Identification of human thrombin-activatable fibrinolysis inhibitor in vascular and inflammatory cells
Bibliographic record
Abstract
TAFI (thrombin-activatable fibrinolysis inhibitor) is a carboxypeptidase zymogen originally identified in plasma. The TAFI pathway helps to regulate the balance between the coagulation and fibrinolytic cascades. Activated TAFI (TAFIa) can also inactivate certain pro-inflammatory mediators, suggesting that the TAFI pathway may also regulate communication between coagulation and inflammation. Expression in the liver is considered to be the source of plasma TAFI. TAFI has also been identified in platelets and CPB2 (the gene encoding TAFI) mRNA has been detected in megakaryocytic cell lines as well as in endothelial cells. We have undertaken a quantitative analysis of CPB2 mRNA and TAFI protein in extrahepatic cell types relevant to vascular disease. Using RT-PCR and quantitative RT-PCR, we detected CPB2 mRNA in the human megakaryoblastic cell lines MEG-01 and Dami, the human monocytoid cell line THP-1 as well as THP-1 cells differentiated into a macrophage-like phenotype, and in primary human umbilical vein and coronary artery endothelial cells. CPB2 mRNA abundance in MEG-01, Dami, and THP-1 cells was modulated by the state of differentiation of these cells. Using a recently developed TAFIa assay, we detected TAFI protein in the lysates of the human hepatocellular carcinoma cell line HepG2 as well as in MEG-01 and Dami cells and in the conditioned medium of HepG2 cells, differentiated Dami cells, and THP-1 macrophages. We have obtained clear evidence for extrahepatic expression of TAFI, which has clear implications for the physiological and pathophysiological functions of the TAFI pathway.
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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 | 0.000 | 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".