Differential response of TIMP-3 null mice to the lung insults of sepsis, mechanical ventilation, and hyperoxia
Bibliographic record
Abstract
An imbalance in matrix metalloproteinases (MMPs) and the tissue inhibitors of metalloproteinases (TIMPs) leads to excessive or insufficient tissue breakdown, which is associated with many disease processes. The TIMP-3 null mouse is a model of MMP/TIMP imbalance, which develops air space enlargement and decreased lung function. These mice responded differently to cecal ligation and perforation (CLP)-induced septic lung injury than wild-type controls. The current study addresses whether the TIMP-3 knockout lung is susceptible to different types of insults or only those involving sepsis, by examining its response to lipopolysaccharide (LPS)-induced sepsis, mechanical ventilation (MV), and hyperoxia. TIMP-3 null noninjured controls of each insult consistently demonstrated significantly higher compliance vs. wild-type mice. Null mice treated with LPS had a further significantly increased compliance compared with untreated controls. Conversely, MV and hyperoxia did not alter compliance in the null lung. MMP abundance and activity increased in response to LPS but were generally unaltered following MV or hyperoxia, correlating with compliance alterations. All three insults produced inflammatory cytokines; however, the response of the null vs. wild-type lung was dependent on the type of insult. Overall, this study demonstrated that 1) LPS-induced sepsis produced a similar response in null mice to CLP-induced sepsis, 2) the null lung responded differently to various insults, and 3) the null susceptibility to compliance changes correlated with increased MMPs. In conclusion, this study provides insight into the role of TIMP-3 in response to various lung insults, specifically its importance in regulating MMPs to maintain compliance during a sepsis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".