Membrane-type I matrix metalloproteinase (MT1-MMP), lipid metabolism, and therapeutic implications
Bibliographic record
Abstract
Lipids exert many essential physiological functions, such as serving as a structural component of biological membranes, storing energy, and regulating cell signal transduction. Dysregulation of lipid metabolism can lead to dyslipidemia related to various human diseases, such as obesity, diabetes, and cardiovascular disease. Therefore, lipid metabolism is strictly regulated through multiple mechanisms at different levels, including the extracellular matrix. Membrane-type I matrix metalloproteinase (MT1-MMP), a zinc-dependent endopeptidase, proteolytically cleaves extracellular matrix components, and non-matrix proteins, thereby regulating many physiological and pathophysiological processes. Emerging evidence supports the vital role of MT1-MMP in lipid metabolism. For example, MT1-MMP mediates ectodomain shedding of low-density lipoprotein receptor and increases plasma low-density lipoprotein cholesterol levels and the development of atherosclerosis. It also increases the vulnerability of atherosclerotic plaque by promoting collagen cleavage. Furthermore, it can cleave the extracellular matrix of adipocytes, affecting adipogenesis and the development of obesity. Therefore, the activity of MT1-MMP is strictly regulated by multiple mechanisms, such as autocatalytic cleavage, endocytosis and exocytosis, and post-translational modifications. Here, we summarize the latest advances in MT1-MMP, mainly focusing on its role in lipid metabolism, the molecular mechanisms regulating the function and expression of MT1-MMP, and their pharmacotherapeutic implications.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".