A systematic review and meta-analysis of bone loss in space travelers
Bibliographic record
Abstract
Bone loss in space travelers is a major challenge for long-duration space exploration. To quantify microgravity-induced bone loss in humans, we performed a meta-analysis of studies systematically identified from searching Medline, Embase, Web of Science, BIOSIS, NASA Technical reports, and HathiTrust, with the last update in November 2019. From 25 articles selected to minimize the overlap between reported populations, we extracted post-flight bone density values for 148 individuals, and in-flight and post-flight biochemical bone marker values for 124 individuals. A percentage difference in bone density relative to pre-flight was positive in the skull, +2.2% [95% confidence interval: +1.1, +3.3]; neutral in the thorax/upper limbs, -0.7% [-1.3, -0.2]; and negative in the lumbar spine/pelvis, -6.2 [-6.7, -5.6], and lower limbs, -5.4% [-6.0, -4.9]. In the lower limb region, the rate of bone loss was -0.8% [-1.1, -0.5] per month. Bone resorption markers increased hyperbolically with a time to half-max of 11 days [9, 13] and plateaued at 113% [108, 117] above pre-flight levels. Bone formation markers remained unchanged during the first 30 days and increased thereafter at 7% [5, 10] per month. Upon landing, resorption markers decreased to pre-flight levels at an exponential rate that was faster after longer flights, while formation markers increased linearly at 84% [39, 129] per month for 3-5 months post-flight. Microgravity-induced bone changes depend on the skeletal-site position relative to the gravitational vector. Post-flight recovery depends on spaceflight duration and is limited to a short post-flight period during which bone formation exceeds resorption.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".