Acute exposure to streptozotocin but not human proinflammatory cytokines impairs neonatal porcine islet insulin secretion in vitro but not in vivo
Bibliographic record
Abstract
BACKGROUND: Neonatal porcine islets (NPI) are a potentially useful source of beta cells for transplantation to treat type 1 diabetes mellitus. However, cytokine exposure following xenotransplantation is likely to prevent successful NPI xenograft survival. In this study, we examined the effects of human proinflammatory cytokines (IL-1 beta, IFN gamma, TNFalpha) on NPI function and cell death. These cytokines have been shown to be cytotoxic to beta cells, in part through the generation of nitric oxide. Therefore, we also examined NPI function after acute oxidative stress caused by streptozotocin (STZ), a nitric oxide-generating beta cell cytotoxin. METHODS: Cultured NPI were exposed to human IL-1 beta, TNFalpha and IFN gamma for 48 h or STZ for 30 min in vitro. Cytokine exposed islets were transplanted into diabetic mice and assessed for function. Mice transplanted with control NPI were injected with STZ and also assessed metabolically. RESULTS: In vitro exposure to STZ, but not cytokines, significantly reduced NPI glucose stimulated insulin secretion (1.1 +/- 0.1 vs. 4.3 +/- 1.3-fold stimulation index in STZ vs. control, P < 0.05) in addition to cellular DNA recovery (57.6 +/- 4.4%, P < 0.05). Total cellular insulin content was significantly reduced in NPI exposed to either cytokines (56.6 +/- 8.1%) or STZ (45.7 +/- 1.6%) compared to controls (P < 0.05). Interestingly, both STZ and cytokines did not appear to negatively affect NPI function post-transplant. CONCLUSIONS: The potent nitric oxide generating cytotoxin STZ is able to impair in vitro NPI beta cell insulin release whereas human cytokines (IL-1 beta, TNFalpha, IFN gamma) do not affect the secretory response nor are they cytotoxic in vitro. These results may have implications for the development of anti-rejection protocols to be used in clinical NPI xenotransplants.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".