The Optimization of Renal Graft Preservation Temperature to Mitigate Cold Ischemia-Reperfusion Injury in Kidney Transplantation
Bibliographic record
Abstract
Renal transplantation is the preferred treatment for patients with end-stage renal disease. The current gold standard of kidney preservation for transplantation is static cold storage (SCS) at 4 °C. However, SCS contributes to renal ischemia-reperfusion injury (IRI), a pathological process that negatively impacts graft survival and function. Recent efforts to mitigate cold renal IRI involve preserving renal grafts at higher or subnormothermic temperatures. These temperatures may be beneficial in reducing the risk of cold renal IRI, while also maintaining active biological processes such as increasing the expression of mitochondrial protective metabolites. In this review, we discuss different preservation temperatures for renal transplantation and pharmacological supplementation of kidney preservation solutions with hydrogen sulfide to determine an optimal preservation temperature to mitigate cold renal IRI and enhance renal graft function and recipient survival.
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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 | 0.002 | 0.001 |
| 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) | 0.003 | 0.001 |
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".