Oxidative stress–induced fibrinogen modifications in liver transplant recipients: unraveling a novel potential mechanism for cardiovascular risk
Bibliographic record
Abstract
Background: Cardiovascular events represent a major cause of non-graft-related death after liver transplant. Evidence suggest that chronic inflammation associated with a remarkable oxidative stress in the presence of endothelial dysfunction and procoagulant environment plays a major role in the promotion of thrombosis. However, the underlying molecular mechanisms are not completely understood. Objectives: In order to elucidate the mechanisms of posttransplant thrombosis, the aim of the present study was to investigate the role of oxidation-induced structural and functional fibrinogen modifications in liver transplant recipients. Methods: A case-control study was conducted on 40 clinically stable liver transplant recipients and 40 age-matched, sex-matched, and risk factor-matched controls. Leukocyte reactive oxygen species (ROS) production, lipid peroxidation, glutathione content, plasma antioxidant capacity, fibrinogen oxidation, and fibrinogen structural and functional features were compared between patients and controls. Results: Patients displayed enhanced leukocyte ROS production and an increased plasma lipid peroxidation with a reduced total antioxidant capacity compared with controls. This systemic oxidative stress was associated with fibrinogen oxidation with fibrinogen structural alterations. Thrombin-catalyzed fibrin polymerization and fibrin resistance to plasmin-induced lysis were significantly altered in patients compared with controls. Moreover, steatotic graft and smoking habit were associated with high fibrin degradation rate. Conclusion: ROS-induced fibrinogen structural changes might increase the risk of thrombosis in liver transplant recipients.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".