Kidney preservation at subzero temperatures using a novel storage solution and insect ice-binding proteins.
Bibliographic record
Abstract
BACKGROUND: Contemporary kidney preservation methods involve storing at 4 degree C up to 24 h prior to transplantation. By decreasing the storage temperature to below 0 degree C, we hypothesized that the safe storage time could be significantly lengthened. OBJECTIVE: The efficacy of a proprietary CryoStasis (CrS) storage solution for the subzero preservation of kidneys was tested, with or without addition of a hyperactive insect antifreeze protein (TmAFP). MATERIALS AND METHODS: Rat kidneys were stored in either University of Wisconsin (UW) solution (4 degree C, 24 h), CrS (-2 degree C, 48 h), or CrS with 61.5 µM TmAFP (-4.4 degree C, 72 h). Following storage, viability was assessed with MTT reduction assays and live vs. dead cell (FDA/PI) staining. Markers of ischemic damage were analyzed using fluormetric substrates for caspase-3 and calpain activity. RESULTS: Kidneys stored in CrS for 48 h and CrS with TmAFP for 72 h displayed similar levels of enzymatic activity compared to 24 h UW controls. CONCLUSION: This methodology shows promise to prolong the safe storage time of kidneys and offers the potential of increased organ availability for renal transplants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".