Gestational age‐dependent gene expression profiling of<scp>ATP</scp>‐binding cassette transporters in the healthy human placenta
Bibliographic record
Abstract
Abstract TheATP‐binding cassette (ABC) transporters control placental transfer of several nutrients, steroids, immunological factors, chemicals, and drugs at the maternal‐fetal interface. We and others have demonstrated a gestational age‐dependent expression pattern of twoABCtransporters, P‐glycoprotein and breast cancer resistance protein throughout pregnancy. However, no reports have comprehensively elucidated the expression pattern of all 50ABCproteins, comparing first trimester and term human placentae. We hypothesized that placentalABCtransporters are expressed in a gestational‐age dependent manner in normal human pregnancy. Using the TaqMan®HumanABCTransporter Array, we assessed themRNAexpression of all 50ABCtransporters in first (first trimester, n = 8) and third trimester (term, n = 12) human placentae and validated the resulting expression of selectedABCtransporters usingqPCR, Western blot and immunohistochemistry. A distinct gene expression profile of 30ABCtransporters was observed comparing first trimestervs. term placentae. Using individualqPCRin selected genes, we validated the increased expression ofABCA1(P < 0.01),ABCA6(P < 0.001),ABCA9(P < 0.001) andABCC3(P < 0.001), as well as the decreased expression ofABCB11(P < 0.001) andABCG4(P < 0.01) with advancing gestation. One important lipid transporter,ABCA6, was selected to correlate protein abundance and characterize tissue localization.ABCA6 exhibited increased protein expression towards term and was predominantly localized to syncytiotrophoblast cells. In conclusion, expression patterns of placentalABCtransporters change as a function of gestational age. These changes are likely fundamental to a healthy pregnancy given the critical role that these transporters play in the regulation of steroidogenesis, immunological responses, and placental barrier function and integrity.
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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".