Chill injury in human kidney tubule cells after subzero storage is not mitigated by antifreeze protein addition
Bibliographic record
Abstract
Abstract By preventing freezing, antifreeze proteins (AFPs) can permit cells and organs to be stored at subzero temperatures. As metabolic rates decrease with decreasing temperature, subzero static cold storage (SCS) could provide more time for tissue matching and potentially lead to fewer discarded organs. Human kidneys are generally stored for under 24 h and the tubule epithelium is known to be particularly sensitive to SCS. Here, telomerase-immortalized proximal-tubule epithelial cells from humans, which closely resemble their progenitors, were used as a proxy to assess the potential benefit of subzero SCS for kidneys. The effects of hyperactive AFPs from a beetle and Cryostasis Storage Solution were compared to University of Wisconsin Solution at standard SCS temperatures (4 °C) and at −6 °C for up to six days. Although the AFPs helped guard against freezing, lower storage temperatures under these conditions were not beneficial. Compared to cells at 4 °C, those stored at −6 °C showed decreased viability as well as increased lactate dehydrogenase release and apoptosis. This suggests that this kidney cell type might be prone to chilling injury and that the addition of AFPs to enable subzero storage may not be effective for increasing storage times.
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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 | 0.000 |
| 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) | 0.002 | 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".