THE TRANSFORMING GROWTH FACTOR-??1 CODON 10 GENE POLYMORPHISM AND ACCELERATED GRAFT VASCULAR DISEASE AFTER CLINICAL HEART TRANSPLANTATION
Bibliographic record
Abstract
BACKGROUND: The multifunctional cytokine transforming growth factor- (TGF) beta1 is thought to play a role in the pathogenesis of graft vascular disease (GVD). Polymorphisms at codon 10, (Leu10-->Pro) and codon 25 (Arg25-->Pro) in the signal sequence of the TGF-beta1 gene regulate the production and secretion of the protein. We investigated whether these polymorphisms are risk factors for the development of GVD after clinical heart transplantation. METHOD: TGF-beta1 polymorphisms, Leu10-->Pro and Arg25-->Pro, were determined in DNA from heart transplant recipients (n=252) and their donors (n=213), using sequence-specific oligonucleotide probing. GVD was angiographically diagnosed 1 year after transplantation. In addition other potential risk factors including underlying disease, recipient and donor age, recipient and donor gender, number of acute rejections in the first year, cold ischemia time, and HLA mismatches were analyzed by univariate and multivariate logistic regression analysis. RESULTS: Univariate analysis showed that the recipient TGF-beta1 polymorphism Leu10-->Pro, (P=0.056, chi2 test), underlying disease (P=0.01, chi2 test), number of acute rejections in the first-year (P=0.03, analysis of variance), and donor age (P<0.001, analysis of variance) were risk factors for the development of GVD. The TGF-beta1 Arg25-->Pro polymorphism was not a risk factor. Also in the multivariate analysis, the recipient TGF-beta1 codon 10 polymorphism was associated with GVD, with patients homozygous for Pro at greatest risk (odds ratio 7.7, P=0.03). Apart for the recipient TGF-beta1 Leu10-->Pro polymorphism, donor age appeared to be an independent risk factor for the development of GVD at 1 year. Patients with older donor hearts were at greater risk than patients receiving grafts from younger donors (odds ratio 1.1/year, P<0.001). CONCLUSION: Recipient TGF-beta1 Leu10-->Pro polymorphism and higher donor age are independent risk factors for the development of GVD after clinical heart transplantation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".