Gene Expression Profiling of Acute Liver Stress During Living Donor Liver Transplantation
Bibliographic record
Abstract
During liver transplantation, the donor graft is subjected to a number of acute stresses whose molecular basis is not well-understood. The effects of surgical stress, preservation and reperfusion injury were studied in 24 consecutive living donor liver transplant (LDLT) operations. Liver biopsies were taken early in the donor operation (OPENING), after transection of the donor liver (PRECLAMP) and following implantation of the graft (post hepatic artery, [PHA]); these were evaluated for histology, tissue glutathione content and gene expression using a 19K-human cDNA microarray. LDLT was associated with an ischemia/reperfusion injury, with accumulation of small numbers of neutrophils and decreased glutathione in the PHA biopsies. Following reperfusion, the expression of 129 genes increased and 106 genes decreased when compared to OPENING levels (> or <2-fold, p < 0.01). By real-time PCR a subset of 25 genes was verified (15 increased, 10 decreased). These genes were similarly altered in another condition of acute liver stress (the response to brain-death), but not in three chronic liver disease states (HCV, HBV and PBC). This study has identified a set of genes whose expression is altered in acute, but not chronic, liver stress, likely to play a central role in the pathogenesis of acute liver injury of liver 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".