Regulatory Role of Redox Balance in Determination of Neural Precursor Cell Fate
Bibliographic record
Abstract
In 1990s, reports of discovery of a small group of cells capable of proliferation and contribution to formation of new neurons in the central nervous system (CNS) reversed a century-old concept on lack of neurogenesis in the adult mammalian brain. These cells are found in all stages of human life and contribute to normal cellular turnover of the CNS. Therefore, the identity of regulating factors that affect their proliferation and differentiation is a highly noteworthy issue for basic scientists and their clinician counterparts for therapeutic purposes. The cues for such control are embedded in developmental and environmental signaling through a highly regulated tempo-spatial expression of specific transcription factors. Novel findings indicate the importance of reactive oxygen species (ROS) in the regulation of this signaling system. The elusive nature of ROS signaling in many vital processes from cell proliferation to cell death creates a complex literature in this field. Here, we discuss the emerging thoughts on the importance of redox regulation of proliferation and maintenance in mammalian neural stem and progenitor cells under physiological and pathological conditions. The current knowledge on ROS-mediated changes in redox-sensitive proteins that govern the molecular mechanisms in proliferation and differentiation of these cells is reviewed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".