Functional Expression of Multidrug-Resistance (MDR) Transporters in Developing Human Fetal Brain Endothelial Cells
Bibliographic record
Abstract
There is little information about the functional expression of the multidrug resistance (MDR) transporters P-glycoprotein (P-gp, encoded by ABCB1) and breast cancer resistance protein (BCRP/ABCG2) in the developing blood−brain barrier (BBB). We isolated and cultured primary human fetal brain endothelial cells (hfBECs) from early and mid-gestation brains and assessed P-gp/ABCB1 and BCRP/ABCG2 expression and function, as well as tube formation capability. Immunolocalization of the von Willebrand factor (marker of endothelial cells), zonula occludens-1 and claudin-5 (tight junctions) was detected in early and mid-gestation-derived hfBECs, which also formed capillary-like tube structures, confirming their BEC phenotype. P-gp and BCRP immunostaining was detected in capillary-like tubes and in the cytoplasm and nucleus of hfBECs. P-gp protein levels in the plasma membrane and nuclear protein fractions, as well as P-gp protein/ABCB1 mRNA and BCRP protein levels decreased (p < 0.05) in hfBECs, from early to mid-gestation. No differences in P-gp or BCRP activity in hfBECs were observed between the two age groups. The hfBECs from early and mid-gestation express functionally competent P-gp and BCRP drug transporters and may thus contribute to the BBB protective phenotype in the conceptus from early stages of pregnancy.
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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".