Medium Chain Triglycerides Modulate the Ketogenic Effect of a Metabolic Switch
Bibliographic record
Abstract
Ketones provide an alternative brain fuel and may be neuroprotective in older people. Little is known of how to optimize the ketogenic effect of C8:0-C10:0 medium chain triglyceride supplement (kMCT). Metabolic switching (MS) from glucose to ketones as a fuel may have metabolic benefits but has not been extensively studied in humans. The objective of the present study was to use an 8 h metabolic study day protocol to assess the influence of typical components of MS, including a kMCT supplement, low-carbohydrate meal and meal timing, on blood ketones, glucose, insulin and free fatty acids (FFA). In one test, the effect of age was also investigated. Over the 8 h metabolic study day, two 10 g doses of the kMCT increased the plasma ketone response by 19% while reducing overall glycemia by 12% without altering insulin or FFA levels. Moreover, a single early meal (breakfast but no lunch) potentiated the ketogenic effect of MS over 8 h, compared to a single delayed meal (lunch but no breakfast). Age and the low carbohydrate meal did not affect the ketones response. We conclude that an 8-h test period can be used to assess metabolic changes during short-term MS. kMCT provide a robust short-term increase in ketones and might enhance the metabolic effectiveness of short-term or intermittent fasting as a component of MS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".