Amyloid‐Beta Pathology Increases Synaptic Engulfment by Glia in Feline Cognitive Dysfunction Syndrome: A Naturally Occurring Model of Alzheimer's Disease
Bibliographic record
Abstract
Feline cognitive dysfunction syndrome (CDS; a.k.a. feline dementia) is an age-related neurodegenerative disorder, comparable to dementia in people, characterised by behavioural changes such as increased vocalisation, altered social interactions, sleep-wake cycle, disorientation and house-soiling. Although the underlying mechanisms remain poorly understood, pathologies similar to those observed in Alzheimer's disease (AD) have been identified in the brains of aged or CDS-affected cats, including brain atrophy, neuronal loss, amyloid-beta plaques, tau pathology and cerebral amyloid angiopathy. Neuroinflammation and synapse loss, other important hallmarks of AD, may also play important roles in feline ageing and CDS, but these are yet to be explored. Several mechanisms of synapse loss have been described in human AD and mouse models of amyloidopathy, including synaptic accumulation of amyloid-beta and the aberrant induction of synaptic engulfment by microglia and astrocytes. In this study, immunohistochemistry and confocal microscopy were used to examine the parietal cortex of young (n = 7), aged (n = 10) and CDS-affected (n = 8) cats. Linear mixed effect modelling revealed that amyloid-beta accumulates within synapses in the aged and CDS-affected brain. Additionally, in the aged and CDS groups, there was microgliosis, astrogliosis and increased synaptic engulfment by microglia and astrocytes in regions with Aβ plaques. Further, microglia and astrocytes show increased internalisation of amyloid-beta-containing synapses near plaques. These findings suggest that amyloid-beta exerts a pathogenic effect in the feline brain, with mechanisms mirroring those seen in human AD. Importantly, these results support the use of feline CDS as a naturally occurring, translational model of Alzheimer's disease, offering valuable insights into AD pathogenesis and potential therapeutic targets.
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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) | 0.001 | 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".