O4‐05‐03: Ketogenic Diet Effects on Brain Ketone Metabolism and Alzheimer's Disease Csf Biomarkers
Bibliographic record
Abstract
Diet is a powerful modulator of brain function. The ketogenic diet (KD), a very low carbohydrate diet, is remarkably effective in treating refractory epilepsy; 50-70% of patients have >50% seizure reduction and 30% have >90% seizure reduction. Although the mechanisms underlying its effectiveness are not definitively known, reduction of neuronal hyperexcitability and neuroprotective effects of ketones have been demonstrated, as has reduction in AD pathology in rodent models. In small pilot studies, interventions that elevate ketones improve memory in adults with MCI and AD. The present study was undertaken to determine whether elevating ketones with diet affected cerebral bioenergetics and AD biomarkers in cerebrospinal fluid (CSF) in adults at risk for AD due to amnestic mild cognitive impairment (MCI) and metabolic dysregulation (prediabetes). Adults with MCI and prediabetes (n=10, mean age=63.6) consumed a 6-week ketogenic diet (<15g carb per day) and a 6-week low fat diet (<10g fat per day) in random order, separated by a 6-week washout period. Diets were equicaloric with participants’ normal diet. Compliance was verified by measuring plasma ketone levels during intervention. Brain glucose and ketone metabolism were assessed before and after the intervention with dual tracer F-FDG and C-acetoacetate PET. Cerebrospinal fluid (CSF) was collected at baseline and after each intervention and assayed for AD biomarkers (Aβ42 and total tau) with INNO-BIA-Alzbio3. Global C-acetoacetate uptake decreased after the lowfat diet intervention (Fig 1 A Baseline and Fig 1 B Post-Lowfat Diet) and increased after the ketogenic diet intervention (Fig 1C Baseline and Fig 1D Post-Ketogenic Diet), whereas no changes were observed for F-FDG after either diet. Interestingly, CSF total tau increased with the ketogenic diet (p<0.05), with a similar trend noted for Aβ42 (p=0.08). Furthermore, the increase in Aβ42and tau biomarkers was correlated (r=, p=0.002). No biomarker changes were observed after low fat diet intervention.
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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) | 0.000 | 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) | 0.006 | 0.001 |
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.
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".