Hypoxia‐induced matrix metalloproteinase‐13 expression in astrocytes enhances permeability of brain endothelial cells
Bibliographic record
Abstract
Matrix metalloproteinase-13 (MMP-13) is involved in the degradation of extracellular matrix in many kinds of tissues. Here we found that hypoxia increased MMP-13 protein and mRNA levels in primary rat astrocyte cultures. Hypoxia stimulation also increased the secretion of MMP-13 from astrocytes, as shown by zymographic analysis. In addition, exposure to hypoxia up-regulated the expression of c-Fos and c-Jun time-dependently. Hypoxia-induced MMP-13 overexpression was antagonized by transfection with antisense oligodeoxynucleotides (AS-ODN) of c-Fos or c-Jun. Furthermore, hypoxic-conditioned medium (Hx-CM) collected from astrocytes exposed to hypoxia increased paracellular permeability of adult rat brain endothelial cells (ARBECs). Administration of MMP-13 neutralizing antibody antagonized Hx-CM-induced paracellular permeability of ARBECs. Furthermore, pre-transfection of astrocytes with AS-ODN of c-Fos, c-Jun or MMP-13-shRNA significantly decreased hyperpermeability of ARBECs induced by Hx-CM. The arrangement of tight junction protein (TJP) zonular occludens-1 (ZO-1) of ARBECs disorganized in response to Hx-CM. Administration of Hx-CM to ARBECs also resulted in the production of proteolytic fragments of ZO-1, which was antagonized by transfection of MMP-13-shRNA in primary astrocytes. Administration of MMP-13 recombinant protein to ARBECs led to the disorganization and fragmentation of ZO-1 protein and also increased paracellular permeability. These results suggest that hypoxia-induced MMP-13 expression in astrocytes is regulated by c-Fos and c-Jun. MMP-13 is an important factor leading to the disorganization of ZO-1 and hyperpermeablility of blood-brain barrier in response to hypoxia.
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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".