Powerful beneficial effects of macrophage colony-stimulating factor on -amyloid deposition and cognitive impairment in Alzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease is a major cause of dementia in humans. The appearance of cognitive decline is linked to the overproduction of a short peptide called beta-amyloid (Abeta) in both soluble and aggregate forms. Here, we show that injecting macrophage colony-stimulating factor (M-CSF) to Swedish beta-amyloid precursor protein (APP(Swe))/PS1 transgenic mice, a well-documented model for Alzheimer's disease, on a weekly basis prior to the appearance of learning and memory deficits prevented cognitive loss. M-CSF also increased the number of microglia in the parenchyma and decreased the number of Abeta deposits. Senile plaques were smaller and less dense in the brain of M-CSF-treated mice compared to littermate controls treated with vehicle solution. Interestingly, a higher ratio of microglia internalized Abeta in the brain of M-CSF-treated animals and the phagocytosed peptides were located in the late endosomes and lysosomes. Less Abeta(40) and Abeta(42) monomers were also detected in the extracellular protein enriched fractions of M-CSF-treated transgenic mice when compared with vehicle controls. Finally, treating APP(Swe)/PS1 mice that were already demonstrating installed Abeta pathology stabilized the cognitive decline. Together these results provide compelling evidence that systemic M-CSF administration is a powerful treatment to stimulate bone marrow-derived microglia, degrade Abeta and prevent or improve the cognitive decline associated with Abeta burden in a mouse model of 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 | 0.000 | 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) | 0.000 | 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".