On the Anticonvulsant Effect of Acetone and the Ketogenic Diet
Bibliographic record
Abstract
Rho et al. (1) recently demonstrated that acetoacetate and acetone protected mice from audiogenic seizures (Epilepsia, April, 2002). The authors “propose that the anticonvulsant efficacy of the KD [ketogenic diet] may be due in part to the accumulation of acetone in the brain….” Although Rho et al. referenced past work suggesting anticonvulsant activity of acetoacetate, they failed to acknowledge the past work showing the anticonvulsant activity of acetone (2–6). Helmholz and Keith (2,3) were the first to report and demonstrate the anticonvulsant effects of acetone in the 1930s. Several more recent reports also suggested anticonvulsant activity of acetone (4–6). We have measured dose–response relations for acetone by using the maximal electroshock, pentylenetetrazole, and kindling seizure models. Our data suggest that acetone has a broad spectrum of anticonvulsant activity. These comprehensive data were presented at the PERC (Pediatric Epilepsy Research Center) Ketogenic Diet Workshop in the University of Washington in Seattle on February 8, 2001. The workshop was devoted to the possible anticonvulsant mechanisms of the ketogenic diet. Dr. Rho, the first author of the study (1), participated in the Seattle workshop but may have had difficulty acknowledging our presentation because the data have not yet been published. The possible involvement of acetone in the effects of the ketogenic diet, therefore, has previously been suggested. In our opinion, the major finding of Rho et al. is the demonstration of a direct anticonvulsant activity of acetoacetate. This is the first modern demonstration of the anticonvulsant activity of acetoacetate since the pioneering reports of Keith.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".