Selection Based on FOXA2 Expression Is Not Sufficient to Enrich for Dopamine Neurons From Human Pluripotent Stem Cells
Bibliographic record
Abstract
Human embryonic and induced pluripotent stem cells are potential cell sources for regenerative approaches in Parkinson disease. Inductive differentiation protocols can generate midbrain dopamine neurons but result in heterogeneous cell mixtures. Therefore, selection strategies are necessary to obtain uniform dopamine cell populations. Here, we developed a selection approach using lentivirus vectors to express green fluorescent protein under the promoter region of FOXA2, a transcription factor that is expressed in the floor plate domain that gives rise to dopamine neurons during embryogenesis. We first validated the specificity of the vectors in human cell lines against a promoterless construct. We then selected FOXA2-positive neural progenitors from several human pluripotent stem cell lines, which demonstrated a gene expression profile typical for the ventral domain of the midbrain and floor plate, but failed to enrich for dopamine neurons. To investigate whether this was due to the selection approach, we overexpressed FOXA2 in neural progenitors derived from human pluripotent stem cell lines. FOXA2 forced expression resulted in an increased expression of floor plate but not mature neuronal markers. Furthermore, selection of the FOXA2 overexpressing fraction also failed to enrich for dopamine neurons. Collectively, our results suggest that FOXA2 is not sufficient to induce a dopaminergic fate in this system. On the other hand, our study demonstrates that a combined approach of promoter activation and lentivirus vector technology can be used as a versatile tool for the selection of a defined cell population from a variety of human pluripotent stem cell lines.
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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 | 0.001 | 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".