AA and DHA are decreased in paediatric AD/HD and inattention is ameliorated by increased plasma DHA
Bibliographic record
Abstract
The purpose of this study was to assess long chain polyunsaturated fatty acid (LCPUFA) status in relation to socio-behavioral outcomes in children with Attention Deficit/Hyperactivity Disorder (AD/HD). In a case-control design, plasma phospholipid fatty acid content was assessed in children aged 5–12 years with AD/HD and in typically functioning children. Dietary intakes of LCPUFAs arachidonic acid (AA; 20:4n6) and docosahexaenoic acid (DHA; 22:6n3) were quantified using a four-day food record, polymorphisms were determined in FADS1 and FADS2, and socio-behavioral outcomes were assessed using the Conners 3 Parent Rating Scales in a cross section of children with AD/HD. Compared to typically functioning children, plasma AA and DHA were 40% lower in children with AD/HD. Median intake of AA, but not DHA, was higher in children with AD/HD compared to typically functioning children. Polymorphisms in FADS1 (rs174546) and FADS2 (174575) were associated with higher plasma linoleic acid (LA; 18:2n6) level. Plasma DHA level was inversely associated with inattention score. Despite having an elevated intake of AA, children diagnosed with AD/HD have a reduction in plasma AA level which may be due in part to polymorphisms in the fatty acid desaturase (FADS) gene cluster or increased conversion to AA-derived metabolites. Increasing intake of DHA may ameliorate symptoms of inattention in AD/HD.
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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) | 0.000 | 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) | 0.001 | 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".