On the combined effects of normobaric hypoxia and bed rest upon bone and mineral metabolism: Results from the PlanHab study
Bibliographic record
Abstract
Bone losses are common as a consequence of unloading and also in patients with chronic obstructive pulmonary disease (COPD). Although hypoxia has been implicated as an important factor to drive bone loss, its interaction with unloading remains unresolved. The objective therefore was to assess whether human bone loss caused by unloading could be aggravated by chronic hypoxia. In a cross-over designed study, 14 healthy young men underwent 21-day interventions of bed rest in normoxia (NBR), bed rest in hypoxia (HBR), and hypoxic ambulatory confinement (HAmb). Hypoxic conditions were equivalent to 4000m altitude. Bone metabolism (NTX, P1NP, sclerostin, DKK1) and phospho-calcic homeostasis (calcium and phosphate serum levels and urinary excretion, PTH) were assessed from regular blood samples and 24-hour urine collections, and tibia and femur bone mineral content was assessed by peripheral quantitative computed tomography (pQCT). Urinary NTX excretion increased (P<0.001) to a similar extent in NBR and HBR (P=0.69) and P1NP serum levels decreased (P=0.0035) with likewise no difference between NBR and HBR (P=0.88). Serum total calcium was increased during bed rest by 0.059 (day D05, SE 0.05mM) to 0.091mM (day D21, P<0.001), with no additional effect by hypoxia during bed rest (P=0.199). HAmb led, at least temporally, to increased total serum calcium, to reduced serum phosphate, and to reduced phosphate and calcium excretion. In conclusion, hypoxia did not aggravate bed rest-induced bone resorption, but led to changes in phospho-calcic homeostasis likely caused by hyperventilation. Whether hyperventilation could have mitigated the effects of hypoxia in this study remains to be established.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".