TGF-β1 Regulation of Multidrug Resistance P-glycoprotein in the Developing Male Blood-Brain Barrier
Bibliographic record
Abstract
P-glycoprotein (P-gp), an efflux transporter encoded by the abcb1 gene, protects the developing fetal brain. Levels of P-gp in endothelial cells of the blood-brain barrier (BBB) increase dramatically during the period of peak brain growth. This is coincident with increased release of TGF-β1 by astrocytes and neurons. Although TGF-β1 has been shown to modulate P-gp activity in a number of cell types, little is known about how TGF-β1 regulates brain protection. In the present study, we hypothesized that TGF-β1 increases abcb1 expression and P-gp activity in fetal and postnatal BBB in an age-dependent manner. We found TGF-β1 to potently regulate abcb1 mRNA and P-gp function. TGF-β1 increased P-gp function in brain endothelial cells (BECs) derived from fetal and postnatal male guinea pigs. These effects were more pronounced earlier in gestation when compared with BECs derived postnatally. To investigate the signaling pathways involved, BECs derived at gestational day 50 and postnatal day 14 were exposed to ALK1 and ALK5 inhibitors and agonists. Through inhibition of ALK5, we demonstrated that ALK5 is required for the TGF-β1 effects on P-gp function. Activation of ALK1, by the agonist BMP-9, produced similar results to TGF-β1 on P-gp function. However, TGF-β1 signaling through the ALK1 pathway is age-dependent as dorsomorphin, an ALK1 inhibitor, attenuated TGF-β1-mediated effects in BECs derived at postnatal day 14 but not in those derived at gestational day 50. In conclusion, TGF-β1 regulates P-gp at the fetal and neonatal BBB and both ALK5 and ALK1 pathways are implicated in the regulation of P-gp function. Aberrations in TGF-β1 levels at the developing BBB may lead to substantial changes in fetal brain exposure to P-gp substrates, triggering consequences for brain 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 | 0.000 | 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".