The mRNA encoding TAFI is alternatively spliced in different cell types and produces intracellular forms of the protein lacking TAFIa activity
Bibliographic record
Abstract
TAFI (thrombin-activatable fibrinolysis inhibitor) is a pro-carboxypeptidase, encoded by the CPB2 gene in humans that links the coagulation cascade to fibrinolysis and inflammation. The liver is the main source for plasma TAFI, and TAFI expression has been documented in platelets and monocyte-derived macrophages. A recent study reported an alternatively spliced CPB2 mRNA variant lacking exon 7 (∆7) in HepG2 cells and liver. Another study identified a CPB2 mRNA variant lacking exon 7 and a 52 bp deletion in exon 11 (∆7+11) in human hippocampus. We have examined alternative splicing of CPB2 mRNA in various cell types by RT-PCR and have assessed the functional properties of TAFI variants encoded by these transcripts by recombinant expression in mammalian cells. We identified the Δ7 exon skipping event in liver, Dami megakaryoblasts, THP-1-derived macrophages, peripheral blood mononuclear cells, platelets, testis, cerebellum, and SH-SY5Y neuroblastoma cells. The Δ11 alternative splicing event was notably absent in liver cells. We also detected a novel exon Δ7+8 skipping event in liver and megakaryocytes. Of note, we detected non-alternatively spliced CPB2 transcripts in brain tissues, suggesting the expression of full-length TAFI in brain. Experiments using cultured mammalian cells transfected with wild-type CPB2-, ∆7-, ∆7+11-, and ∆11-cDNA revealed that alternatively spliced TAFI is stored inside the cells, cannot be activated by thrombin-thrombomodulin, and does not have TAFIa activity. The alternative splicing events clearly do not give rise to a secreted protein with basic carboxypeptidase activity, but the intracellular forms may possess novel functions related to intracellular proteolysis.
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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) | 0.001 | 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".