Identification, regulation and role of tissue inhibitor of metalloproteinases‐4 (TIMP‐4) in human platelets
Bibliographic record
Abstract
1. Matrix metalloproteinase-2 (MMP-2) released during activation of human platelets by aggregating agents and cancer cells is known to stimulate platelet aggregation. 2. The expression, activity and role of tissue inhibitors of metalloproteinases (TIMPs), natural inhibitors of MMPs, in isolated human platelets were investigated. 3. Western blot, reverse zymography, immunogold electron microscopy, aggregometry (collagen-, thrombin and HT-1080 human fibrosarcoma cells-induced aggregation), flow cytometry and the release of (14)C-serotonin from labelled platelets recruited to the aggregate were used to characterize the presence and function of platelet TIMPs. 4. TIMP-4 (23 kDa) has been identified as the major MMP inhibitor (12-16 ng per 10(8) platelets) in human platelets. Platelets expressed lower (<1 ng per 10(8) platelets) amounts of TIMP-1. No other TIMPs were detected using Western blot analysis. 5. TIMP-4 co-localized with MMP-2 in resting platelets and was released upon platelet aggregation induced by collagen and thrombin. 6. Collagen resulted also in the release of higher molecular weight (60 kDa) complexes of TIMP-4. 7. The release of TIMP-4 was reduced by prostacyclin and S-nitroso-glutathione (GSNO), an NO donor. 8. Human recombinant TIMP-4 (rTIMP-4), but not human rTIMP-1, inhibited partially both platelet aggregation and recruitment. 9. The recombinant TIMP-4 potentiated the recruitment inhibitor effects of GSNO. 10. TIMP-4 was not released during platelet aggregation induced by HT-1080 cells. 11. Human rTIMP-4 exerted a biphasic effect on HT-1080 cells-induced aggregation. 12. Thus, TIMP-4 is the major intraplatelet MMP inhibitor and it is involved in regulation of platelet aggregation and recruitment.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".