Going to extremes - a metagenomic journey into the dark matter of life

The Virus-X-Viral Metagenomics for Innovation Value-project was a scientific expedition to explore and exploit uncharted territory of genetic diversity in extreme natural environments such as geothermal hot springs and deep-sea ocean ecosystems. Specifically, the project was set to analyse and exploit viral metagenomes with the ultimate goal of developing new gene products with high innovation value for applications in biotechnology, pharmaceutical, medical, and the life science sectors. Viral gene pool analysis is also essential to obtain fundamental insight into ecosystem dynamics and to investigate how viruses influence the evolution of microbes and multicellular organisms. The Virus-X Consortium, established in 2016, included experts from eight European countries. The unique approach based on high throughput bioinformatics technologies combined with structural and functional studies resulted in the development of a biodiscovery pipeline of significant capacity and scale. The activities within the Virus-X consortium cover the entire range from bioprospecting and methods development in bioinformatics to protein production and characterisation, with the final goal of translating our results into new products for the bioeconomy. The significant impact the consortium made in all of these areas was possible due to the successful cooperation between expert teams that worked together to solve a complex scientific problem using state-of-the-art technologies as well as developing novel tools to explore the virosphere, widely considered as the last great frontier of life.

The Longitudinal Association between Self-esteem and Depressive Symptoms in Adolescents: Separating between-person effects from within-person effects

Many longitudinal studies have investigated whether self-esteem predicts depressive symptoms (vulnerability model) or the other way around (scar model) in adolescents. The most common method of analysis has been the Cross-lagged Panel Model (CLPM). The CLPM does not separate between-person effects from within-person effects, making it unclear whether the results from previous studies actually reflect the within-person effects, or whether they reflect differences between people. We investigated the associations between self-esteem and depressive symptoms at the within-person level, using Random Intercept Cross-Lagged Panel Models (RI-CLPM). To get an impression of the magnitude of possible differences between the RI-CLPM and CLPM, we compared the results of both models. We used data from three longitudinal adolescent samples (age range 7-18; Study 1: N=1,948; Study 2: N=1,455; Study 3: N=316). Intervals between the measurements were 1-1.5 years. Single-paper meta-analyses showed support for small within-person associations from self-esteem to depressive symptoms, but not the other way around, thus only providing some support for the vulnerability model. The cross-lagged associations in the aggregated RI-CLPM and CLPM showed similar effect sizes. Overall, our results show that over 1-1.5 year time intervals, low self-esteem may negatively influence depressive symptoms over time within adolescents, but only weakly so.

Trajectories of loneliness during childhood and adolescence: predictors and health outcomes

The present study employed latent growth mixture modeling to discern distinct trajectories of loneliness using data collected at 2-year intervals from age 7-17 years (N = 586) and examine whether measures taken at age 5 years were good predictors of group membership. Four loneliness trajectory classes were identified: (1) low stable (37% of the sample), (2) moderate decliners (23%), (3) moderate increasers (18%), and (4) relatively high stable (22%). Predictors at age 5 years for the high stable trajectory were low trust beliefs, low trusting, low peer acceptance, parent reported negative reactivity, an internalizing attribution style, low self-worth, and passivity during observed play. The model also included outcome variables. We found that both the high stable and moderate increasing trajectories were associated with depressive symptoms, a higher frequency of visits to the doctor, and lower perceived general health at age 17. We discuss implications of findings for future empirical work.