49 research outputs found

    Factors associated with first return to work and sick leave durations in workers with common mental disorders

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    Background: Associations are examined between socio-demographic, medical, work-related and organizational factors and the moment of first return to work (RTW) (within or after 6 weeks of sick leave) and total sick leave duration in sick leave spells due to common mental disorders. Methods: Data are derived from a Dutch database, build to provide reference data for sick leave duration for various medical conditions. The cases in this study were entered in 2004 and 2005 by specially trained occupational health physicians, based on the physician's assessment of medical and other factors. Odds ratios for first RTW and sick leave durations are calculated in logistic regression models. Results: Burnout, depression and anxiety disorder are associated with longer sick leave duration. Similar, but weaker associations were found for female sex, being a teacher, small company size and moderate or high psychosocial hazard. Distress is associated with shorter sick leave duration. Medical factors, psychosocial hazard and company size are also and analogously associated with first RTW. Part-time work is associated with delayed first RTW. The strength of the associations varies for various factors and for different sick leave durations. Conclusion: The medical diagnosis has a strong relation with the moment of first RTW and the duration of sick leave spells in mental disorders, but the influence of demographic and work-related factors should not be neglected

    Identification of permissive amber suppression sites for efficient non-canonical amino acid incorporation in mammalian cells

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    The genetic code of mammalian cells can be expanded to allow the incorporation of non-canonical amino acids (ncAAs) by suppressing in-frame amber stop codons (UAG) with an orthogonal pyrrolysyl-tRNA synthetase (PylRS)/tRNAPylCUA (PylT) pair. However, the feasibility of this approach is substantially hampered by unpredictable variations in incorporation efficiencies at different stop codon positions within target proteins. Here, we apply a proteomics-based approach to quantify ncAA incorporation rates at hundreds of endogenous amber stop codons in mammalian cells. With these data, we compute iPASS (Identification of Permissive Amber Sites for Suppression; available at www.bultmannlab.eu/tools/iPASS), a linear regression model to predict relative ncAA incorporation efficiencies depending on the surrounding sequence context. To verify iPASS, we develop a dual-fluorescence reporter for high-throughput flow-cytometry analysis that reproducibly yields context-specific ncAA incorporation efficiencies. We show that nucleotides up- and downstream of UAG synergistically influence ncAA incorporation efficiency independent of cell line and ncAA identity. Additionally, we demonstrate iPASS-guided optimization of ncAA incorporation rates by synonymous exchange of codons flanking the amber stop codon. This combination of in silico analysis followed by validation in living mammalian cells substantially simplifies identification as well as adaptation of sites within a target protein to confer high ncAA incorporation ratesISSN:1362-4962ISSN:0301-561
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