Breast Cancer-Resistance Protein (BCRP1) in the Fetal Mouse Brain: Development and Glucocorticoid Regulation
Bibliographic record
Abstract
Breast cancer-resistance protein (BCRP1), encoded by Abcg2 mRNA, limits the penetration of a spectrum of compounds into the brain. The fetal brain is a primary target for many BCRP1 substrates; however, the developmental expression, function, and regulation of Abcg2/BCRP1 in the mouse fetal brain are unknown. Synthetic glucocorticoids (e.g., dexamethasone [DEX]) increase Abcg2/BCRP1 expression and function in vitro in endothelial cells derived from brain microvessels. A regulatory role of glucocorticoids on Abcg2/BCRP1 in the fetal brain is of importance given that approximately 10% of pregnant women are treated with synthetic glucocorticoid for threatened preterm labor. We hypothesized the following: 1) Abcg2 mRNA and BCRP1 protein expression increases with development (from Embryonic Day [E] 15.5 to E18.5), corresponding to decreased accumulation of BCRP1 substrate in the fetal brain. 2) Maternal treatment with DEX will up-regulate Abcg2 mRNA and BCRP1 protein expression in the fetal brain, resulting in decreased BCRP1 substrate accumulation. Pregnant FVB dams were euthanized on E15.5 or E18.5, and fetal brains were collected and analyzed for [(3)H]mitoxantrone (BCRP1-specific substrate) accumulation and Abcg2/BCRP1 expression. In another six groups (n = 4-5/group), pregnant mice were treated with DEX (0.1 or 1 mg/kg) or vehicle (saline) from either E9.5 to E15.5 (midgestation) or E12.5 to E18.5 (late gestation) and then injected with [(3)H]mitoxantrone. In conclusion, Abcg2 mRNA expression significantly decreases with advancing gestation, while BCRP1-mediated neuroprotection increases. Furthermore, there is a dose-, sex-, and age-dependent effect of DEX on Abcg2 mRNA in the fetal brain in vivo, indicating a complex regulatory role of glucocorticoid during 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".