Review: Astrocytes in Alzheimer's disease and other age‐associated dementias: a supporting player with a central role
Bibliographic record
Abstract
Astrocytes have essential roles in the central nervous system and are also implicated in the pathogenesis of neurodegenerative disease. Forming non-overlapping domains, astrocytes are highly complex cells. Immunohistochemistry to a variety of proteins can be used to study astrocytes in tissue, labelling different cellular components and sub-populations, including glial fibrillary acidic protein, ALDH1L1, CD44, NDRG2 and amino acid transporters, but none of these labels the entire astrocyte population. Increasing heterogeneity is recognized in the astrocyte population, a complexity that is relevant both to their normal function and pathogenic roles. They are involved in neuronal support, as active components of the tripartite synapse and in cell interactions within the neurovascular unit (NVU), where they are essential for blood-brain barrier maintenance and neurovascular coupling. Astrocytes change with age, and their responses may modulate the cellular effects of neurodegenerative pathologies, which alone do not explain all of the variance in statistical models of neurodegenerative dementias. Astrocytes respond to both the neurofibrillary tangles and plaques of Alzheimer's disease, to hyperphosphorylated tau and Aβ, eliciting an effect which may be neuroprotective or deleterious. Not only astrocyte hypertrophy, in the form of gliosis, occurs, but also astrocyte injury and atrophy. Loss of normal astrocyte functions may contribute to reduced support for neurones and dysfunction of the NVU. Understanding how astrocytes contribute to dementia requires an understanding of the underlying heterogeneity of astrocyte populations, and the complexity of their responses to pathology. Enhancing the supportive and neuroprotective components of the astrocyte response has potential translational applications in therapeutic approaches to dementia.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".