Ketogenic Medium Chain Triglycerides Increase Brain Energy Metabolism in Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: In Alzheimer's disease (AD), it is unknown whether the brain can utilize additional ketones as fuel when they are derived from a medium chain triglyceride (MCT) supplement. OBJECTIVE: To assess whether brain ketone uptake in AD increases in response to MCT as it would in young healthy adults. METHODS: Mild-moderate AD patients sequentially consumed 30 g/d of two different MCT supplements, both for one month: a mixture of caprylic (55%) and capric acids (35%) (n = 11), followed by a wash-out and then tricaprylin (95%; n = 6). Brain ketone (11C-acetoacetate) and glucose (FDG) uptake were quantified by PET before and after each MCT intervention. RESULTS: Brain ketone consumption doubled on both types of MCT supplement. The slope of the relationship between plasma ketones and brain ketone uptake was the same as in healthy young adults. Both types of MCT increased total brain energy metabolism by increasing ketone supply without affecting brain glucose utilization. CONCLUSION: Ketones from MCT compensate for the brain glucose deficit in AD in direct proportion to the level of plasma ketones achieved.
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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) | 0.000 | 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) | 0.002 | 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".