Exercise training decreases whole‐body and tissue iron storage in adults with obesity
Bibliographic record
Abstract
New Findings What is the central question of this study? Does exercise training modify tissue iron storage in adults with obesity? What is the main finding and its importance? Twelve weeks of moderate‐intensity exercise or high‐intensity interval training lowered whole‐body iron stores, decreased the abundance of the key iron storage protein in skeletal muscle (ferritin) and tended to lower hepatic iron content. These findings show that exercise training can reduce tissue iron storage in adults with obesity and might have important implications for obese individuals with dysregulated iron homeostasis. Abstract The regulation of iron storage is crucial to human health, because both excess and deficient iron storage have adverse consequences. Recent studies suggest altered iron storage in adults with obesity, with increased iron accumulation in their liver and skeletal muscle. Exercise training increases iron use for processes such as red blood cell production and can lower whole‐body iron stores in humans. However, the effects of exercise training on liver and muscle iron stores in adults with obesity have not been assessed. The aim of this study was to determine the effects of 12 weeks of exercise training on whole‐body iron stores, liver iron content and the abundance of ferritin (the key iron storage protein) in skeletal muscle in adults with obesity. Twenty‐two inactive adults (11 women and 11 men; age, 31 ± 6 years; body mass index, 33 ± 3 kg/m2) completed 12 weeks (four sessions/week) of either moderate‐intensity continuous training (MICT; 45 min at 70% of maximal heart rate; n = 11) or high‐intensity interval training (HIIT; 10 × 1 min at 90% of maximal heart rate, interspersed with 1 min active recovery; n = 11). Whole‐body iron stores were lower after training, as indicated by decreased plasma concentrations of ferritin (P = 3 × 10−5) and hepcidin (P = 0.02), without any change in C‐reactive protein. Hepatic R2*, an index of liver iron content, was 6% lower after training (P = 0.06). Training reduced the skeletal muscle abundance of ferritin by 10% (P = 0.03), suggesting lower muscle iron storage. Interestingly, these adaptations were similar in MICT and HIIT groups. Our findings indicate that exercise training decreased iron storage in adults with obesity, which might have important implications for obese individuals with dysregulated iron homeostasis.
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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".