Evolution of screen use among youth between 2012 and 2020 in Switzerland.

To compare the evolution of screen and Internet use by youths between 2012 and 2020 in Switzerland. Cross-sectional studies of 10th-graders (age 13-14) were performed in Switzerland in 2012 and 2020, and compared in bivariate and multivariate analyses on sociodemographic, schooling, physical activity, emotional well-being, and screen use variables. We found that screen use had shifted to smartphones with 71.7 % of youths primarily using this device in 2020 compared to 23.2 % in 2012. In association with this change, young people's screen time had increased dramatically with an odds ratio (OR) of 11.90 for adolescents spending more than 4 h in front of screens in 2020 compared to 2012. No changes were found in the score on the Internet Addiction Test (IAT) to detect problematic screen use and for adolescents' emotional well-being. Furthermore, youths in 2020 engaged in less physical activity lasting 60 min daily, but the frequency of their extracurricular sport participation remained unchanged. Young people spend more time on screens, especially because of an increase in smartphone use in 2020. However, youths do not seem to show more problematic behaviors regarding screen use, nor has this development affected their emotional well-being. The daily and continuous use of new devices is now an integral part of young people's lives. This process seems to be part of the growth of the digital world. However, Internet and screen addiction scales should be adapted to ensure that adolescents in need of help and counseling are identified

Dynamic changes in eIF4F-mRNA interactions revealed by global analyses of environmental stress responses

BACKGROUND: Translation factors eIF4E and eIF4G form eIF4F, which interacts with the messenger RNA (mRNA) 5' cap to promote ribosome recruitment and translation initiation. Variations in the association of eIF4F with individual mRNAs likely contribute to differences in translation initiation frequencies between mRNAs. As translation initiation is globally reprogrammed by environmental stresses, we were interested in determining whether eIF4F interactions with individual mRNAs are reprogrammed and how this may contribute to global environmental stress responses. RESULTS: Using a tagged-factor protein capture and RNA-sequencing (RNA-seq) approach, we have assessed how mRNA associations with eIF4E, eIF4G1 and eIF4G2 change globally in response to three defined stresses that each cause a rapid attenuation of protein synthesis: oxidative stress induced by hydrogen peroxide and nutrient stresses caused by amino acid or glucose withdrawal. We find that acute stress leads to dynamic and unexpected changes in eIF4F-mRNA interactions that are shared among each factor and across the stresses imposed. eIF4F-mRNA interactions stabilised by stress are predominantly associated with translational repression, while more actively initiating mRNAs become relatively depleted for eIF4F. Simultaneously, other mRNAs are insulated from these stress-induced changes in eIF4F association. CONCLUSION: Dynamic eIF4F-mRNA interaction changes are part of a coordinated early translational control response shared across environmental stresses. Our data are compatible with a model where multiple mRNA closed-loop complexes form with differing stability. Hence, unexpectedly, in the absence of other stabilising factors, rapid translation initiation on mRNAs correlates with less stable eIF4F interactions

Transimulation - protein biosynthesis web service

Although translation is the key step during gene expression, it remains poorly characterized at the level of individual genes. For this reason, we developed Transimulation - a web service measuring translational activity of genes in three model organisms: Escherichia coli, Saccharomyces cerevisiae and Homo sapiens. The calculations are based on our previous computational model of translation and experimental data sets. Transimulation quantifies mean translation initiation and elongation time (expressed in SI units), and the number of proteins produced per transcript. It also approximates the number of ribosomes that typically occupy a transcript during translation, and simulates their propagation. The simulation of ribosomes' movement is interactive and allows modifying the coding sequence on the fly. It also enables uploading any coding sequence and simulating its translation in one of three model organisms. In such a case, ribosomes propagate according to mean codon elongation times of the host organism, which may prove useful for heterologous expression. Transimulation was used to examine evolutionary conservation of translational parameters of orthologous genes. Transimulation may be accessed at http://nexus.ibb.waw.pl/Transimulation (requires Java version 1.7 or higher). Its manual and source code, distributed under the GPL-2.0 license, is freely available at the website