Assessing the Impact of Factors that Influence the Ketogenic Response to Varying Doses of Medium Chain Triglyceride (MCT) Oil
Bibliographic record
Abstract
Objectives, Design, Setting: The ketogenic effect of medium chain triglyceride (MCT) oil offers potential for Alzheimer's disease prevention and treatment. Limited literature suggests a linear B-hyroxybutyrate (BHB) response to increasing MCT doses. This pharmacokinetic study evaluates factors affecting BHB response in three subject groups. PARTICIPANTS: Healthy subjects without cognitive deficits <65years, similarly healthy subjects >=65years, and those with Alzheimer's Disease were assessed. INTERVENTION: Different doses (0g,14g, 28g, 42g) of MCT oil (99.3% C8:0) were administered, followed by fasting during the study period. MEASUREMENTS: BHB measured by finger prick sampling hourly for 5 hours after ingestion. Each subject attended four different days for each ascending dose. Data was also collected on body composition, BMI, waist/hip ratio, grip strength, gait speed, nutrient content of pre-study breakfast and side effects. RESULTS: Twenty-five participants: eight healthy; average age of 44yr (25-61), nine healthy; 79yr (65-90) and eight with AD; 78.6yr (57-86) respectively. Compiled data showed the expected linear dose response relationship. No group differences, with baseline corrected area under the blood vs. time curve (r2=0.98) and maximum concentrations (r2=0.97). However, there was notable individual variability in maximum BHB response (42g dose: 0.4 -2.1mM), and time to reach maximum BHB response both, within and between individuals. Variability was unrelated to age, sex, sarcopenic or AD status. Visceral fat, BMI, waist/hip ratio and pretest meal CHO and protein content all affected the BHB response (p<0.001). CONCLUSION: There was a large inter-individual variability, with phenotype effects identified. This highlights challenges in interpreting clinical responses to MCT intake.
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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 | 0.001 | 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".