Variability in valproic acid (VPA) metabolite signatures in children
Bibliographic record
Abstract
VPA is associated with an idiosyncratic hepatotoxicity that is most prevalent in children under 2 years of age receiving concurrent enzyme‐inducing anti‐epileptic drugs. The goal of this study was to establish the limits of normal variability in VPA metabolite patterns in a population of children. Urine was collected over a steady state dosing interval in 91 pediatric patients aged 2 to 17 years receiving VPA either as monotherapy or polytherapy, and analyzed by GC‐MS methods for VPA and 14 metabolites. Principal components analysis of the log‐transformed metabolite data (corrected for urinary creatinine) revealed three distinct clusters of metabolites generally corresponding to microsomal biotransformation, mitochondrial beta‐oxidation, and N‐acetylcysteine (NAC) metabolites derived from glutathione (GSH)‐conjugates of (E)‐2,4‐diene. If NAC conjugates are the products of reactive metabolite formation and GSH conjugation in mitochondria and free 2,4‐diene‐VPA is derived from a non‐reactive microsomal pathway, we hypothesize that the NAC‐VPA/2,4‐diene ratio may reflect interindividual variability in bioactivation and detoxification capacity. A Q‐Q plot of the log‐transformed ratio implies a bimodal distribution that is being evaluated as a potential biomarker for VPA‐toxicity in this population. Supported by grant U01 HD‐044239 from NICHD
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".