Combination Therapy with Glucagon-Like Peptide-1 and Gastrin Induces β-Cell Neogenesis from Pancreatic Duct Cells in Human Islets Transplanted in Immunodeficient Diabetic Mice
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Bibliographic record
Abstract
Pancreatic islet transplantation as a treatment for type 1 diabetes is limited by human donor tissue availability. We investigated whether the beta-cell mass in human isolated islets could be expanded by treatments with glucagon-like peptide-1 (GLP-1) and gastrin, peptides reported to stimulate beta-cell growth in mice and rats with deficits in beta-cell mass. Human islets with low endocrine cell purity (7% beta-cells, 4% alpha-cells) and abundant exocrine cells (29% duct cells and 25% acinar cells) were implanted under the renal capsule of nonobese diabetic-severe combined immune deficiency (NOD-scid) mice made diabetic with streptozotocin. The mice were treated with GLP-1 and gastrin, separately and together, daily for 5 weeks. Blood glucose was significantly reduced only in mice implanted with human pancreatic cells and treated with GLP-1 plus gastrin. Correction of hyperglycemia was accompanied by increased insulin content in the human pancreatic cell grafts as well as by increased plasma levels of human C-peptide in the mice. Immunocytochemical examination revealed a fourfold increase in insulin-positive cells in the human pancreatic cell grafts in GLP-1 plus gastrin-treated mice, and most of this increase was accounted for by the appearance of cytokeratin 19-positive pancreatic duct cells expressing insulin. We conclude that combination therapy with GLP-1 and gastrin expands the beta-cell mass in human islets implanted in immunodeficient diabetic mice, largely from pancreatic duct cells associated with the islets, and this is sufficient to ameliorate hyperglycemia in the mice.
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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 it