Negative impact of tissue inhibitor of metalloproteinase-3 null mutation on lung structure and function in response to sepsis
Bibliographic record
Abstract
Matrix metalloproteinases (MMPs) are degradative enzymes, which act to remodel tissue. Their activity is regulated by the tissue inhibitors of metalloproteinases (TIMPs). An imbalance in the degradation/inhibition activities has been associated with many diseases, including sepsis. We have previously shown that TIMP-3 knockout animals develop spontaneous, progressive air space enlargement. The objectives of this study were to determine the effects of a septic lung stress induced by cecal ligation and perforation (CLP) on lung function, structure, pulmonary surfactant, and inflammation in TIMP-3 null mice. Knockout and wild-type animals were randomized to either sham or CLP surgery, allowed to recover for 6 h, and then euthanized. TIMP-3 null animals exposed to sham surgery had a significant increase in lung compliance when compared with sham wild-type mice. Additionally, the TIMP-3 knockout mice showed a significant increase in compliance following CLP. Rapid compliance changes were accompanied by significantly decreased collagen and fibronectin levels and increased gelatinase (MMP-2 and -9) abundance and activation. Additionally, in situ zymography showed increased airway-associated gelatinase activity in the knockout animals enhanced following CLP. In conclusion, exposing TIMP-3 null animals to sepsis rapidly enhances the phenotypic abnormalities of these mice, due to increased MMP activity induced by CLP.
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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) | 0.002 | 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".