The Effect of Microgravity on Parathyroid Hormone Secretion: A Meta-Analysis
Bibliographic record
Abstract
Background: The relationship between microgravity and parathyroid hormone (PTH), a keystone of bone mineral density, remains controversial. Bone loss is a prominent, ongoing issue in spaceflight, and PTH has been suggested as a treatment for microgravity-induced osteopenia, indicating the importance of this hormone. This systematic review and meta-analysis aimed to evaluate the association between exposure to microgravity and the production of PTH. Methods: PubMed, Embase, Scopus, and Google Scholar were searched for studies reporting PTH levels during and after exposure to microgravity. Non-peer-reviewed articles, studies lacking control groups, and articles published earlier than 2002 were excluded. Twelve articles from 2002 to present, with a total of 145 subjects, were identified and the standardized mean differences from baseline PTH levels were combined in a random effects model. Two-way analysis of variance (ANOVA) with Tukey honestly significant difference (HSD) testing on weighted mean differences was conducted to obtain 95% confidence intervals. Results: Compared to baseline measurements, significant changes in PTH levels are found during and after microgravity exposure. In-flight levels significantly decrease (P < 0.01), and post-flight levels show increases. Furthermore, there is evidence of an interaction between experimental condition (real or simulated microgravity) and time after removal from microgravity on PTH. Conclusions: The findings of this systematic review and meta-analysis suggest that microgravity affects parathyroid gland function during and after spaceflight, with decreases in function in-flight and an increase at 7 days post-flight. Experimental condition also appears to play a role in the recovery timeline of PTH. J Endocrinol Metab. 2023;13(1):1-12 doi: https://doi.org/10.14740/jem849
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.030 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".