Inverse relationship between brain glucose and ketone metabolism in adults during short-term moderate dietary ketosis: A dual tracer quantitative positron emission tomography study
Bibliographic record
Abstract
Ketones (principally β-hydroxybutyrate and acetoacetate (AcAc)) are an important alternative fuel to glucose for the human brain, but their utilisation by the brain remains poorly understood. Our objective was to use positron emission tomography (PET) to assess the impact of diet-induced moderate ketosis on cerebral metabolic rate of acetoacetate (CMRa) and glucose (CMRglc) in healthy adults. Ten participants (35 ± 15 y) received a very high fat ketogenic diet (KD) (4.5:1; lipid:protein plus carbohydrates) for four days. CMRa and CMRglc were quantified by PET before and after the KD with the tracers, 11 C-AcAc and 18 F-fluorodeoxyglucose ( 18 F-FDG), respectively. During the KD, plasma ketones increased 8-fold ( p = 0.005) while plasma glucose decreased by 24% ( p = 0.005). CMRa increased 6-fold ( p = 0.005), whereas CMRglc decreased by 20% ( p = 0.014) on the KD. Plasma ketones were positively correlated with CMRa (r = 0.93; p < 0.0001). After four days on the KD, CMRa represented 17% of whole brain energy requirements in healthy adults with a 2-fold difference across brain regions (12–24%). The CMR of ketones (AcAc and β-hydroxybutyrate combined) while on the KD was estimated to represent about 33% of brain energy requirements or approximately double the CMRa. Whether increased ketone availability raises CMR of ketones to the same extent in older people as observed here or in conditions in which chronic brain glucose hypometabolism is present remains to be determined.
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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 | 0.001 |
| 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".