Matrix metalloproteinases contribute to endotoxin and interleukin‐1<i>β</i> induced vascular dysfunction
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The acute vascular inflammatory dysfunction associated with endotoxaemia may reflect an imbalance between matrix metalloproteinases (MMPs) and their natural inhibitors (TIMPs), induced by the endotoxin. This possibility was tested in rat aortic tissue. EXPERIMENTAL APPROACHES: Tone induced by phenylephrine in aortic rings was measured after exposure in vitro to ambient lipopolysaccharide (LPS) or the proinflammatory cytokine interleukin-1beta (IL-1beta) for 6h, with or without MMP inhibitors (doxycycline or GM6001). Gelatinase and MMP activities, TIMP proteins and contractility were measured in aortae taken from rats 6h after receiving LPS in vivo. KEY RESULTS: Inhibition of MMP prevented the loss of phenylephrine-induced tone in aortic rings after LPS or IL-1beta. IL-1beta also increased release of MMP-2 activity from aortic tissue. In aortae exposed in vivo to LPS, net gelatinase, MMP-9 activities and TIMP-1 protein levels were increased, whereas TIMP-4 was reduced. These aortae were hypocontractile to both phenylephrine and KCl. Hypocontractility was partially reversed by doxycycline ex vivo. CONCLUSIONS AND IMPLICATIONS: MMP inhibitors ameliorate vascular hyporeactivity induced by either LPS or IL-1beta in vitro. LPS in vivo alters the balance between MMPs and TIMPs, contributing to vascular dysfunction which is partially reversed by MMP inhibitors. Vascular MMPs are activated as a result of LPS or IL-1beta-induced stress and contribute to the hyporeactivity of blood vessels to vasoconstrictors.
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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) | 0.001 | 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".