Metabolic Framework for the Improvement of Autism Spectrum Disorders by a Modified Ketogenic Diet: A Pilot Study
Why this work is in the frame
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Bibliographic record
Abstract
The ketogenic diet (KD) can improve the core features of autism spectrum disorders (ASD) in some children, but the effects on the overall metabolism remain unclear. This pilot study investigated the behavioral parameters in relation to blood metabolites and trace elements in a cohort of 10 typically developed controls (TC) and 17 children with ASD at baseline and following 3 months of treatment with a modified KD regimen. A nontargeted, multiplatform metabolomic approach was employed, including gas chromatography–mass spectrometry, 1H nuclear magnetic resonance spectroscopy, and inductively coupled plasma–mass spectrometry. The associations among plasma metabolites, trace elements, and behavior scores were investigated. Employing a combination of metabolomic platforms, 118 named metabolites and 73 trace elements were assessed. Relative to TC, a combination of glutamate, galactonate, and glycerol discriminated ASD with 88% accuracy. ASD had higher concentrations of galactose intermediates, gut microbe-derived trimethylamine N-oxide and N-acetylserotonin, and lower concentrations of 3-hydroxybutyrate and selenium at baseline. Following 3 months of KD intervention, the levels of circulating ketones and acetylcarnitine were increased. KD restored lower selenium levels in ASD to that of controls, and correlation analysis identified a novel negative correlation between the changes in selenium and behavior scores. Based on the different behavior responses to KD, we found that high responders had greater concentrations of 3-hydroxybutyrate and ornithine, with lower galactose. These findings enhance our current understanding of the metabolic derangements present in ASD and may be of utility in predicting favorable responses to KD intervention.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it