Whole body and regional body composition changes following 10-day hypoxic confinement and unloading–inactivity
Bibliographic record
Abstract
Future planetary habitats will expose inhabitants to both reduced gravity and hypoxia. This study investigated the effects of short-term unloading and normobaric hypoxia on whole body and regional body composition (BC). Eleven healthy, recreationally active, male participants with a mean (SD) age of 24 (2) years and body mass index of 22.4 (3.2) kg·m(-2) completed the following 3 10-day campaigns in a randomised, cross-over designed protocol: (i) hypoxic ambulatory confinement (HAMB; FIO2 = 0.147 (0.008); PIO2 = 93.8 (0.9) mm Hg), (ii) hypoxic bed rest (HBR; FIO2 = 0.147 (0.008); PIO2 = 93.8 (0.9) mm Hg), and (iii) normoxic bed rest (NBR; FIO2 = 0.209; PIO2 = 133.5 (0.7) mm Hg). Nutritional requirements were individually precalculated and the actual intake was monitored throughout the study protocol. Body mass, whole body, and regional BC were assessed before and after the campaigns using dual-energy X-ray absorptiometry. The calculated daily targeted energy intake values were 2071 (170) kcal for HBR and NBR and 2417 (200) kcal for HAMB. In both HBR and NBR campaigns the actual energy intake was within the targeted level, whereas in the HAMB the intake was lower than targeted (-8%, p < 0.05). Body mass significantly decreased in all 3 campaigns (-2.1%, -2.8%, and -2.0% for HAMB, HBR, and NBR, respectively; p < 0.05), secondary to a significant decrease in lean mass (-3.8%, -3.8%, -4.3% for HAMB, HBR, and NBR, respectively; p < 0.05) along with a slight, albeit not significant, increase in fat mass. The same trend was observed in the regional BC regardless of the region and the campaign. These results demonstrate that, hypoxia per se, does not seem to alter whole body and regional BC during short-term bed rest.
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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 | 0.001 |
| 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".