Modulation of Wnt/β-catenin signaling promotes blood-brain barrier phenotype in cultured brain endothelial cells
Bibliographic record
Abstract
Wnt/β-catenin signaling is important for blood-brain barrier (BBB) development and is implicated in BBB breakdown under various pathophysiological conditions. In the present study, a comprehensive characterization of the relevant genes, transport and permeability processes influenced by both the autocrine and external activation of Wnt signaling in human brain endothelial cells was examined using hCMEC/D3 culture model. The hCMEC/D3 expressed a full complement of Wnt ligands and receptors. Preventing Wnt ligand release from hCMEC/D3 produced minimal changes in brain endothelial function, while inhibition of intrinsic/autocrine Wnt/β-catenin activity through blocking β-catenin binding to Wnt transcription factor caused more modest changes. In contrast, activation of Wnt signaling using exogenous Wnt ligand (Wnt3a) or LiCl (GSK3 inhibitor) improved the BBB phenotypes of the hCMEC/D3 culture model, resulting in reduced paracellular permeability, and increased P-glycoprotein (P-gp) and breast cancer resistance associated protein (BCRP) efflux transporter activity. Further, Wnt3a reduced plasmalemma vesicle associated protein (PLVAP) and vesicular transport activity in hCMEC/D3. Our data suggest that this in vitro model of the BBB has a more robust response to exogenous activation of Wnt/β-catenin signaling compared to autocrine activation, suggesting that BBB regulation may be more dependent on external activation of Wnt signaling within the brain microvasculature.
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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) | 0.001 | 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".