Forward programming of hiPSCs towards beta-like cells using Ngn3, Pdx1, and MafA
Bibliographic record
Abstract
Abstract Transplantation of stem cell-derived β-cells is a promising therapeutic advancement in the treatment of type 1 diabetes mellitus. A current limitation of this approach is the long differentiation timeline of up to two months that generates a heterogeneous population of pancreatic endocrine cells. To address this limitation, an inducible lentiviral overexpression system of mature β-cell markers was introduced into human induced-pluripotent stem cells (hiPSCs). Following selection of the successfully transduced hiPSCs, the cells were treated with doxycycline in pancreatic progenitor induction medium to support their transition towards the pancreatic lineage. Cells cultured with doxycycline presented the markers of interest, NGN3, PDX1, and MAFA, after five days of culture, and glucose-stimulated insulin secretion assays demonstrated that the cells were glucose-responsive in a monolayer culture. When cultured as a spheroid, the markers of interest and insulin secretion in a parallel glucose-stimulated insulin secretion assay were maintained; however, insulin secretion upon consecutive glucose challenges was limited. Comparison to human fetal and adult donor tissues identified that although the hiPSC-derived spheroids present similar markers to adult insulin-producing cells, they are functionally representative of fetal development. Together, these results suggest that with optimization of the temporal expression of these markers, forward programming of hiPSCs towards insulin-producing cells could be a possible alternative for islet transplantation.
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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) | 0.002 | 0.001 |
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".