Brain energy rescue with ketones improves cognitive outcomes in MCI
Bibliographic record
Abstract
Abstract Background An emerging strategy to delay the onset of Alzheimer disease (AD) is to use ketones to overcome the progressive brain energy deficit caused by deteriorating brain glucose metabolism in mild cognitive impairment (MCI). Ketones (acetoacetate and beta‐hydroxybutyrate) are the brain’s main alternative fuel to glucose; in contrast to glucose, ketone metabolism by the brain is now known to be unaffected in MCI and AD. Successful brain energy rescue with ketones in MCI was recently reported. Methods In the 6‐month, randomized, placebo‐controlled Benefic Trial (NCT02551419), the active arm was a ketogenic medium chain triglyceride (kMCT) supplement in a lactose‐free skim milk emulsion (15 g kMCT twice/day; n = 39 completers). The placebo arm was a non‐ketogenic iso‐energetic vegetable oil (n = 44 completers). Brain ketone and glucose metabolism were assessed by PET. Results Performance on all five cognitive domains improved significantly over 6 months in the kMCT group: (i) Episodic memory (trial 1, Free and Cued Recall Test) increased by 1 word (+0.5 Δ Z‐score); (ii) Executive function (Verbal Fluency Test) correct answers increased by 2 words (+0.3 Δ Z‐score) but decreased by 1 word on placebo (‐0.1 Δ Z‐score), time taken on the Stroop Colour Naming Test decreased by 1 sec (p = 0.09), and errors on the Trail Making Test increased by 0.8 on placebo (p = 0.02); (iii) Language (Boston naming test) correct answers increased by 1.3 words. (iv) Processing speed increased directly with higher brain ketone uptake in several white matter tracts. (v) Improved attention was directly associated with increased ketone uptake and functional connectivity in the dorsal attention network. Conclusions Improved cognition correlating positively with improved brain energy supply by ketones suggests a direct link to brain energy status. The moderate effect size of this kMCT intervention indicates a clinically meaningful benefit on certain cognitive outcomes, some of which relate directly to risk of MCI progressing to AD. Other potential ketogenic interventions that have been less well studied in MCI or AD include a ketogenic diet and ketone salts or esters. Whether brain energy rescue with ketones can delay the onset or progression of AD should now be assessed.
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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) | 0.002 | 0.001 |
| 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 | 0.001 | 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".