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We propose an integrated model of learning demands, work-related resources, and job stressors, which incorporates core assumptions of work design in predicting processes of learning and performance as well as health impairment. The model was tested in a heterogeneous sample of 830 employees using structural equation modeling. Empirical results largely support theoretical assumptions. Learning demands and work-related resources were positively related to intrinsic motivation and creative performance. Job stressors and low work-related resources were predictive for health impairment. The suggested tripartite taxonomy reconciles inconsistent research findings on the impact of work characteristics. The model provides practical guidance for work analysis and design by clarifying relationships between established work characteristics, job performance, and worker health.

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While some individuals age without pathological memory impairments, others develop age‐associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study, we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3‐microRNA signature that reflects key processes linked to neural homeostasis and inform about cognitive status. We furthermore provide evidence that expression changes in this signature represent multiple mechanisms deregulated in the aging and diseased brain and are a suitable target for RNA therapeutics.

Alzheimer's disease (AD) is a devastating brain disorder clinically characterised by progressive loss of characteristic cognitive abilities. Increasing evidence suggests a disturbed copper (Cu) homeostasis to be associated with the pathological processes. In the present study we analysed the plasma Cu levels and cognitive abilities using the Alzheimer's disease Assessment Scale-cognitive subscale (ADAS-cog) in 32 patients with mild to moderate AD. Statistical analysis revealed a negative correlation between plasma Cu levels and cognitive decline (r = −0.49; P < 0.01). Patients with low plasma Cu (mean 82 ± SD 9) had significant higher ADAS-cog values (mean 23 ± SD 7), than patients with medium plasma Cu (mean 110 ± SD 7), who exhibited lower ADAS-cog scores (mean 16 ± SD 4; ANOVA, P < 0.0001). Despite the fact that all patients had plasma Cu levels within the physiological range between 65 µg and 165 µg/dL, 87.5% of the patients revealed a significant negative correlation between plasma Cu and ADAS-cog. This finding supports the hypothesis of a mild Cu deficiency in most AD patients.