Retinoic Acid Induces Blood–Brain Barrier Development
Bibliographic record
Abstract
The blood-brain barrier (BBB) is crucial in the maintenance of a controlled environment within the brain to safeguard optimal neuronal function. The endothelial cells (ECs) of the BBB possess specific properties that restrict the entry of cells and metabolites into the CNS. The specialized BBB endothelial phenotype is induced during neurovascular development by surrounding cells of the CNS. However, the molecular differentiation of the BBB endothelium remains poorly understood. Retinoic acid (RA) plays a crucial role in the brain during embryogenesis. Because radial glial cells supply the brain with RA during the developmental cascade and associate closely with the developing vasculature, we hypothesize that RA is important for the induction of BBB properties in brain ECs. Analysis of human postmortem fetal brain tissue shows that the enzyme mainly responsible for RA synthesis, retinaldehyde dehydrogenase, is expressed by radial glial cells. In addition, the most important receptor for RA-driven signaling in the CNS, RA-receptor β (RARβ), is markedly expressed by the developing brain vasculature. Our findings have been further corroborated by in vitro experiments showing RA- and RARβ-dependent induction of different aspects of the brain EC barrier. Finally, pharmacologic inhibition of RAR activation during the differentiation of the murine BBB resulted in the leakage of a fluorescent tracer as well as serum proteins into the developing brain and reduced the expression levels of important BBB determinants. Together, our results point to an important role for RA in the induction of the BBB during human and mouse 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 | 0.001 | 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 | 0.001 |
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".