Combination Therapy with a Dipeptidyl Peptidase-4 Inhibitor and a Proton Pump Inhibitor Induces β-Cell Neogenesis from Adult Human Pancreatic Duct Cells Implanted in Immunodeficient Mice
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Bibliographic record
Abstract
Combination therapy with a dipeptidyl peptidase-4 inhibitor (DPP-4i) and a proton pump inhibitor (PPI) raises endogenous levels of GLP-1 and gastrin, respectively, and restores pancreatic β-cell mass and normoglycemia in nonobese diabetic (NOD) mice with autoimmune diabetes. The aim of this study was to determine whether a DPP-4i and PPI combination could increase β-cell mass in the adult human pancreas. Pancreatic cells from adult human pancreas donors were implanted in NOD-severe combined immunodeficient (NOD-scid) mice and the mice were treated with a DPP-4i and a PPI for 16 weeks. Human grafts were examined for insulin content and insulin-stained cells. Graft β-cell function was assessed by intravenous glucose tolerance tests (IVGTT) and by glucose control in human cell-engrafted mice treated with streptozotocin (STZ) to delete mouse pancreatic β-cells. Plasma GLP-1 and gastrin levels were raised to two- to threefold in DPP-4i- and PPI-treated mice. Insulin content and insulin-stained cells in human pancreatic cell grafts were increased 9- to 13-fold in DPP-4i and PPI-treated mice and insulin-stained cells were colocalized with pancreatic exocrine duct cells. Plasma human C-peptide responses to IVGTT were significantly higher and STZ-induced hyperglycemia was more completely prevented in DPP-4i- and PPI-treated mice with grafts than in vehicle-treated mice with grafts. In conclusion, DPP-4i and PPI combination therapy raises endogenous levels of GLP-1 and gastrin and greatly expands the functional β-cell mass in adult human pancreatic cells implanted in immunodeficient mice, largely from pancreatic duct cells. This suggests that a DPP-4i and PPI combination treatment may provide a pharmacologic therapy to correct the β-cell deficit in type 1 diabetes.
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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