Reduced postural stability in men and women aged 55–65 following 14 days of head-down bed rest
Bibliographic record
Abstract
Aging and head-down bed rest (HDBR) decrease postural stability. Chances of being bedridden increase with age, but HDBR studies usually focus on young men. Here, we evaluate the impact of HDBR on postural stability among late middle-aged individuals. Twenty-two healthy participants (55-65 years old, 11 women) were exposed to 14-day HDBR. Eleven participants performed daily exercise. Static posturography data were collected before, 5 h after, and 4 weeks after HDBR. No time×group or time×sex effects were observed, but women had lower postural stability. With eyes open, the root mean square of the center of pressure was larger immediately after HDBR only in the medio-lateral axis (median [interquartile range]: +53% [+ 15%; +129%], p = 0.002). The mean velocity was increased on both axes (+ 20% [+ 8%; +46%] for medio-lateral and + 19% [+ 13%; +36%] for antero-posterior, both p < 0.001). The complexity features and the critical time were left unchanged. The effects of HDBR were more visible in the eyes open condition and the deconditioning was reversible after four weeks. 14-day HDBR decreased postural stability in individuals aged 55-65, with no impact of the chosen countermeasure. While the deconditioning was equivalent to two decades of aging for some features, additional research is required to determine whether age was an aggravating factor.
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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 | 0.001 |
| 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".