Factors That Influence Health-Promoting Behaviors in Cancer Caregivers.

OBJECTIVES: To describe cancer caregivers' participation in health-promoting behaviors and to identify factors influencing participation. SAMPLE & SETTING: 129 informal cancer caregivers at the National Institutes of Health Clinical Center. METHODS & VARIABLES: Cross-sectional survey methodology using Health-Promoting Lifestyle Profile-II (HPLP-II), PROMIS® Global Physical Health, NIH Toolbox Stress and Self-Efficacy, Caregiver Reaction Assessment, and Family Care Inventory Mutuality subscale. RESULTS: Caregivers reported the highest HPLP-II subscale scores for spirituality and interpersonal relationships and the lowest for physical activity. Caregivers who were older, with lower body mass indices, in better physical health, and with higher self-efficacy and mutuality participated in more health-promoting behaviors. Sixty percent of the caregivers reported that they exercised less since becoming a caregiver, and 47% reported that their diet was worse. IMPLICATIONS FOR NURSING: Future research is needed to examine novel interventions to increase health-promoting activities in cancer caregivers, and these interventions might be strengthened by including components that focus on increasing self-efficacy and/or improving the strength of the relationship between the caregiver and care recipient.

Modeling and Simulation of a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein in a Viral Membrane

This technical study describes all-atom modeling and simulation of a fully-glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB:6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently-determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully-glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19), so researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.