Tissue Inhibitor of Metalloproteinase (TIMP)-2 Acts Synergistically with Synthetic Matrix Metalloproteinase (MMP) Inhibitors but Not with TIMP-4 to Enhance the (Membrane Type 1)-MMP-dependent Activation of Pro-MMP-2
Bibliographic record
Abstract
The membrane-type 1 matrix metalloproteinase (MT1-MMP) has been shown to be a key enzyme in tumor angiogenesis and metastasis. MT1-MMP hydrolyzes a variety of extracellular matrix components and is a physiological activator of pro-MMP-2, another MMP involved in malignancy. Pro-MMP-2 activation by MT1-MMP involves the formation of an MT1-MMP.tissue inhibitors of metalloproteinases 2 (TIMP-2). pro-MMP-2 complex on the cell surface that promotes the hydrolysis of pro-MMP-2 by a neighboring TIMP-2-free MT1-MMP. The MT1-MMP. TIMP-2 complex also serves to reduce the intermolecular autocatalytic turnover of MT1-MMP, resulting in accumulation of active MT1-MMP (57 kDa) on the cell surface. Evidence shown here in Timp2-null cells demonstrates that pro-MMP-2 activation by MT1-MMP requires TIMP-2. In contrast, a C-terminally deleted TIMP-2 (Delta-TIMP-2), unable to form ternary complex, had no effect. However, Delta-TIMP-2 and certain synthetic MMP inhibitors, which inhibit MT1-MMP autocatalysis, can act synergistically with TIMP-2 in the promotion of pro-MMP-2 activation by MT1-MMP. In contrast, TIMP-4, an efficient MT1-MMP inhibitor, had no synergistic effect. These studies suggest that under certain conditions the pericellular activity of MT1-MMP in the presence of TIMP-2 can be modulated by synthetic and natural (TIMP-4) MMP inhibitors.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".