Evaluating The Contributions of Focal Subclinical Ischemia to Alzheimer’s Disease Pathogenesis
Bibliographic record
Abstract
Alzheimer’s disease (AD) is the most common form of dementia. The amyloid hypothesis of AD proposes that pathogenic expression of amyloid precursor protein (APP) leads to amyloid plaque, and hyperphosphorylated tau, resulting in neuronal death. Patients living with AD experience a progressive loss of memory and cognition, with deficits in activities of daily living. AD is also a disease of aging and has been shown to be strongly associated with many age-related comorbidities. One major group of comorbidities are vascular risk factors and diseases of the vasculature, which include stroke. In addition, covert stroke or subclinical focal ischemia, accounts for the majority of these stroke cases. However, as covert strokes fail to present with any clinical symptoms and are often only detectable through imaging, it is difficult to accurately assess the interactions between covert stroke and AD. Adding to this complication, AD can occur 10-15 years prior to clinical diagnosis. In this thesis, I modelled and examined the effects of focal subclinical ischemia on the early stages of AD pathogenesis using two different preclinical models of AD. In my first two aims, I assessed the effects of focal subclinical ischemia on AD pathogenesis in an independent manner, where the covert strokes occur prior to the expression of APP. When focal subclinical ischemia occurs prior to AD onset, focal subclinical ischemia accelerated the peri-lesional amyloid pathology and enhanced the activation of microglia but not astrocytes. However, focal subclinical ischemia did not worsen the cognitive deficits after APP expression. As AD has a long preclinical phase, in my 3rd aim, I also examined the effects of focal subclinical ischemia on AD pathogenesis concurrent to early AD. In contrast to the first two aims, focal subclinical ischemia did not result in a peri-lesional increase in amyloid plaque load. However, there was a change in the distribution of cerebral amyloid angiopathy in the peri-lesional region. Although we found a localized change in white matter as a result of focal subclinical ischemia, the behavioural deficits were ultimately driven by APP expression. Overall, focal subclinical ischemia resulted in differential localized effects in the AD brain.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".