<i>In vivo</i> characterization of transplanted human embryonic stem cell‐derived pancreatic endocrine islet cells
Bibliographic record
Abstract
OBJECTIVES: Islet-like clusters (ILCs), differentiated from human embryonic stem cells (hESCs), were characterized both before and after transplantation under the kidney capsule of streptozotocin-induced diabetic immuno-incompetent mice. MATERIALS AND METHODS: Multiple independent ILC preparations (n = 8) were characterized by immunohistochemistry, flow cytometry and cell insulin content, with six preparations transplanted into diabetic mice (n = 42), compared to controls, which were transplanted with either a human fibroblast cell line or undifferentiated hESCs (n = 28). RESULTS: Prior to transplantation, ILCs were immunoreactive for the islet hormones insulin, C-peptide and glucagon, and for the ductal epithelial marker cytokeratin-19. ILCs also had cellular insulin contents similar to or higher than human foetal islets. Expression of islet and pancreas-specific cell markers was maintained for 70 days post-transplantation. The mean survival of recipients was increased by transplanted ILCs as compared to transplanted human fibroblast cells (P < 0.0001), or undifferentiated hESCs (P < 0.042). Graft function was confirmed by secretion of human C-peptide in response to an oral bolus of glucose. CONCLUSIONS: hESC-derived ILC grafts continued to contain cells that were positive for islet endocrine hormones and were shown to be functional by their ability to secrete human C-peptide. Further enrichment and maturation of ILCs could lead to generation of a sufficient source of insulin-producing cells for transplantation into patients with type 1 diabetes.
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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 | 0.000 |
| 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".