Astrocytes display ultrastructural alterations and heterogeneity in the hippocampus of aged APP-PS1 mice and human post-mortem brain samples
Bibliographic record
Abstract
The past decade has witnessed increasing evidence for a crucial role played by glial cells, notably astrocytes, in Alzheimer's disease (AD). To provide novel insights into the roles of astrocytes in the pathophysiology of AD, we performed a quantitative ultrastructural characterization of their intracellular contents and parenchymal interactions in an aged mouse model of AD pathology, as aging is considered the main risk factor for developing AD. We compared 20-month-old APP-PS1 and age-matched C57BL/6J male mice, among the ventral hippocampus CA1 strata lacunosum-moleculare and radiatum, two hippocampal layers severely affected by AD pathology. Astrocytes in both layers interacted more with synaptic elements and displayed more ultrastructural markers of increased phagolysosomal activity in APP-PS1 versus C57BL6/J mice. In addition, we investigated the ultrastructural heterogeneity of astrocytes, describing in the two examined layers a dark astrocytic state that we characterized in terms of distribution, interactions with AD hallmarks, and intracellular contents. This electron-dense astrocytic state, termed dark astrocytes, was observed throughout the hippocampal parenchyma, closely associated with the vasculature, and possessed several ultrastructural markers of cellular stress. A case study exploring the hippocampal head of an aged human post-mortem brain sample also revealed the presence of a similar electron-dense, dark astrocytic state. Overall, our study provides the first ultrastructural quantitative analysis of astrocytes among the hippocampus in aged AD pathology, as well as a thorough characterization of a dark astrocytic state conserved from mouse to human.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".