Effects of intermittent hypoxia on erythropoietin, soluble erythropoietin receptor and ventilation in humans
Bibliographic record
Abstract
Erythropoietin (EPO) and soluble EPO receptors (sEPOR) have been proposed to play a central role in the ventilatory acclimatisation to continuous hypoxia in mice. In this study, we demonstrated for the first time in humans (n = 9) that sEPOR is downregulated upon daytime exposure to 4 days of intermittent hypoxia (IH; 6 h·day⁻¹, cycles of 2 min of hypoxia followed by 2 min of reoxygenation; peak end-tidal oxygen tension (P(ET,O₂)) 88 Torr, nadir P(ET,O₂)) 45 Torr), thereby allowing EPO concentration to rise. We also determined the strength of the association between these haematological adaptations and alterations in the acute hypoxic ventilatory response (AHVR). We observed a nadir in sEPOR on day 2 (-70%), concomitant with the peak in EPO concentration (+50%). Following exposure to IH, tidal volume (V(T)) increased, respiratory frequency remained unchanged, and minute ventilation (V'(E)) was increased. There was a negative correlation between EPO and sEPOR (r = -0.261; p = 0.05), and between sEPOR and V(T) (r = -0.331; p = 0.02). EPO was positively correlated with V'(E) (r = 0.458; p = 0.001). In conclusion, the downregulation of sEPOR by IH modulates the subsequent EPO response. Furthermore, the alterations in AHVR and breathing pattern following IH appear to be mediated, at least in part, by the increase in 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".