Doxorubicin‐induced Activation of Intracellular Matrix Metalloproteinase‐2 by Oxidative Stress
Bibliographic record
Abstract
Matrix metalloproteinase‐2 (MMP‐2) activity is involved in several heart pathologies resulting from increased oxidative stress including ischemia‐reperfusion injury. In addition to its roles in extracellular matrix remodeling, MMP‐2 is also an intracellular protease with specific intracellular substrates. MMP‐2 mRNA and protein levels are elevated in cancer patients treated with doxorubicin (DXR). Though effective in chemotherapy, DXR's dose‐limiting cardiotoxicity may cause heart failure by activating intracellular MMP‐2. Human fibrosarcoma cells (HT1080 cells) and neonatal rat ventricular myocytes (NRVM) were treated with 0.01‐1 μM DXR for 0.5 and 2 h at 37°C. DXR treatment had no effect on cell viability. MMP‐2 activity and protein levels were measured by gelatin zymography and immunoblotting, respectively. Oxidative stress was measured by changes in mitochondrial aconitase activity. To visualize changes in intracellular MMP‐2 activity in real time, we will use a genetically encoded, fluorescence resonance energy transfer (FRET)‐based biosensor. In HT1080 cells 0.1‐1 μM DXR stimulated a 1.6 fold increase in intracellular MMP‐2 activity after 2 h without changing its protein level. DXR had no effect on MMP‐2 activity in NRVM. The FRET‐based MMP‐2 biosensor detected MMP but not other intracellular proteases, such as calpains and caspases, in vitro . In human cancer cells, acute treatment with DXR activates intracellular MMP‐2. The biosensors are now being expressed in cells to directly study intracellular MMP‐2 activity. The FRET‐based biosensor will allow us to better understand how oxidative stress stimuli affects intracellular MMP‐2 activity and its specific substrates.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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 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".