Chorioamnionitis Induces a Specific Signature of Placental ABC Transporters Associated with an Increase of miR-331-5p in the Human Preterm Placenta
Bibliographic record
Abstract
BACKGROUND/AIMS: The ATP-binding cassette (ABC) transporters mediate drug biodisposition and immunological responses in the placental barrier. In vitro infective challenges alter expression of specific placental ABC transporters. We hypothesized that chorioamnionitis induces a distinct pattern of ABC transporter expression. METHODS: Gene expression of 50 ABC transporters was assessed using TaqMan® Human ABC Transporter Array, in preterm human placentas without (PTD; n=6) or with histological chorioamnionitis (PTDC; n=6). Validation was performed using qPCR, immunohistochemistry and Western blot. MicroRNAs known to regulate P-glycoprotein (P-gp) were examined by qPCR. RESULTS: Up-regulation of ABCB9, ABCC2 and ABCF2 mRNA was detected in chorioamnionitis (p<0.05), whereas placental ABCB1 (P-gp; p=0.051) and ABCG2 (breast cancer resistance protein-BCRP) mRNA levels (p=0.055) approached near significant up-regulation. In most cases, the magnitude of the effect significantly correlated to the severity of inflammation. Upon validation, increased placental ABCB1 and ABCG2 mRNA levels (p<0.05) were observed. At the level of immunohistochemistry, while BCRP was increased (p<0.05), P-gp staining intensity was significantly decreased (p<0.05) in PTDC. miR-331-5p, involved in P-gp suppression, was upregulated in PTDC (p<0.01) and correlated to the grade of chorioamnionitis (p<0.01). CONCLUSIONS: Alterations in the expression of ABC transporters will likely lead to modified transport of clinically relevant compounds at the inflamed placenta. A better understanding of the potential role of these transporters in the events surrounding PTD may also enable new strategies to be developed for prevention and treatment of PTD.
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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 | 0.001 |
| 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".