Immune dysfunction in spaceflight and diabetes mellitus – translating space observations to terrestrial disease
Bibliographic record
Abstract
Introduction: Spaceflight alters normal physiology of cells and tissues seen on Earth. Immune cells and signaling molecules appear to be particularly affected, resulting in changes in leukocyte populations, killing ability and effector function, and signaling molecule response. Akin to spaceflight, diabetes mellitus produces significant immune system dysfunction. Applying observations and interventions from spaceflight to conditions such as diabetes mellitus may help to identify new approaches that combat the high clinical and financial burden of terrestrial disease.Discussion: A literature review was conducted using PubMed, MEDLINE, and Google Scholar. Papers of immune cells conducted in space and studies on diabetes mellitus-related immune dysfunction were included. Broad themes of immunosuppression were seen in both spaceflight and diabetes mellitus. Effects on lymphocytes, neutrophils, eosinophils, monocytes, fibroblasts, growth factors, and inflammatory factors are presented.Conclusions: Immune responses to spaceflight and DM are inconsistent. The innate immune system responds similarly to spaceflight and DM. In contrast, the adaptive immune system responds differently to spaceflight than to DM. This difference may be the result of a glucocorticoid dominant response linked to innate suppression and a Th2 lymphocyte shift.Relevance: Diabetes mellitus causes major morbidity and mortality on Earth. Further research is needed to elucidate mechanisms behind these differences and develop countermeasures for immunosuppression in space with application towards diabetic therapy on earth. Furthermore, commercial spaceflight makes it all the more necessary to elucidate these mechanisms as civilian participants with diabetes mellitus or other immune-altering conditions may be space bound.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".