Bibliographic record
Abstract
Objective The cognitive advantage conferred by breastfeeding may be dependent on maternal FADS2 genotype. In a Canadian sample (Xie & Innis, 2008), fatty acid content of human milk related to genotype at rs174575 on the FADS2 gene. This study was undertaken to explore this in a sample from the USA. Methods Breastfeeding dyads were enrolled when infant was 3–4 months of age (n=200). Mothers collected a morning sample by emptying one entire breast, agitating, aliquoting, and transporting to the lab on ice. Samples were stored at −20 F until lipids were extracted and saponified. Fatty acids were trans‐methylated to methyl esters that were analyzed using capillary gas chromatography. DNA was extracted from saliva using a QIAcube robotic station (Qiagen), as per manufacturer's protocol. 20 ng DNA was used with validated primers from Applied Biosystems. The real time PCR assay was run on an Eppendorf thermal cycler. Results Maternal genotype is related to fatty acids: homozygous recessive (GG) had lower fatty acid levels than wildtype (CC). Levels of arachidonic acid, docosapentaenoic acid (n‐3), and docosahexaenoic acid reached statistical significance ( p <0.05). Conclusion The desaturases used in biosynthesis of fatty acids from their precursors may be in limited supply in certain genotypes. These mothers should insure exogenous fatty acids are being consumed. Support: Nutrition Obesity Research Center, UNC
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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) | 0.003 | 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".