Diabetic pregnancy, maternal and fetal docosahexaenoic acid: a review of existing evidence
Bibliographic record
Abstract
OBJECTIVE: Docosahexaenoic acid (DHA) is vital for fetal development especially during the third trimester of gestation when the speed of fetal brain growth is at its peak. Diabetes modifies the maternal fatty acid profile, which may in turn change the quantity and/or quality of lipids transferred to the fetus. Neonates born to diabetic mothers might be more vulnerable to DHA deficiency leading to lower cognitive scores together with lower overall intellectual quotients when compared to control. We reviewed the influence of type 1 or type 2 pre-gestational (PGD) and gestational diabetes mellitus (GDM) on maternal and fetal DHA levels. METHOD: We searched MEDLINE articles about PGD and/or GDM and DHA published before October 2016. RESULTS: Maternal blood DHA level seems higher in those with diabetes than those without diabetes. However, DHA in cord plasma of neonates born to PGD and/or GDM mothers seem lower compared to neonates born to nondiabetic mothers. CONCLUSIONS: Altogether, these results suggest that the transfer of DHA from the mother to the fetus may be deficient or dysregulated in diabetic pregnancies. What remains to be understood is how placental lipid transport is regulated and whether there is a link with clinical neurodevelopmental phenotypes in the newborns.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| 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) | 0.004 | 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".