Knotify_V2.0: Deciphering RNA Secondary Structures with H-Type Pseudoknots and Hairpin Loops.

Accurately predicting the pairing order of bases in RNA molecules is essential for anticipating RNA secondary structures. Consequently, this task holds significant importance in unveiling previously unknown biological processes. The urgent need to comprehend RNA structures has been accentuated by the unprecedented impact of the widespread COVID-19 pandemic.

Selenium, Selenoproteins and 10-year Cardiovascular Risk: Results from the ATTICA Study.

Background: Selenium (Se) is an essential trace element that is involved in several pathophysiological functions. The relationship of Se with cardiovascular disease remains inconclusive, especially regarding the role of different selenospecies.

Objective: The present study assessed the levels of Se distribution in plasma selenoproteins, namely glutathione peroxidase 3 (GPx3), selenoprotein P (SelP) and selenoalbumin (SeAlb) and total Se in selenoproteins in relation to 10-year cardiovascular risk in the ATTICA prospective study.

Citizen Science to improve healthy and active living among adolescents in four European countries: a protocol of the cluster randomised controlled trial of the Science Engagement to Empower aDolescentS (SEEDS) project.

Introduction: Improving healthy lifestyles of adolescents is challenging. Citizen Science is a way to engage them in the design and delivery of interventions, and may also increase their interest in science, technology, engineering and mathematics (STEM). The Science Engagement to Empower aDolescentS (SEEDS) project aims to use an equity-lens, and engage and empower boys and girls from deprived areas by designing and cocreating interventions to promote healthy lifestyles, and to seed interest in STEM.

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures.