Expansion and Differentiation of Germline-Derived Pluripotent Stem Cells on Biomaterials
Bibliographic record
Abstract
Stem cells with broad differentiation potential, such as the recently described germline-derived pluripotent stem cells (gPS cells), are an appealing source for tissue engineering strategies. Biomaterials can inhibit, support, or induce proliferation and differentiation of stem cells. Here we identified (1) polymers that maintain self-renewal and differentiation potential of gPS cells for feeder-free expansion and (2) polymers supporting the cardiomyogenic fate of gPS cells by analyzing a panel of polymers of an established biomaterial bank previously used to assess growth of diverse stem cell types. Identification of cytocompatible gPS cell/biomaterial combinations required analysis of several parameters, including morphology, viability, cytotoxicity, apoptosis, proliferation, and differentiation potential. Pluripotency of gPS cells was visualized by the endogenous Oct4-promoter-driven GFP and by Sox2 and Nanog immunofluorescence. Viability assay, proliferation assay, and flow cytometry showed that gPS cells efficiently adhere and are viable on synthetic polymers, such as Resomer(®) LR704 (poly(L-lactic-D,L-lactic acid), poly(tetrafluor ethylene) (PTFE), poly(vinylidene fluoride) (PVDF), and on gelatine-coated tissue culture polystyrene. Expansion experiments showed that Resomer LR704 is an alternative substrate for feeder-free gPS cell maintenance. Resomer LR704, PTFE, and PVDF were found to be suitable for gPS cell differentiation. Spontaneous beating in embryoid bodies cultured on Resomer LR704 occurred already on day 8 of differentiation, much earlier compared to the other surfaces. This indicates that Resomer LR704 supports spontaneous cardiomyogenic differentiation of gPS cells, which was also confirmed on molecular, protein and functional level.
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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".