Pancreatic resident endocrine progenitors demonstrate high islet neogenic fidelity and committed homing towards diabetic mice pancreas
Bibliographic record
Abstract
Pancreatic progenitors have been explored for their profound characteristics and unique commitment to generate new functional islets in regenerative medicine. Pancreatic resident endocrine progenitors (PREPs) with mesenchymal stem cell (MSC) phenotype were purified from BALB/c mice pancreas and characterized. PREPs were differentiated into mature islet clusters in vitro by activin-A and swertisin and functionally characterized. A temporal gene and protein profiling was performed during differentiation. Furthermore, PREPs were labeled with green fluorescent protein (GFP) and transplanted intravenously into streptozotocin (STZ) diabetic mice while monitoring their homing and differentiation leading to amelioration in the diabetic condition. PREPs were positive for unique progenitor markers and transcription factors essential for endocrine pancreatic homeostasis along with having the multipotent MSC phenotype. These cells demonstrated high fidelity for islet neogenesis in minimum time (4 days) to generate mature functional islet clusters (shortest reported period for any isolated stem/progenitor). Furthermore, GFP-labeled PREPs transplanted in STZ diabetic mice migrated and localized within the injured pancreas without trapping in any other major organ and differentiated rapidly into insulin-producing cells without an external stimulus. A rapid decrease in fasting blood glucose levels toward normoglycemia along with significant increase in fasting serum insulin levels was observed, which ameliorated the diabetic condition. This study highlights the unique potential of PREPs to generate mature islets within the shortest period and their robust homing toward the damaged pancreas, which ameliorated the diabetic condition suggesting PREPs affinity toward their niche, which can be exploited and extended to other stem cell sources in diabetic therapeutics.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".