A review of the immune response stimulated by xenogenic tissue heart valves
Bibliographic record
Abstract
Valvular heart disease continues to afflict millions of people around the world. In many cases, the only corrective treatment for valvular heart disease is valve replacement. Valve replacement options are currently limited, and the most common construct utilized are xenogenic tissue heart valves. The main limitation with the use of this valve type is the development of valvular deterioration. Valve deterioration results in intrinsic permanent changes in the valve structure, often leading to hemodynamic compromise and clinical symptoms of valve re-stenosis. A significant amount of research has been performed regarding the incidence of valve deterioration and determination of significant risk factors for its development. As a result, many believe that the underlying driver of valve deterioration is a chronic immune-mediated rejection process of the foreign xenogenic-derived tissue. The underlying mechanisms of how this occurs are an area of ongoing research and active debate. In this review, we provide an overview of the important components of the immune system and how they respond to xenografts. A review of the proposed mechanisms of xenogenic heart valve deterioration is provided including the immune response to xenografts. Finally, we discuss the role of strategies to combat valve degeneration such as preservation protocols, epitope modification and decellularization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".