Establishment of a Stringent Large Animal Model of Insulin-Dependent Diabetes for Islet Autotransplantation
Bibliographic record
Abstract
OBJECTIVE: A stringent porcine islet autograft diabetes model was developed to enable the assessment of autoislet safety and efficacy in either portal vein or an extrahepatic site. METHODS: A 95% pancreatectomy was performed preserving the pancreaticoduodenal arcade; however, glycemic control was still maintained at 3.3 ± 0.3 days (mean ± SEM), shown by euglycemic fasting blood glucose levels of 4.9 ± 0.8 mmol/L (mean ± SEM, n = 3). To reduce surgical complications and eliminate remaining islets, pigs were dosed intravenously after a modified 90% pancreatectomy, with 150-mg/kg streptozotocin, producing a diabetic state (18.9 ± 1.8 mmol/L [mean ± SEM], n = 8; P < 0.001) within 2.0 ± 0.9 days (mean ± SEM). RESULTS: Animals presented with sustained hyperglycemia, failing a glucose challenge test 12 weeks after diabetic induction, and showed no stimulated C-peptide secretion compared to nondiabetic controls (baseline: 0.479 ± 0.080 ng/mL [mean ± SEM] vs after procedure: 0.219 ± 0.055 ng/mL [mean ± SEM], P = 0.02). Diabetic animals were maintained on daily insulin. Despite an initial decline in body weight acutely after pancreatectomy and streptozotocin administration, the mean body weight increased after induction over the approximately 88-day study, indicating that the animals were in good health. CONCLUSION: This stringent porcine model of diabetic induction should be used to assess autograft transplantation safety and efficacy.
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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".