Most aspects of RNA metabolism involve DEAD-box RNA helicases, enzymes that bind and remodel RNA and RNA-protein complexes in an ATP-dependent manner. Here we show that the DEAD-box helicase Ded1p oligomerizes in the cell and in vitro, and unwinds RNA as a trimer. Two protomers bind the single-stranded region of RNA substrates and load a third protomer to the duplex, which then separates the strands. ATP utilization differs between the strand-separating protomer and those bound to the single-stranded region. Binding of the eukaryotic initiation factor 4G to Ded1p interferes with oligomerization and thereby modulates unwinding activity and RNA affinity of the helicase. Our data reveal a strict division of labor between the Ded1p protomers in the oligomer. This mode of oligomerization fundamentally differs from other helicases. Oligomerization represents a previously unappreciated level of regulation for DEAD-box helicase activities.
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http://dx.doi.org/10.1016/j.molcel.2015.06.030 | DOI Listing |
Quant Plant Biol
September 2024
Department of Life Sciences, Imperial College London, London, UK.
In this work, we present a quantitative comparison of the cell division dynamics between populations of intact and regenerating root tips in the plant model system To achieve the required temporal resolution and to sustain it for the duration of the regeneration process, we adopted a live imaging system based on light-sheet fluorescence microscopy, previously developed in the laboratory. We offer a straightforward quantitative analysis of the temporal and spatial patterns of cell division events showing a statistically significant difference in the frequency of mitotic events and spatial separation of mitotic event clusters between intact and regenerating roots.
View Article and Find Full Text PDFGlob Ment Health (Camb)
December 2024
Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
Background: There is a high prevalence of depression among refugee youth in low- and middle-income countries, yet depression trajectories are understudied. This study examined depression trajectories, and factors associated with trajectories, among urban refugee youth in Kampala, Uganda.
Methods: We conducted a longitudinal cohort study with refugee youth aged 16-24 in Kampala, Uganda.
Front Immunol
December 2024
Department of Medicine, Division of Hematology, Oncology and Transplantation, University of Minnesota, Minneapolis, MN, United States.
Sickle cell disease (SCD) is a devastating hemolytic disease, marked by recurring bouts of painful vaso-occlusion, leading to tissue damage from ischemia/reperfusion pathophysiology. Central to this process are oxidative stress, endothelial cell activation, inflammation, and vascular dysfunction. The endothelium exhibits a pro-inflammatory, pro-coagulant, and enhanced permeability phenotype.
View Article and Find Full Text PDFJ Gen Fam Med
January 2025
Background: Deprescribing is a critical component of clinical practice, especially in geriatric medicine. Nevertheless, the attributes of patients who are prepared for, interested in, and could potentially benefit from deprescribing have not been well examined. The Patient Perceptions of Deprescribing (PPoD) evaluates patients' overall readiness for deprescribing and is complemented by an 11-item validated short form (SF-PPoD).
View Article and Find Full Text PDFEur Heart J Imaging Methods Pract
October 2024
Cardiologia 1-Emodinamica, Dipartimento Cardiotoracovascolare 'A. De Gasperis', ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy.
Artificial intelligence (AI) is transforming cardiovascular imaging by offering advancements across multiple modalities, including echocardiography, cardiac computed tomography (CCT), cardiovascular magnetic resonance (CMR), interventional cardiology, nuclear medicine, and electrophysiology. This review explores the clinical applications of AI within each of these areas, highlighting its ability to improve patient selection, reduce image acquisition time, enhance image optimization, facilitate the integration of data from different imaging modality and clinical sources, improve diagnosis and risk stratification. Moreover, we illustrate both the advantages and the limitations of AI across these modalities, acknowledging that while AI can significantly aid in diagnosis, risk stratification, and workflow efficiency, it cannot replace the expertise of cardiologists.
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