Proliferation, differentiation and amyloid-β production in neural progenitor cells isolated from TgCRND8 mice
Bibliographic record
Abstract
The amyloid precursor protein (APP) and amyloid-β (Aβ) peptide play central roles in the pathology and etiology of Alzheimer's disease. Amyloid-induced impairments in neurogenesis have been investigated in several transgenic mouse models but the mechanism of action remains to be conclusively demonstrated. The changes in neurogenesis during this transition of increasing Aβ levels and plaque formation were investigated in the present study. We found that the proliferation of newborn cell in the dentate gyrus was enhanced prior to elevations in soluble Aβ production as well as amyloid deposition in 5-week-old TgCRND8 mice, which are well-established Alzheimer's disease models, compared to non-transgenic (Non-Tg) mice. The number of BrdU-positive cells remained higher in TgCRND8 vs Non-Tg mice for a period of 8weeks. The numbers of BrdU/NeuN-positive cells were not significantly different in TgCRND8 compared to Non-Tg mice. A significant decrease in BrdU/GFAP but not in BrdU/S100β was found in Tg vs Non-Tg at 6-weeks of age. In addition, a unique observation was made using isolated neuroprogenitor cells from TgCRND8 mice which were found to be less viable in culture and produced substantial amounts of secreted Aβ peptides. This suggests that the proliferation of neural progenitors in vivo may be modulated by high levels of APP expression and the resulting Aβ generated directly by the progenitor cells. These findings indicate that cell proliferation is increased prior to Aβ deposition and that cell viability is decreased in TgCRND8 mice over time.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".