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Stress increases among the working population in Germany. Workplace stress management interventions are therefore becoming increasingly important, especially in the public sector, which has a higher structural risk for work-related stress than other organizations. Currently, face-to-face formats dominate, but promising digital offerings are being developed. The aim of this study was to investigate the effectiveness of a stress management intervention as a face-to-face and self-guided digital format, referring to the Job Demands-Resources Model. The preregistered study applied a randomized control group design in which N = 65 public service employees were assigned to face-to-face training, an online course, or waitlist control group. Participants completed online questionnaires before the intervention, shortly after the intervention, and six weeks later. Although trends for reductions in emotional exhaustion and perceived stress were evident among the intervention groups, mixed analyses of variance showed no interaction effects between the time and group on the outcomes. The main effects showed a significant decrease in stress levels regardless of the group and significant differences between intervention groups, with the online course reporting the lowest stress level. The results indicate that digital and analog stress management interventions can have desired effects within occupational health management. However, many unpredictable events (e.g., illness, vacation during the intervention) seem to influence the effectiveness in the workplace setting, and so further research is needed. [ABSTRACT FROM AUTHOR]

Background: The demand for biobased polymers is increasing steadily worldwide. Microbial hosts for production of their monomeric precursors such as glutarate are developed. To meet the market demand, production hosts have to be improved constantly with respect to product titers and yields, but also shortening bioprocess duration is important. Results: In this study, adaptive laboratory evolution was used to improve a C. glutamicum strain engineered for production of the C5-dicarboxylic acid glutarate by flux enforcement. Deletion of the l-glutamic acid dehydrogenase gene gdh coupled growth to glutarate production since two transaminases in the glutarate pathway are crucial for nitrogen assimilation. The hypothesis that strains selected for faster glutarate-coupled growth by adaptive laboratory evolution show improved glutarate production was tested. A serial dilution growth experiment allowed isolating faster growing mutants with growth rates increasing from 0.10 h−1 by the parental strain to 0.17 h−1 by the fastest mutant. Indeed, the fastest growing mutant produced glutarate with a twofold higher volumetric productivity of 0.18 g L−1 h−1 than the parental strain. Genome sequencing of the evolved strain revealed candidate mutations for improved production. Reverse genetic engineering revealed that an amino acid exchange in the large subunit of l-glutamic acid-2-oxoglutarate aminotransferase was causal for accelerated glutarate production and its beneficial effect was dependent on flux enforcement due to deletion of gdh. Performance of the evolved mutant was stable at the 2 L bioreactor-scale operated in batch and fed-batch mode in a mineral salts medium and reached a titer of 22.7 g L−1, a yield of 0.23 g g−1 and a volumetric productivity of 0.35 g L−1 h−1. Reactive extraction of glutarate directly from the fermentation broth was optimized leading to yields of 58% and 99% in the reactive extraction and reactive re-extraction step, respectively. The fermentation medium was adapted according to the downstream processing results. Conclusion: Flux enforcement to couple growth to operation of a product biosynthesis pathway provides a basis to select strains growing and producing faster by adaptive laboratory evolution. After identifying candidate mutations by genome sequencing causal mutations can be identified by reverse genetics. As exemplified here for glutarate production by C. glutamicum, this approach allowed deducing rational metabolic engineering strategies. [ABSTRACT FROM AUTHOR]