Kidney Storage at Subzero Temperature Is Safe for Porcine Auto-Trans-plantation: A World First In Vivo Study
Bibliographic record
Abstract
Background: Static cold storage (SCS) at 4°C remains the method of choice for kidney preservation prior to transplantation, but the rapid decline of graft quality at 4°C limits prolonged SCS and graft exchange over larger distances. Kidney storage below 0°C could prolong graft viability and offer new opportunities for kidney graft exchange over larger distances, or controlled scheduling of kidney transplant. The aim of this study was to determine the feasibility of sub-zero storage followed by auto-transplantation of porcine kidneys. Methods: Kidneys were retrieved from Yorkshire pigs and either stored at 4°C for five hours (n=4) or flushed and stored using a novel preservation solution (CrS SC 0.3 EQ, Cryostasis Inc®) at -2°C (n=4). After storage, kidneys were auto-transplanted. Results: All kidneys were successfully transplanted and immediately produced urine. Results were compared between the two groups, and assesed using T-test or ANOVA. Creatinine values at days 1, 3 and 7 for the -2°C and 4°C groups were 3.07 vs. 3.05 mg/dL, 3.28 vs. 2.84 mg/dL, and 1.4 vs.1.54 mg/dL, respectively (p>0.05). 24-hour urine output was 1700 ml (562.5 - 3250 ml) vs. 1700 ml (1450- 2650 ml) for -2°C and 4°C groups. Lactate values at 1, 3 and 7 days were 0.9 vs. 1.1, 0.75 vs. 0.56, and 0.95 vs. 0.88 mmol/L (p= 0.34). AST levels at 1, 3 and 7 days were: 152.3 vs.101.6, 33.3 vs. 27.8 and 25 vs. 22.8 U/L (p>0.05). Potassium levels were 4.8 vs. 4.2, 4.3 vs. 3.8 and 4.2 vs. 4.4 mmol/L at days 1, 3 and 7 (p=0.05). Conclusions: Sub-zero short storage of porcine kidneys is feasible and results are comparable to ideal heartbeating-donor kidneys briefly stored at 4 °C. Histological, celular and molecular analyses are underway to better understand sub-zero protective mechanisms, and its extents will be further studied by prolonging storage times. Funding: Commercial Support - Cryostasis Incorporated
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".