Autophagy alleviates hypoxia-induced blood-brain barrier injury via regulation of CLDN5 (claudin 5)
Bibliographic record
Abstract
Blood-brain barrier (BBB) disruption is a key event in triggering secondary damage to the central nervous system (CNS) under stroke, and is frequently associated with abnormal macroautophagy/autophagy in brain microvascular endothelial cells (BMECs). However, the underlying mechanism of autophagy in maintaining BBB integrity remains unclear. Here we report that in BMECs of patients suffering stroke, CLDN5 (claudin 5) abnormally aggregates in the cytosol accompanied by autophagy activation. In vivo zebrafish and in vitro cell studies reveal that BBB breakdown is partially caused by CAV1 (caveolin 1)-mediated redistribution of membranous CLDN5 into the cytosol under hypoxia. Meanwhile, autophagy is activated and contributes mainly to the degradation of CAV1 and aggregated CLDN5 in the cytosol of BMECs, therefore alleviating BBB breakdown. Blockage of autophagy by genetic methods or chemicals aggravates cytosolic aggregation of CLDN5, resulting in severer BBB impairment. These data demonstrate that autophagy functions in the protection of BBB integrity by regulating CLDN5 redistribution and provide a potential therapeutic strategy for BBB disorder-related cerebrovascular disease. Abbreviations: BBB: blood-brain barrier; BECN1: beclin 1; BMEC: brain microvascular endothelial cell; CAV1: caveolin 1; CCA: common carotid artery; CLDN5: claudin 5; CNS: central nervous system; CQ: chloroquine; HIF1A: hypoxia inducible factor 1 subunit alpha; MCAO: middle cerebral artery occlusion-reperfusion; OCLN: occludin; ROS: reactive oxygen species; STED: stimulated emission depletion; TEER: trans-endothelial electrical resistance; TEM: transmission electron microscopy; TJ: tight junction; TJP1: tight junction protein 1; UPS: ubiquitin-proteasome system
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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".