Characterizing coagulation responses in humans and nonhuman primates following kidney xenotransplantation—A narrative review
Bibliographic record
Abstract
The recent report of the first pig kidney transplant in a living human brings hope to thousands of people with end-stage kidney failure. The scientific community views this early success with caution as kidney xenotransplantation exhibits many challenges and barriers. One of these is coagulation dysregulation. This includes (i) pig von Willebrand Factor (vWF) interaction with human platelets, which can induce abnormal clotting responses, heightening the risk of graft failure, (ii) the inefficiency of pig thrombomodulin in activating human protein C, which emphasizes the species-specific variations that aggravate coagulation challenges, and (iii) the development of thrombotic microangiopathy in the pig grafts and the occurrence of systemic consumptive coagulopathy in the recipients. Indeed, coagulation dysregulation largely results from differences in endothelial cell response and incompatibilities between pig and human coagulation-anticoagulation pathways. These barriers can be resolved by modifications to pig vWF and the expression of human thrombomodulin and endothelial protein C receptors in pig cells, serving as strategic interventions to align the coagulation systems of the two species more closely. These coagulation challenges have clinical implications in how they affect graft survival and patient outcome. Genetic engineering of the organ-source pig and the administration of various drugs have assisted in correcting this coagulation dysregulation. Hence, comprehending and controlling coagulation dysregulation is crucial for progress in xenotransplantation as a viable option for treating patients with terminal kidney disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".