Cold Preservation with a Hyperbranched Polyglycerol-Based Solution Improves Functional Recovery of Kidney Transplants in a Pig Model
Bibliographic record
Abstract
Background Organ preservation solutions are used to limit donor organ injury during cold preservation (perfusion and storage) in organ transplantation, and hyperbranched polyglycerol (HPG) is a promising colloid for the solutions to improve donor organ protection. This study was to evaluate the outcomes of kidney transplants after cold preservation with a HPG-based organ preservation solution in a human-like model Materials and Methods The orthotopic kidney autotransplantation was performed in farm pigs (Sus scrofa domesticus, weighing 35–45 kg) under general anesthesia. The left kidney was perfused with and stored in either cold HPG-based organ preservation solution or cold UW solution, followed by autologous transplantation to the right side after right nephrectomy. The survival and function of transplanted kidneys were determined by using their primary outcome-urine production. Results The cold ischemia time in both groups (HPG versus UW) was similar (both median 7.625 hours, P = 0.9376, t-test, n=6). Within 7 days after transplantation, the survival of transplanted kidneys between these two groups was not significantly different (P = 0.09193, Log-rank test). The urine output from the first day post-transplantation in HPG group was 1593.33 ± 887.39 mL, which was significantly higher than 310.83 ± 419.48 mL in UW group (P = 0.0095, t-test, n = 6), and this difference was consistent when the urine production between the HPG and the UW groups was compared during the entire period of 7 days (P = 0.0002, two-way ANOVA, n = 6). Conclusion Our preliminary data show that as compared to the UW solution, the cold preservation of donor kidneys with the HPG solution has less negative impact on the immediate functional recovery of kidney transplants after transplantation in the pig model, which may suggest that the HPG solution likely improve donor kidney preservation, resulting in better outcomes for kidney transplants. This study was funded by the Canadian Institutes of Health Research and the Natural Sciences and Engineering Research Council of Canada. Dr. Shadan Li received scholarship from the China Scholarship Council and funding support from General Hospital of Chengdu Military Command (Grant No.: 2016KC28), Science and Technology Department of Sichuan Province (Grant No.: 2017HH0073) and the Center of Donation After Cardiac Death, Center of Medical Science of Chengdu Military Command.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".