Evaluating the Effects of Kidney Preservation at 10 °C with Hemopure and Sodium Thiosulfate in a Rat Model of Syngeneic Orthotopic Kidney Transplantation
Bibliographic record
Abstract
Kidney transplantation is preferred for end-stage renal disease. The current gold standard for kidney preservation is static cold storage (SCS) at 4 °C. However, SCS contributes to renal graft damage through ischemia–reperfusion injury (IRI). We previously reported renal graft protection after SCS with a hydrogen sulfide donor, sodium thiosulfate (STS), at 4 °C. Therefore, this study aims to investigate whether SCS at 10 °C with STS and Hemopure (blood substitute), will provide similar protection. Using in vitro model of IRI, we subjected rat renal proximal tubular epithelial cells to hypoxia–reoxygenation for 24 h at 10 °C with or without STS and measured cell viability. In vivo, we preserved 36 donor kidneys of Lewis rats for 24 h in a preservation solution at 10 °C supplemented with STS, Hemopure, or both followed by transplantation. Tissue damage and recipient graft function parameters, including serum creatinine, blood urea nitrogen, urine osmolality, and glomerular filtration rate (GFR), were evaluated. STS-treated proximal tubular epithelial cells exhibited enhanced viability at 10 °C compared with untreated control cells (p < 0.05). Also, STS and Hemopure improved renal graft function compared with control grafts (p < 0.05) in the early time period after the transplant, but long-term function did not reach significance. Overall, renal graft preservation at 10 °C with STS and Hemopure supplementation has the potential to enhance graft function and reduce kidney damage, suggesting a novel approach to reducing IRI and post-transplant complications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".