
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Abstract: Abstract RNA m 6 A modification is the most widely distributed RNA methylation and is closely related to various pathophysiological processes. Although the benefit of regular exercise on the heart has been well recognized, the role of RNA m 6 A in exercise training and exercise-induced physiological cardiac hypertrophy remains largely unknown. Here, we show that endurance exercise training leads to reduced cardiac mRNA m 6 A levels. METTL14 is downregulated by exercise, both at the level of RNA m 6 A and at the protein level. In vivo, wild-type METTL14 overexpression, but not MTase inactive mutant METTL14, blocks exercise-induced physiological cardiac hypertrophy. Cardiac-specific METTL14 knockdown attenuates acute ischemia-reperfusion injury as well as cardiac dysfunction in ischemia-reperfusion remodeling. Mechanistically, silencing METTL14 suppresses Phlpp2 mRNA m 6 A modifications and activates Akt-S473, in turn regulating cardiomyocyte growth and apoptosis. Our data indicates that METTL14 plays an important role in maintaining cardiac homeostasis. METTL14 downregulation represents a promising therapeutic strategy to attenuate cardiac remodeling.
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Acute Myocardial Infarction: Molecular Pathogenesis, Diagnosis, and Clinical Management
TL;DR: This review systematically explores the molecular pathogenesis, diagnosis, and clinical management of acute myocardial infarction, integrating mechanistic insights with interdisciplinary clinical strategies to establish a precision-based framework for prevention and management.
References
HISAT: a fast spliced aligner with low memory requirements
TL;DR: Tests showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method, and requires only 4.3 gigabytes of memory.
2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC.
Piotr Ponikowski,Adriaan A. Voors,Stefan D. Anker,Héctor Bueno,John G.F. Cleland,Andrew J.S. Coats,Volkmar Falk,José Ramón González-Juanatey,Veli-Pekka Harjola,Ewa A. Jankowska,Mariell Jessup,Cecilia Linde,Petros Nihoyannopoulos,John Parissis,Burkert Pieske,Jillian P. Riley,Giuseppe M.C. Rosano,Luis M. Ruilope,Frank Ruschitzka,Frans H. Rutten,Peter van der Meer,Gerasimos Filippatos,John J.V. McMurray,Victor Aboyans,Stephan Achenbach,Stefan Agewall,Nawwar Al-Attar,John Atherton,Johann Bauersachs,A. John Camm,Scipione Carerj,Claudio Ceconi,Antonio Coca,Perry M. Elliott,Çetin Erol,Justin A. Ezekowitz,Covadonga Fernández-Golfín,Donna Fitzsimons,Marco Guazzi,Maxime Guenoun,Gerd Hasenfuss,Gerhard Hindricks,Arno W. Hoes,Bernard Iung,Tiny Jaarsma,Paulus Kirchhof,Juhani Knuuti,Philippe Kolh,Stavros Konstantinides,Mitja Lainscak,Patrizio Lancellotti,Gregory Y.H. Lip,Francesco Maisano,Christian Mueller,Mark C. Petrie,Massimo F Piepoli,Silvia G. Priori,Adam Torbicki,Hiroyuki Tsutsui,Dirk J. van Veldhuisen,Stephan Windecker,Clyde W. Yancy,José Luis Zamorano +62 more
TL;DR: Authors/Task Force Members: Piotr Ponikowski* (Chairperson) (Poland), Adriaan A. Voors* (Co-Chair person) (The Netherlands), Stefan D. Anker (Germany), Héctor Bueno (Spain), John G. F. Cleland (UK), Andrew J. S. Coats (UK)
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Differential expression analysis for sequence count data.
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TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.
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