Q-FISH Measurement of Hepatocyte Telomere Lengths in Donor Liver and Graft after Pediatric Living-Donor Liver Transplantation: Donor Age Affects Telomere Length Sustainability
Bibliographic record
Abstract
Along with the increasing need for living-donor liver transplantation (LDLT), the issue of organ shortage has become a serious problem. Therefore, the use of organs from elderly donors has been increasing. While the short-term results of LDLT have greatly improved, problems affecting the long-term outcome of transplant patients remain unsolved. Furthermore, since contradictory data have been reported with regard to the relationship between donor age and LT/LDLT outcome, the question of whether the use of elderly donors influences the long-term outcome of a graft after LT/LDLT remains unsettled. To address whether hepatocyte telomere length reflects the outcome of LDLT, we analyzed the telomere lengths of hepatocytes in informative biopsy samples from 12 paired donors and recipients (grafts) of pediatric LDLT more than 5 years after adult-to-child LDLT because of primary biliary atresia, using quantitative fluorescence in situ hybridization (Q-FISH). The telomere lengths in the paired samples showed a robust relationship between the donor and grafted hepatocytes (r = 0.765, p = 0.0038), demonstrating the feasibility of our Q-FISH method for cell-specific evaluation. While 8 pairs showed no significant difference between the telomere lengths for the donor and the recipient, the other 4 pairs showed significantly shorter telomeres in the recipient than in the donor. Multiple regression analysis revealed that the donors in the latter group were older than those in the former (p = 0.001). Despite the small number of subjects, this pilot study indicates that donor age is a crucial factor affecting telomere length sustainability in hepatocytes after pediatric LDLT, and that the telomeres in grafted livers may be elongated somewhat longer when the grafts are immunologically well controlled.
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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) | 0.000 | 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) | 0.001 | 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".