Low Oxygen Enhances Primitive and Definitive Neural Stem Cell Colony Formation by Inhibiting Distinct Cell Death Pathways
Bibliographic record
Abstract
Neural stem cells (NSCs) can be derived from single mouse embryonic stem cells (ESCs) in the absence of instructive factors. Clonal primitive NSC (pNSC) colonies are formed first, and then give rise to clonal, fibroblast growth factor-dependent definitive neural stem cells (dNSCs). We tested low-oxygen culture as a potential method of alleviating the extensive cell death seen in pNSCs and dNSCs. Culture in low (4%) oxygen promoted survival of pNSCs by inhibiting apoptosis-inducing factor (AIF)-dependent cell death, although pNSCs undergo both AIF- and caspase-mediated cell death in 20% oxygen. In contrast, survival of dNSCs in low oxygen was increased by inhibition of caspase-dependent cell death. In normoxia, AIF is implicated in promoting dNSC survival. Neither survival effect was dependent on the main transcriptional effector of hypoxia, hypoxia-inducible factor 1. Low-oxygen concentrations may be involved in expansion of early NSC populations by inhibiting cell death through different pathways in these sequential pNSC and dNSC populations.
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 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".