Molecular specification of expanded forebrain neural stem and progenitor cells
Bibliographic record
Abstract
The molecular specification of neural precursor cells has been suggested to be a progressive process, with a transition from an early requirement for extrinsic signals to intrinsic mechanisms. Thus, the cells in the nervous system acquire distinct fates in response to extrinsic signals, which activate repertoires of transcription factors in a region and cell type specific manner. The studies in this thesis are aimed to increase our understanding as to the extent neural stem and progenitor cells maintain their regional identity during expansion in vitro. To address this issue, cells isolated from different regions of the embryonic or adult mouse and human forebrain were expanded, either as free-floating neurosphere cultures or as attached monolayer cultures. The expression of developmental control genes specific for each region was analyzed in the expanded cells, and their developmental potency was tested both after in vitro differentiation, and after transplantation in vivo. The results show that independent of culture method the expanded cells maintain many aspects of their regional identity. They express developmental control genes characteristic for their area of origin, and upon differentiation they generate neurons characteristic of that area. However, the different culture methods differentially expand specific progenitor populations within each area, and the progenitor composition in the cultures is decisive for the differentiation potential of the expanded cells. Besides its relevance for understanding basic developmental processes, the results may also have an impact on the selection of donor cells and expansion method for cells to be used in cell replacement therapies
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".