Increased hippocampal neurogenesis in the progressive stage of Alzheimer's disease phenotype in an APP/PS1 double transgenic mouse model
Bibliographic record
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with senile beta-amyloid (Abeta) plaques and cognitive decline. Neurogenesis in the adult hippocampus is implicated in regulating learning and memory, and is increased in human postmortem brain of AD patients. However, little is currently known about the changes of hippocampal neurogenesis in the progression of AD. As brain tissues from patients during the progression of AD are generally not available, an amyloid precursor protein (APP)/presenilin1 (PS1) double transgenic mouse model of AD was studied. Bromodeoxyuridine (BrdU) labeling supported by doublecortin staining was used to detect proliferating hippocampal cells in the mice. Compared with age-matched wild-type controls, 9-month-old transgenic mice with memory impairment and numerous brain Abeta deposits showed increased numbers of proliferating hippocampal cells. However, 3-month-old transgenic mice with normal memory and subtle brain Abeta deposits showed normal hippocampal proliferation. Double immunofluorescent labeling with BrdU and either NeuN or glial fibrillary acidic protein was conducted in mice at 10 months (28 days after the last BrdU injection) to determine the differentiation of proliferating cells. The number of hippocampal BrdU-positive cells and BrdU-positive cells differentiating into neurons (neurogenesis) in 10-month-old mice was greater in transgenic mice compared with age-matched controls, but the ratio of hippocampal BrdU-positive cells differentiating into neurons and astroglia was comparable. These results suggest hippocampal neurogenesis may increase during the progression of AD. Targeting this change in neurogenesis and understanding the underlying mechanism could lead to the development of a new treatment to control the progression of AD.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".