Overnight hypoxic exposure and glucagon-like peptide-1 and leptin levels in humans
Bibliographic record
Abstract
Altitude exposure has been associated with loss of appetite and weight loss in healthy humans; however, the endocrine factors that contribute to these changes remain unclear. Leptin and glucagon-like peptide-1 (GLP-1) are peptide hormones that contribute to the regulation of appetite. Leptin increases with hypoxia; however, the influence of hypoxia on GLP-1 has not been studied in animals or humans to date. We sought to determine the influence of normobaric hypoxia on plasma leptin and GLP-1 levels in 25 healthy humans. Subjects ingested a control meal during normoxia and after 17 h of exposure to normobaric hypoxia (fraction of inspired oxygen of 12.5%, simulating approximately 4100 m). Plasma leptin was assessed before the meal, and GLP-1 was assessed premeal, at 20 min postmeal, and at 40 min postmeal. We found that hypoxia caused a significant elevation in plasma leptin levels (normoxia, 4.9 +/- 0.8 pg.mL-1; hypoxia, 7.7 +/- 1.5 pg.mL-1; p < 0.05; range, -16% to 190%), no change in the average GLP-1 response to hypoxia, and only a small trend toward an increase in GLP-1 levels 40 min postmeal (fasting, 15.7 +/- 0.9 vs 15.9 +/- 0.7 pmol.L-1; 20 min postmeal, 21.7 +/- 0.9 vs 21.8 +/- 1.2 pmol.L-1; 40 min postmeal, 19.5 +/- 1.2 vs. 21.0 +/- 1.2 pmol.L-1 for normoxia and hypoxia, respectively; p > 0.05 normoxia vs hypoxia). There was a correlation between SaO2 and leptin after the 17 h exposure (r = 0.45; p < 0.05), but no relation between SaO2 and GLP-1. These data confirm that leptin increases with hypoxic exposure in humans. Further study is needed to determine the influence of hypoxia and altitude on GLP-1 levels.
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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".