The use of a <scp>SOX10</scp> reporter toward ameliorating oligodendrocyte lineage differentiation from human induced pluripotent stem cells
Bibliographic record
Abstract
Oligodendrocytes (OLs) are key players in the central nervous system, critical for the formation and maintenance of the myelin sheaths insulating axons, ensuring efficient neuronal communication. In the last decade, the use of human induced pluripotent stem cells (iPSCs) has become essential for recapitulating and understanding the differentiation and role of OLs in vitro. Current methods include overexpression of transcription factors for rapid OL generation, neglecting the complexity of OL lineage development. Alternatively, growth factor-based protocols offer physiological relevance but struggle with efficiency and cell heterogeneity. To address these issues, we created a novel SOX10-P2A-mOrange iPSC reporter line to track and purify oligodendrocyte precursor cells. Using this reporter cell line, we analyzed an existing differentiation protocol and shed light on the origin of glial cell heterogeneity. Additionally, we have modified the differentiation protocol, toward enhancing reproducibility, efficiency, and terminal maturity. Our approach not only advances OL biology but also holds promise to accelerate research and translational work with iPSC-derived OLs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".