Role of Maternal/Fetal Iron Status on Placental Transferrin Receptor Expression
Bibliographic record
Abstract
The placenta plays an important role in mediating iron transfer to the fetus. However, the responsiveness of the placenta to maternal and fetal demands remains unclear. Placental transferrin receptor (TfR) is a key placental iron transport protein on the apical membrane. Placentas were collected from twelve pregnant adolescents (38‐40 wks gestation) and protein expression of TfR was examined. Iron status indicators were assessed from maternal blood obtained during the second trimester and at delivery. Cord blood samples were also collected at birth. There was a significant inverse relationship between cord serum ferritin (SF) and placental TfR expression (P=0.042). A non‐significant inverse trend was detected between maternal SF in the second trimester and placental TfR expression (P=0.075). Relationships between maternal SF in the second trimester and cord SF approached significance (P=0.055). However, maternal SF at birth was not significantly related to placental TfR expression or cord SF. Hemoglobin and TfR in both the infant and mother were not significantly related to placental TfR expression. In conclusion both maternal and fetal iron status appear to impact placental expression of TfR. Studies are on‐going to assess the impact of maternal iron status on neonatal iron stores at birth in the planned cohort of 300 pregnant teens. Grant Funding Source Supported by USDA Grant no. 2008‐0857.
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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) | 0.000 | 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) | 0.002 | 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".