A short-term intervention combining aerobic exercise with medium-chain triglycerides (MCT) is more ketogenic than either MCT or aerobic exercise alone: a comparison of normoglycemic and prediabetic older women
Bibliographic record
Abstract
The objectives of this study were to determine (i) whether a 5-day aerobic exercise (AE) program combined with a medium-chain triglyceride (MCT) supplement would increase the plasma ketone response in older women more than either intervention alone and (ii) whether ketonemia after these combined or separate treatments was alike in normoglycemic (NG) and prediabetic (PD) women. Older women (NG, n = 10; PD, n = 9) underwent a 4-h metabolic study after each of 4 different treatments: (i) no treatment (control), (ii) 5 days of MCT alone (30 g·day−1), (iii) 1 session of 30 min of AE alone, and (iv) 5 days of MCT and AE combined (MCT+AE). Blood was sampled every 30 min over 4 h for analysis. In NG, MCT+AE induced the highest area under the curve (AUC) for plasma ketones (835 ± 341 μmol·h·L−1); this value was 69% higher than that observed with MCT alone (P < 0.05). AUCs were not different between MCT alone and MCT+AE in PD, but both treatments induced a significantly higher AUC than the control or AE alone (P < 0.05). Although there was a trend towards a higher ketone AUC in NG versus PD with AE alone (P = 0.091), there was no significant difference between the ketone AUCs in PD and NG. In conclusion, MCT+AE was more ketogenic in older women than MCT or AE alone. MCT+AE had a synergistic effect on ketonemia in NG but not in PD. Whether improving insulin sensitivity with a longer term AE intervention can improve the ketogenic effect of MCT in PD and thereby increase brain ketone uptake in older people merits further investigation.
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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) | 0.001 | 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".