Why does placement of persons with Alzheimer's disease into long-term care improve caregivers' well-being? Examination of psychological mediators.

Caregiving for individuals with Alzheimer's disease is associated with chronic stress and elevated symptoms of depression. Placement of the care receiver (CR) into a long-term care setting may be associated with improved caregiver well-being; however, the psychological mechanisms underlying this relationship are unclear. This study evaluated whether decreases in activity restriction and increases in personal mastery mediated placement-related reductions in caregiver depressive symptoms. In a 5-year longitudinal study of 126 spousal Alzheimer's disease caregivers, we used multilevel models to evaluate placement-related changes in depressive symptoms (short form of the Center for Epidemiologic Studies Depression scale), activity restriction (Activity Restriction Scale), and personal mastery (Pearlin Mastery Scale) in 44 caregivers who placed their spouses into long-term care relative to caregivers who never placed their CRs. The Monte Carlo method for assessing mediation was used to evaluate the significance of the indirect effect of activity restriction and personal mastery on postplacement changes in depressive symptoms. Placement of the CR was associated with significant reductions in depressive symptoms and activity restriction and was also associated with increased personal mastery. Lower activity restriction and higher personal mastery were associated with reduced depressive symptoms. Furthermore, both variables significantly mediated the effect of placement on depressive symptoms. Placement-related reductions in activity restriction and increases in personal mastery are important psychological factors that help explain postplacement reductions in depressive symptoms. The implications for clinical care provided to caregivers are discussed.

Comparison of 3D kinetic and hydrodynamic models to ROSINA-COPS measurements of the neutral coma of 67P/Churyumov-Gerasimenko

67P/Churyumov-Gerasimenko (67P) is a Jupiter-family comet and the object of investigation of the European Space Agency mission Rosetta. This report presents the first full 3D simulation results of 67P’s neutral gas coma. In this study we include results from a direct simulation Monte Carlo method, a hydrodynamic code, and a purely geometric calculation which computes the total illuminated surface area on the nucleus. All models include the triangulated 3D shape model of 67P as well as realistic illumination and shadowing conditions. The basic concept is the assumption that these illumination conditions on the nucleus are the main driver for the gas activity of the comet. As a consequence, the total production rate of 67P varies as a function of solar insolation. The best agreement between the model and the data is achieved when gas fluxes on the night side are in the range of 7% to 10% of the maximum flux, accounting for contributions from the most volatile components. To validate the output of our numerical simulations we compare the results of all three models to in situ gas number density measurements from the ROSINA COPS instrument. We are able to reproduce the overall features of these local neutral number density measurements of ROSINA COPS for the time period between early August 2014 and January 1 2015 with all three models. Some details in the measurements are not reproduced and warrant further investigation and refinement of the models. However, the overall assumption that illumination conditions on the nucleus are at least an important driver of the gas activity is validated by the models. According to our simulation results we find the total production rate of 67P to be constant between August and November 2014 with a value of about 1 × 10²⁶ molecules s⁻¹.

A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.