A factor XIa-activatable hirudin-albumin fusion protein reduces thrombosis in mice without promoting blood loss
Bibliographic record
Abstract
BACKGROUND: Hirudin is a potent thrombin inhibitor but its antithrombotic properties are offset by bleeding side-effects. Because hirudin's N-terminus must engage thrombin's active site for effective inhibition, fusing a cleavable peptide at this site may improve hirudin's risk/benefit ratio as a therapeutic agent. Previously we engineered a plasmin cleavage site (C) between human serum albumin (HSA) and hirudin variant 3 (HV3) in fusion protein HSACHV3. Because coagulation factor XI (FXI) is more involved in thrombosis than hemostasis, we hypothesized that making HV3 activity FXIa-dependent would also improve HV3's potential therapeutic profile. We combined albumin fusion for half-life extension of hirudin with positioning of an FXIa cleavage site N-terminal to HV3, and assessed in vitro and in vivo properties of this novel protein. RESULTS: FXIa cleavage site EPR was employed. Fusion protein EPR-HV3HSA but not HSAEPR-HV3 was activated by FXIa in vitro. FVIIa, FXa, FXIIa, or plasmin failed to activate EPR-HV3HSA. FXIa-cleavable EPR-HV3HSA reduced the time to occlusion of ferric chloride-treated murine arteries and reduced fibrin deposition in murine endotoxemia; noncleavable mycHV3HSA was without effect. EPR-HV3HSA elicited less blood loss than constitutively active HV3HSA in murine liver laceration or tail transection but extended bleeding time to the same extent. EPR-HV3HSA was partially activated in citrated human or murine plasma to a greater extent than HSACHV3. CONCLUSIONS: Releasing the N-terminal block to HV3 activity using FXIa was an effective way to limit hirudin's bleeding side-effects, but plasma instability of the exposed EPR blocking peptide rendered it less useful than previously described plasmin-activatable HSACHV3.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".