Serpins, New Therapeutic Targets for Hemophilia
Bibliographic record
Abstract
Hemostasis is a tightly regulated process characterized by a finely tuned balance between procoagulant and anticoagulant systems. Among inherited hemostatic conditions, hemophilia is one of the most well-known bleeding disorders. Hemophilia A (HA) and B (HB) are due to deficiencies in coagulation factor VIII (FVIII) or FIX, respectively, leading to unwanted bleeding. Until recently, hemophilia treatment has consisted of prophylactic replacement therapy using plasma-derived or recombinant FVIII in cases of HA or FIX in cases of HB. Because FVIII and FIX deficiencies lead to an imbalance between procoagulant and anticoagulant systems, a recent upcoming strategy implies blocking of endogenous anticoagulant proteins to compensate for the procoagulant factor deficit, thus restoring hemostatic equilibrium. Important physiological proteins of the anticoagulant pathways belong to the serpin (serine protease inhibitor) family and, recently, different experimental and clinical studies have demonstrated that targeting natural serpins could decrease bleeding in hemophilia. Here, we aim to review the different, recent studies demonstrating that blocking serpins such as antithrombin, protein Z-dependent protease inhibitor, and protease nexin-1 or modifying a serpin like α1-antitrypsin could rebalance coagulation in hemophilia. Furthermore, we underline the potential therapeutic use of serpins for the treatment of hemophilia.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".