A medium‐chain triglycerides‐enriched diet improves cognition and prevents metabolic and gut microbial alterations in Alzheimer’s disease models
Bibliographic record
Abstract
BACKGROUND: Lifestyle-based interventions can reduce 45% of dementia risk. Dietary supplementation with medium-chain triglycerides (MCT) is a type of ketogenic diet that shows promise against Alzheimer's disease (AD) in humans, presumably through hepatic conversion to circulating ketones. However, the physiological impacts and cellular mechanisms underlying MCT effects remain understudied, particularly in the context of AD. OBJECTIVE: Here, we used two transgenic mouse model of AD to investigate the physiological and molecular mechanisms occurring in peripheral system upon an MCT-enriched diet versus a classic ketogenic diet. METHOD: 3xTg-AD, 5xFAD mice and their respective control strain mice (WT) were administered at different age and duration, a standard carbohydrate-rich diet (Control diet, 70% carbohydrate, 20% fat, 10% protein), a similar Control diet that was supplemented with ketogenic medium-chain triglycerides (MCT, a ketogenic substrate), or an extreme carbohydrate-free, high fat diet (CFHF). Mice were subjected to learning/memory tests, and longitudinal monitoring of body composition, glycemia, ketonemia and fecal microbiome composition. RESULTS: Both ketogenic interventions improved cognition in AD mice after 1 month of treatment. Interestingly, unlike CFHF diet, MCT diet did not induce a sustained ketosis suggesting different mechanisms. Only the MCT diet improved peripheral glucose tolerance, insulin response and reduced adiposity, while CFHF dietary challenge exacerbated AD mice metabolic defects. AD mice exhibited several microbial alterations preceding cognitive symptoms, notably increased levels of Bifidobacterium and decreased levels of Bacteroidetes. Ketogenic interventions restored the fecal microbiome composition by 50% inducing a strong depletion of Bifidobacterium. CONCLUSION: Collectively, these findings reveal metabolism-improving benefits of MCT in the context of Alzheimer's disease that do not require elevated blood ketone levels and reveal potential therapeutic targets for treating AD, in the gut-brain axis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".