The Role of Matrix Metalloproteinase Inhibitors in Ischemia-Reperfusion Injury in the Liver
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Liver ischemia-reperfusion injury is characterized by cell necrosis and apoptosis and by profound modifications in the extracellular matrix (ECM). During the complex series of events that take place both during ischemia and when normal blood flow is restored (reperfusion), a concerted regulation of release and activation of matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) mainly by stellate cells, Kupffer cells and inflammatory cells leads first to endothelial cell injury and subsequent infiltration of neutrophils into the wounded area. Later, MMP activation causes degradation of extracellular matrix components of the liver, mainly collagen and fibronectin, altering tissue architecture. The fibrosis that can result after liver injury is also dependent on the imbalance between MMPs and TIMPs and to new collagen deposition. Several experimental models of liver ischemia-reperfusion injury have demonstrated protective effects of MMP inhibitors in terms of cell necrosis, apoptosis and rearrangement of the extracellular matrix. This review summarizes current knowledge of MMP biology, with particular attention to the most recent evidence of novel, non-extracellular matrix MMP substrates involved in inflammation and cell cycle regulation. An overview of MMP and TIMP expression and activation in hepatic ischemia-reperfusion injury is provided. The analysis of such provides a rational basis for MMP inhibition as a viable strategy to prevent liver injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it