Thrombin Activable Fibrinolysis Inhibitor (TAFI): Molecular Genetics of an Emerging Potential Risk Factor for Thrombotic Disorders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The balance between the activities of the coagulation and fibrinolytic cascades is crucial for normal hemostasis. However, imbalances can lead to pathological thrombotic events, as is observed in heart attacks and strokes, as well as excessive bleeding, as in hemophilia. Recent investigations have uncovered a novel molecular connection between the two cascades that has been termed thrombin-activable fibrinolysis inhibitor (TAFI) as well as procarboxypeptidase U, procarboxypeptidase R or plasma procarboxypeptidase B. TAFI is the precursor of an enzyme (TAFIa) with basic carboxypeptidase activity that attenuates the lysis of fibrin clots by removal of the carboxyl-terminal lysine residues from partially-degraded fibrin that mediate positive feedback in the fibrinolytic cascade. The plasma concentration of TAFI varies substantially (up to approximately 10-fold) in the human population and may constitute a novel risk factor for thrombotic disorders. Sixteen single nucleotide polymorphisms have been identified in the 5'-flanking, protein coding, and 3'-untranslated regions of the TAFI gene. The polymorphisms all have been shown to be associated with variations in plasma TAFI concentrations. One amino acid substitution has been found to directly alter the properties of the TAFIa enzyme. This review provides a general overview of the TAFI pathway, including a discussion of the spectrum of inhibitors of TAFIa that have been described, and summarizes the recent advances in the molecular genetics of the TAFI gene as well as the results of studies that may implicate the TAFI pathway in risk for arterial and venous thrombotic disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it