A Role for CCAAT/Enhancer-binding Protein in Hepatic Expression of Thrombin-activable Fibrinolysis Inhibitor
Bibliographic record
Abstract
Thrombin-activable fibrinolysis inhibitor (TAFI) is a procarboxypeptidase B-like zymogen that upon activation by thrombin, thrombin-thrombomodulin, or plasmin attenuates fibrin clot lysis by inhibiting positive feedback in the fibrinolytic cascade. The concentration of TAFI in plasma varies in the human population and thus may constitute a risk factor for thrombotic disorders. In addition, TAFI has been reported to be a positive acute phase reactant in mice. We have initiated molecular analysis of the human TAFI promoter to understand the mechanisms underlying regulation of TAFI gene expression. We identified a putative C/EBP-binding site between -53 and -40 of the promoter. Mutations in this site that abolish C/EBP binding decrease TAFI promoter activity in human hepatoma (HepG2) cells by approximately 80%. Gel mobility shift analyses indicated that C/EBP-beta present in HepG2 nuclear extracts and C/EBP-alpha and -beta present in adult rat liver nuclear extracts bind to the C/EBP site. C/EBP-alpha, -beta, and -delta isoforms are all capable of binding to the C/EBP site and activating the TAFI promoter. The identification of a functional C/EBP-binding site in the human TAFI promoter may have important implications for the regulation of expression of this gene during development and in response to inflammatory stimuli.
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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 | 0.001 |
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".