Insulin-Induced Normoglycemia Reduces Islet Number Needed to Achieve Normoglycemia after Allogeneic Islet Transplantation in Diabetic Mice
Bibliographic record
Abstract
The Edmonton protocol established that insulin independence could be reached with the transplantation of an appropriate number of islet cells. However, to effect a cure, islets from two or three pancreases are needed. The aim of this study was to examine whether normoglycemia, with insulin treatment before and after transplantation, reduces the islet number needed to achieve normoglycemia in allogeneic islet transplantation. Swiss mice were used as donors and recipients. Diabetes was induced by i.p. administration of streptozotocin (180 mg/kg BW). Diabetic mice were transplanted with 300 (n = 16), 400 (n = 16), or 500 (n = 16) islets under the left kidney capsule. For every group, half the animals were kept normoglycemic with insulin treatment from day 4 before transplantation to day 10 after transplantation. At the end of the study, all normoglycemic mice were given an i.p. glucose tolerance test (IPGTT). For statistical analysis, paired or unpaired Student's t-test or ANOVA was used. Only insulin-treated mice achieved normoglycemia by the end of the study (37.5% of animals transplanted with 400 islets and 50% transplanted with 300 or 500 islets). At the end of the study, normoglycemic mice transplanted with 300 allogeneic islets showed better glycosylated hemoglobin (HbA1C) than did normoglycemic mice transplanted with 500 islets (300 islets: 2.7 +/- 0.2%; 500 islets: 3.6 +/- 0.2%; p < 0.05). After the IPGTT, insulin-treated mice transplanted with 500 islets showed abnormal glucose tolerance; however, insulin-treated mice transplanted with 300 or 400 islets showed normal glucose tolerance. Insulin treatment reduced the islet number needed to achieve normoglycemia in allogeneic islet transplantation. The HbA1C and IPGTT results suggest that transplanting smaller numbers of allogeneic islets improves beta-cell function; some studies suggest that this may be due to lower immunogenicity, hypoxia, and inflammation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".