Task The Effects of Long-Term Exposure to Microgravity on Salivary Markers of Innate Immunity (Completed)
Last Published:  07/31/19 10:05:33 AM (Central)
Short Title: Salivary Markers
Responsible HRP Element: Human Health Countermeasures
Collaborating Org(s):
Other:
Research Operations and Integration (ROI)
Funding Status: Completed - Task completed and produced a deliverable
Procurement Mechanism(s):
Solicited
Aims:

The main goal the proposed project is to characterize acute and chronic changes in innate immune function during long duration spaceflight. To achieve this goal, the present project will address the following three specific aims:

1. Longitudinally examine the impact of long-term spaceflight (up to 6 months) on salivary and cellular markers of innate immune function and latent viral reactivation. Experimental Approach: Resting saliva, urine and blood samples will be obtained from crewmembers and two groups of earth-based controls before launch (L-180 to L-30), on-orbit (at “arly” “id”and “ate”phases of the mission) and after returning to Earth (L+1 to L+30). All samples will be returned to Earth for analysis. Saliva or urine samples will be used to measure AMP concentrations, antibacterial function, latent viral reactivation and biomarkers of stress (i.e. cortisol, catecholamines). Blood samples will be used for monocyte, neutrophil and NK-cell

phenotypic and functional assays.

2. Determine the impact of acute stressors associated with spaceflight on salivary markers of mucosal and innate immune function. Experimental Approach: Saliva samples will be collected before and immediately after (within reason) docking with the ISS, EVA and Soyuz landing. Analysis of salivary biomarkers will be identical to those described in Specific Aim 1.

3. Examine the relationship between changes in salivary and cellular markers of innate immune function and changes in other stressors associated with the spaceflight environment (i.e. circadian desynchronization, sleep loss/disruption, mood state disturbances, stress, infection incidence). Experimental Approach: generalized linear mixed model regression analysis will be adopted to explore these relationships using the longitudinal serial data (i.e within-subject measures).


Integration/Unique Aspects: TBD

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