Age-related changes in synaptic markers and monocyte subsets link the cognitive decline of APPSwe/PS1 mice
Bibliographic record
Abstract
Alzheimer's disease (AD) is characterized by a progressive memory decline and numerous pathological abnormalities, including amyloid β (Aβ) accumulation in the brain and synaptic dysfunction. Here we wanted to study whether these brain changes were associated with alteration in the population of monocyte subsets since accumulating evidence supports the concept that the innate immune system plays a role in the etiology of this disease. We then determined the immune profile together with expression of genes encoding synaptic proteins and neurotrophins in APP(Swe)/PS1 mice and their age-matched wild-type (WT) littermates. We found that the progressive cognitive decline and the dramatic decrease in the expression of numerous synaptic markers and neurotrophins correlated with a major defect in the subset of circulating inflammatory monocytes. Indeed the number of CX(3)CR1(low)Ly6-C(high)CCR2(+)Gr1(+) monocytes remained essentially similar between 5 weeks and 6 months of age in APP(Swe)/PS1 mice, while these cells significantly increased in 6-month-old WT littermates. Of great interest is that the onset of cognitive decline was closely associated with the accumulation of soluble Aβ, disruption of synaptic activity, alteration in the BDNF system, and a defective production in the subset of CX(3)CR1(low)Ly6-C(high)CCR2(+)Gr1(+) monocytes. However, these memory impairments can be prevented or restored by boosting the monocytic production, using a short treatment of macrophage colony-stimulating factor (M-CSF). In conclusion, low CCR2(+) monocyte production by the hematopoietic system may be a direct biomarker of the cognitive decline in a context of AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 | 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".