Long‐chain Polyunsaturated Fat Supplementation in Children With Low Docosahexaenoic Acid Intakes Alters Immune Phenotypes Compared With Placebo
Bibliographic record
Abstract
OBJECTIVES: The objectives of this study were to assess the effects of long-term supplementation with arachidonic acid (AA; 20:4n-6) and docosahexaenoic acid (DHA; 22:6n-3) on cell phenotypes and cytokine production in children. PATIENTS AND METHODS: This randomized, double-blind, placebo-controlled trial provided children, (ages 5-7 years; n = 37) who had low intakes of DHA, with a dietary supplement containing AA (20-30 mg daily) and DHA (14-21 mg daily) or a placebo supplement for 7 months. After the supplementation period, a series of stimulants (pokeweed mitogen, phytohemagluttinin, lipopolysaccharide, beta-lactoglobulin, and ibuprofen) was used to stimulate peripheral blood mononuclear cells ex vivo. Antigen expression on T cells (CD25 and CD80), B cells, and macrophages (CD54), as well as cytokine production (interleukin [IL]-4, IL-10, tumor necrosis factor, IL-2, IL-6, and interferon-gamma), were measured using flow cytometry, monoclonal antibodies, and cytometric bead array, respectively. RESULTS: Mononuclear cells from children provided long-chain polyunsaturated fatty acids (LCPUFAs) had fewer CD8+ cells expressing CD25 and CD80 compared with placebo after exposure to each mitogen. The LCPUFA group also exhibited lower proportions of CD14+ cells after stimulation with beta-lactoglobulin and ibuprofen. The proportion of CD54+ cells was 2-fold higher for the LCPUFA group compared with placebo after exposure to ibuprofen and beta-lactoglobulin (P < 0.05). Each of these immune effects related to the amount of AA and/or DHA in the plasma and erythrocyte phospholipids. CONCLUSIONS: Alterations in cell phenotypes were evident when children were supplemented with AA and DHA. The results of this study have important implications for immune development and sensitivity to antigens in children.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".