MétaCan
Menu
← Back to cohort
Record W2538440182 · doi:10.1109/nssmic.2009.5401943

Regional brain uptake of ketone bodies and glucose in elderly humans: A<sup>11</sup>C-acetoacetate and<sup>18</sup>F-FDG PET study

2009· article· en· W2538440182 on OpenAlexaff
M’hamed Bentourkia, Sébastien Tremblay, Mélanie Fortier, Étienne Croteau, Otman Sarrhini, Éric Turcotte, Stephen C. Cunnane

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsKetone bodiesKetogenic dietPositron emission tomographyCarbohydrate metabolismKetosisMetabolismKetoneHuman brainNuclear medicineMedicineInternal medicineChemistryEndocrinologyDiabetes mellitusPsychiatry

Abstract

fetched live from OpenAlex

The brain relies on glucose as its primary energy substrate. However, ketone bodies, i.e. acetoacetate and hydroxybutyrate, are the main replacement fuels for brain activity during fasting or on a ketogenic (very high fat, low carbohydrate) diet. We report here a study of ketone and glucose metabolism in human brain in young (mean 26 years) and aged (mean 73 years) healthy individuals as measured with positron emission tomography (PET), using the radiotracers11C-acetoacetate and18F-fluorodeoxyglucose (FDG). Three blood samples were withdrawn during the two scans and were analyzed for plasma radioactivity and for concentration of acetoacetate, hydroxybutyrate and glucose. In the eighteen selected brain regions for this study, although the standard uptake values (SUV) were lower in the elderly subjects compared to the young subjects, the ratio of SUV in aged on young were almost similar in glucose and ketone metabolism. This protocol for brain fuel measurement by PET can be combined with treatment or on ketogenic diet to further study brain metabolism in neurodegenerative pathologies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.033
GPT teacher head0.298
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicDiet and metabolism studies→French-language works237,207→