Efficient Generation of Pancreatic Progenitor Cells from Induced Pluripotent Stem Cells Derived from a Non-Invasive and Accessible Tissue Source—The Plucked Hair Follicle
Bibliographic record
Abstract
The advent of induced pluripotent stem cell (iPSC) technology has brought about transformative advancements in regenerative medicine, offering novel avenues for disease modeling, drug testing, and cell-based therapies. Patient-specific iPSC-based treatments hold the promise of mitigating immune rejection risks. However, the intricacies and costs of producing autologous therapies present commercial challenges. The hair follicle is a multi-germ layered versatile cell source that can be harvested at any age. It is a rich source of keratinocytes, fibroblasts, multipotent stromal cells, and the newly defined Hair Follicle-Associated Pluripotent Stem Cells (HAP). It can also be obtained non-invasively and transported via regular mail channels, making it the ideal starting material for an autologous biobank. In this study, cryopreserved hair follicle-derived iPSC lines (HF-iPS) were established through integration-free vectors, encompassing a diverse cohort. These genetically stable lines exhibited robust expression of pluripotency markers, and showcased tri-lineage differentiation potential. The HF-iPSCs effectively differentiated into double-positive cKIT+/CXCR4+ definitive endoderm cells and NKX6.1+/PDX1+ pancreatic progenitor cells, affirming their pluripotent attributes. We anticipate that the use of plucked hair follicles as an accessible, non-invasive cell source to obtain patient cells, in conjunction with the use of episomal vectors for reprogramming, will improve the future generation of clinically applicable pancreatic progenitor cells for the treatment of Type I Diabetes.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".