Plasma-volume contraction and exercise-induced hypoxaemia modulate erythropoietin production in healthy humans
Bibliographic record
Abstract
This study examined exercise-induced hypoxaemia (EIH) and plasma volume contraction as modulators of serum erythropoietin (Epo) production. Five athletes cycled for 3 min at supra-maximal power outputs, at each of two different elevations (1000 m and 2100 m). Five subjects were exposed to normobaric hypoxia (FIO2 = 0.159), seven subjects underwent plasmapheresis to reduce plasma volume and eight subjects were time controls for Epo levels. Oxyhaemoglobin saturation was significantly reduced during exercise and during normobaric hypoxia. The time period of haemoglobin oxygen saturation < 91% was 24±29 s (mean±S.D., n = 5) for exercise at 1000 m, 136±77 s (mean±S.D., n = 5) for exercise at 2100 m and 178±255 s (mean±S.D., n = 5) with resting hypoxic exposure. However, significantly increased serum Epo levels were observed only following exercise (24±3%; mean±S.D., n = 5 at 1000 m and 36±5%; mean±S.D., n = 5 at 2100 m). Volume contraction also resulted in increased serum Epo (35±6%; mean±S.D., n = 7) in spite of a significant rise in haematocrit of 2.2%. Despite similar degrees of arterial desaturation, only the hypoxaemia induced by exercise was associated with an increase in serum Epo. This finding indicates that other factors, in addition to hypoxaemia, are important in modulating the production of Epo in response to exercise. Volume depletion in the absence of exercise resulted in increases in Epo levels that were comparable with those observed in response to exercise. The paradoxical responses of the increased haematocrit and the increase in Epo in subjects undergoing plasmapheresis suggests that plasma volume may also modulate the production of Epo.
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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".