Maternal micronutrients, omega-3 fatty acids, and placental PPARγ expression
Bibliographic record
Abstract
An altered one-carbon cycle is known to influence placental and fetal development. We hypothesize that deficiency of maternal micronutrients such as folic acid and vitamin B12 will lead to increased oxidative stress, reduced long-chain polyunsaturated fatty acids, and altered expression of peroxisome proliferator activated receptor (PPARγ) in the placenta, and omega-3 fatty acid supplementation to these diets will increase the expression of PPARγ. Female rats were divided into 5 groups: control, folic acid deficient, vitamin B12 deficient, folic acid deficient + omega-3 fatty acid supplemented, and vitamin B12 deficient + omega-3 fatty acid supplemented. Dams were dissected on gestational day 20. Maternal micronutrient deficiency leads to lower (p < 0.05) levels of placental docosahexaenoic acid, arachidonic acid, PPARγ expression and higher (p < 0.05) levels of plasma malonidialdehyde, placental IL-6, and TNF-α. Omega-3 fatty acid supplementation to a vitamin B12 deficient diet normalized the expression of PPARγ and lowered the levels of placental TNF-α. In the case of supplementation to a folic acid deficient diet it lowered the levels of malonidialdehyde and placental IL-6 and TNF-α. This study has implications for fetal growth as oxidative stress, inflammation, and PPARγ are known to play a key role in the placental development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".