Dietary lipids in early development: relevance to obesity, immune and inflammatory disorders
Bibliographic record
Abstract
PURPOSE OF REVIEW: Regardless of social, cultural and behavioural environments, obesity is usually caused by an energy intake above requirements, which is accommodated by the accumulation of triacylglycerols. The composition of dietary fat impacts tissue fatty acids, which are important modulators of multiple cell functions, including differentiation, lipogenesis, lipolysis and the generation of inflammatory mediators. This review focuses on the possible contribution of fatty acids to the link between obesity and inflammation in young children. RECENT FINDINGS: Adipose tissue is a complex organ that functions to regulate fatty acid balance, clearing and releasing fatty acids, and synthesizing protein and signaling molecules that act as local and distant inflammatory mediators. Obesity, even in young children, is associated with increased circulating inflammatory mediators. As a result of changes in dietary fat compositions, infants are exposed to high n-6, saturated and trans fatty acids and low n-3 fatty acids. Saturated and trans fatty acids increase and n-3 fatty acids decrease many metabolic and inflammatory changes that accompany diet-induced triacylglycerol storage. High linoleic acid is associated with increased oxidative stress. SUMMARY: There is a biological reason to consider that dietary fatty acids may contribute to oxidative stress and heightened inflammatory responses in young 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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".