Manipulation of EGFR-Induced Signaling for the Recruitment of Quiescent Neural Stem Cells in the Adult Mouse Forebrain
Bibliographic record
Abstract
The ventricular-subventricular zone (V-SVZ) is the principal neurogenic niche in the adult mammalian forebrain. Neural stem/progenitor cell (NSPC) activity within the V-SVZ is controlled by numerous of extrinsic factors, whose downstream effects on NSPC proliferation, survival and differentiation are transduced via a limited number of intracellular signaling pathways. Here, we investigated the relationship between age-related changes in NSPC output and activity of signaling pathways downstream of the epidermal growth factor receptor (EGFR), a major regulator of NSPC activity. Biochemical experiments indicated that age-related decline of NSPC activity in vivo is accompanied by selective deficits amongst various EGFR-induced signal pathways within the V-SVZ niche. Pharmacological loss-of-function signaling experiments with cultured NSPCs revealed both overlap and selectivity in the biological functions modulated by the EGFR-induced PI3K/AKT, MEK/ERK and mTOR signaling modules. Specifically, while all three modules promoted EGFR-mediated NSPC proliferation, only mTOR contributed to NSPC survival and only MEK/ERK repressed NSPC differentiation. Using a gain-of-function in vivo genetic approach, we electroporated a constitutively active EGFR construct into a subpopulation of quiescent, EGFR-negative neural stem cells (qNSCs); this ectopic activation of EGFR signaling enabled qNSCs to divide in 3-month-old early adult mice, but not in mice at middle-age or carrying familial Alzheimer disease mutations. Thus, (i) individual EGFR-induced signaling pathways have dissociable effects on NSPC proliferation, survival, and differentiation, (ii) activation of EGFR signaling is sufficient to stimulate qNSC cell cycle entry during early adulthood, and (iii) the proliferative effects of EGFR-induced signaling are dominantly overridden by anti-proliferative signals associated with aging and Alzheimer’s disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".