A novel redox-active metalloporphyrin reduces reactive oxygen species and inflammatory markers but does not improve marginal mass engraftment in a murine donation after circulatory death islet transplantation model
Bibliographic record
Abstract
Islet transplantation is a highly effective treatment for stabilizing glycemic control for select patients with type-1 diabetes. Despite improvements to clinical transplantation, single-donor transplant success has been hard to achieve routinely, necessitating increasing demands on viable organ availability. Donation after circulatory death (DCD) may be an alternative option to increase organ availability however, these organs tend to be more compromised. The use of metalloporphyrin anti-inflammatory and antioxidant (MnP) compounds previously demonstrated improved in vivo islet function in preclinical islet transplantation. However, the administration of MnP (BMX-001) in a DCD islet isolation and transplantation model has yet to be established. In this study, murine donors were subjected to a 15-min warm ischemic (WI) period prior to isolation and culture with or without MnP. Subsequent to one-hour culture, islets were assessed for in vitro viability and in vivo function. A 15-minute WI period significantly reduced islet yield, regardless of MnP-treatment relative to yields from standard isolation. MnP-treated islets did not improve islet viability compared to DCD islets alone. MnP-treatment did significantly reduce the presence of extracellular reactive oxygen species (ROS) (p < 0 .05). Marginal, syngeneic islets (200 islets) transplanted under the renal capsule exhibited similar in vivo outcomes regardless of WI or MnP-treatment. DCD islet grafts harvested 7 d post-transplant exhibited sustained TNF-α and IL-10, while MnP-treated islet-bearing grafts demonstrated reduced IL-10 levels. Taken together, 15-minute WI in murine islet isolation significantly impairs islet yield. DCD islets do indeed demonstrate in vivo function, though MnP therapy was unable to improve viability and engraftment outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".