Regulation of MMP-9 gene expression for the development of novel molecular targets against cancer and inflammatory diseases
Bibliographic record
Abstract
The need to pharmacologically control the proteolytic activity of matrix metalloproteinases (MMPs) has been commonly acknowledged, despite its limited efficacy in clinical trials. Among the reasons that explain this failure is our limited understanding of the signals that control the expression of MMPs in different cell types during different pathological conditions. Thus, future therapies must rely on more selective approaches. With the continually increasing body of proof implicating MMPs in a large number of diseases, it has become a priority to establish the pertinence of molecules involved in the signalling pathways leading to the expression of these enzymes. MMP-9 is a case in point: its dramatic overexpression in cancer and various inflammatory conditions clearly points to the molecular mechanisms controlling its expression as a potential target for eventual rational therapeutic intervention. In this article, recent progress in the signalling pathways that regulate MMP-9 expression is reviewed, and the latest strategies to be considered in the search for a specific inhibitor of its expression are presented.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".