The molecular mechanisms driving physiological changes after long duration space flights revealed by quantitative analysis of human blood proteins
Bibliographic record
Abstract
BACKGROUND: The conditions of space flight have a significant effect on the physiological processes in the human body, yet the molecular mechanisms driving physiological changes remain unknown. METHODS: Blood samples of 18 Russian cosmonauts who had conducted long-duration missions to the International Space Station were collected 30 days before launch and on the first and seventh days after landing. RESULTS: A panel of 125 proteins in the blood plasma was quantitated by a well-established and highly regarded targeted mass spectrometry approach. This method involves the monitoring of multiple reactions in conjunction with stable isotope-labeled standards at the University of Victoria - Genome BC Proteomics Centre. CONCLUSIONS: Reduction of circulating plasma volume during space flight and activation of fluid retention at the final stage of the flight affect the changes in plasma protein concentrations present in the first days after landing. Using an ANOVA approach, it was revealed that only 1 protein (S100A9) reliably responded to space flight conditions. This protein plays an important role in the functioning of the endothelium and can serve as a marker for activation of inflammatory reactions. Concentrations of the proteins of complement, coagulation cascades, and acute phase reactants increase in the blood of cosmonauts as measured the first day after landing. Most of these proteins' concentrations continue to increase by the 7th day after space flight. Similar dynamics are observed for proteases and their inhibitors. Thus, there is a shift in proteolytic blood systems, which is necessary for the restoration of muscle tissue and maintenance of oncotic homeostasis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".