Exercise attenuates bed rest-induced increases in insulin resistance while α-klotho increases in 55 to 65 year-old women and men
Bibliographic record
Abstract
We evaluated the efficacy of combined aerobic, high intensity interval (HIIT) and resistive exercises during Head-Down Bed Rest (HDBR) in preventing metabolic derangement. Twenty-two participants (control: F (5) BMI: 22.1 ± 2.1, M (6) BMI: 25.7 ± 2.2, exercise F (6) BMI: 24.3 ± 3.2, M (5) BMI: 27.5 ± 1.2; Average age: 59 ± 3 years; weight: 70.1 ± 14.2 kg; height: 1.67 ± 0.09 m; BMI: 24.9 ± 3.0 kg/m 2 )) confined to 6° HDBR for 14-days were randomly assigned to either EX (1 h/day head-down exercise including HIIT every other day) or CONT (passive movement). Oral glucose tolerance tests (OGTT) at baseline, day 9 HDBR (HDT 9) and 13 HDBR (HDT 13) were matched to fasted biomarker analyses and Vastus lateralis biopsies. HDBR increased area under the curve for glucose ( p < 0.01, interaction between groups; group × bed rest; p = 0.07) and insulin ( p < 0.01). Matsuda index fell in CONT alone, FGF-23 increased in EX correlating with elevations to circulating levels of C reactive protein; a negative correlation existed between FGF-23 and HOMA-IR in CONT. A novel finding was that α-klotho increased in all participants ( p < 0.0001), starting higher and rising faster in women, whilst negatively correlating with Matsuda index in CONT alone. Undercarboxylated-osteocalcin ratio fell in CONT ( p = 0.05). Neither IGF-1, nor GLUT1/4 protein content changed during HDBR. HDBR promoted insulin resistance with increases in circulating α-klotho; FGF-23 increased only in EX. Differing Matsuda index responses indicate benefits imparted by multimodal exercise despite elevations in α-klotho and FGF-23. Clinical Trial Registration Number : NCT04964999.
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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) | 0.001 | 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".