Metabolic programming of long‐term outcomes due to fatty acid nutrition in early life
Bibliographic record
Abstract
Understanding of the importance of dietary fatty acids has grown beyond a simple source of energy to complex roles in regulating gene expression and cell and intracellular communication. This is important because the metabolic and neuroendocrine environment of the fetus and infant plays a key role in guiding the set point of neural receptors that regulate energy homeostasis and expression of genes that control energy storage and oxidation. Early deviations in these pathways have the potential to lead to lasting adaptations, termed metabolic programming, which may combine to increase the risk of metabolic syndrome in later life. The quality of fatty acids in human diets has undergone major changes in the last 50 years, characterized by an increase in ω-6 and decrease in ω-3 fatty acids. Evidence is accumulating to support the concept that the maternal intake of ω-6 and ω-3 fatty acids in gestation and lactation, possibly involving both excess ω-6 and inadequate ω-3 fatty acids, can impact the developing infant tissue lipids and neuroendocrine and metabolic pathways relevant to metabolic programming. Further work is needed to understand the needs for different ω-6 and ω-3 fatty acids during fetal and infant life, and their roles with respect to development of energy homeostasis and metabolism.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".