Abstract
It is likely that the human immune system will be damaged in astronauts exposed to the conditions of long-term spaceflight: isolation, containment, microgravity, radiation, and microbial contamination. In all human and animal subjects flown in space, there is evidence of immune compromise, reactivation of latent virus infection, and development of a pre-malignant or malignant condition. Moreover, in all ground-based spaceflight model investigations there is again evidence of immune compromise and reactivation of latent virus infection. Studies are in progress to determine whether malignancy, too, will be observed in experimental animals. All of these observations in spaceflight itself, or in ground-based models of spaceflight, find strong resonance in a wealth of human pathological conditions involving the immune system where reactivated virus infections and cancer appear as a natural consequence. Human immune systems compromised by stress, immunosuppressive drugs, infection, and radiation are known to lead to states of chronic infection and cancer development. The clinical conditions of EBV-driven lymphomas in transplanted patients and Kaposi sarcoma in AIDS patients come easily to mind in trying to identify these conditions. With these thoughts in mind, therefore, it is highly appropriate that careful investigations of human immunity, infection, and cancer be made by spaceflight researchers.
Original language | English (US) |
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Pages (from-to) | 2155-2156 |
Number of pages | 2 |
Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
Volume | 3 |
State | Published - 2002 |
Event | Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States Duration: Oct 23 2002 → Oct 26 2002 |
Keywords
- Astronaut immune system
- Spaceflight model
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics