Reduction of Arachidonate Is Associated With Increase in B‐Cell Activation Marker in Infants
Bibliographic record
Abstract
BACKGROUND: Infants who are not breast-fed benefit from formula with both docosahexaenoic acid (C22:6n3) and arachidonic acid (ARA; C20:4n6). The amount of ARA needed to support immune function is unknown. Infants who carry specific fatty acid desaturase (FADS) polymorphisms may require more dietary ARA to maintain adequate ARA status. OBJECTIVE: The aim of the study was to determine whether ARA intake or FADS polymorphisms alter ARA levels of lymphocytes, plasma, and red blood cells in term infants fed infant formula. METHODS: Infants (N = 89) were enrolled in this prospective, double-blind controlled study. Infants were randomized to consume formula containing 17 mg docosahexaenoic acid and 0, 25, or 34 mg ARA/100 kcal for 10 weeks. Fatty acid composition of plasma phosphatidylcholine and phosphatidylethanolamine, total fatty acids of lymphocytes and red blood cells, activation markers of lymphocytes, and polymorphisms in FADS1 and FADS2 were determined. RESULTS: Lymphocyte ARA was higher in the 25-ARA formula group than in the 0- or 34-ARA groups. In plasma, 16:0/20:4 and 18:0/20:4 species of phosphatidylcholine and phosphatidylethanolamine were highest and 16:0/18:2 and 18:0/18:2 were lowest in the 34-ARA formula group. In minor allele carriers of FADS1 and FADS2, plasma ARA content was elevated only at the highest level of ARA consumed. B-cell activation marker CD54 was elevated in infants who consumed formula containing no ARA. CONCLUSIONS: ARA level in plasma is reduced by low ARA consumption and by minor alleles in FADS. Dietary ARA may exert an immunoregulatory role on B-cell activation by decreasing 16:0/18:2 and 18:0/18:2 species of phospholipids. ARA intake from 25 to 34 mg/100 kcal is sufficient to maintain cell ARA level in infants across genotypes.
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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 | 0.000 | 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) | 0.001 | 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".