Netrin 1 regulates blood–brain barrier function and neuroinflammation
Bibliographic record
Abstract
Blood–brain barrier function is driven by the influence of astrocyte-secreted factors. During neuroinflammatory responses the blood–brain barrier is compromised resulting in central nervous system damage and exacerbated pathology. Here, we identified endothelial netrin 1 induction as a vascular response to astrocyte-derived sonic hedgehog that promotes autocrine barrier properties during homeostasis and increases with inflammation. Netrin 1 supports blood–brain barrier integrity by upregulating endothelial junctional protein expression, while netrin 1 knockout mice display disorganized tight junction protein expression and barrier breakdown. Upon inflammatory conditions, blood–brain barrier endothelial cells significantly upregulated netrin 1 levels in vitro and in situ, which prevented junctional breach and endothelial cell activation. Finally, netrin 1 treatment during experimental autoimmune encephalomyelitis significantly reduced blood–brain barrier disruption and decreased clinical and pathological indices of disease severity. Our results demonstrate that netrin 1 is an important regulator of blood–brain barrier maintenance that protects the central nervous system against inflammatory conditions such as multiple sclerosis and experimental autoimmune encephalomyelitis. Astrocyte-derived Sonic Hedgehog helps to maintain the integrity of the blood-brain barrier, but many of its downstream effectors are unknown. Podjaski et al. show that in multiple sclerosis, Sonic Hedgehog upregulates netrin-1 expression on the CNS vasculature, inducing an autocrine response that reduces blood-brain barrier permeability and dampens neuroinflammation.
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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".