Chronic cerebral hypoperfusion alters amyloid-β peptide pools leading to cerebral amyloid angiopathy, microinfarcts and haemorrhages in Tg-SwDI mice
Bibliographic record
Abstract
Cerebral hypoperfusion is an early feature of Alzheimer's disease (AD) that influences the progression from mild cognitive impairment to dementia. Understanding the mechanism is of critical importance in the search for new effective therapies. We hypothesized that cerebral hypoperfusion promotes the accumulation of amyloid-β (Aβ) and degenerative changes in the brain and is a potential mechanism contributing to development of dementia. To address this, we studied the effects of chronic cerebral hypoperfusion induced by bilateral carotid artery stenosis on Aβ peptide pools in a transgenic mouse model of AD (transgenic mice with Swedish, Dutch and Iowa mutations in human amyloid precursor protein (APP) (Tg-SwDI)). Cerebrovascular integrity was characterized by quantifying the occurrence of microinfarcts and haemorrhages and compared with wild-type mice without Aβ. A significant increase in soluble Aβ peptides (Aβ40/42) was detected after 1 month of hypoperfusion in the parenchyma in parallel with elevated APP and APP proteolytic products. Following 3 months, a significant increase in insoluble Aβ40/42 was determined in the parenchyma and vasculature. Microinfarct load was significantly increased in the Tg-SwDI as compared with wild-type mice and further exacerbated by hypoperfusion at 1 and 3 months. In addition, the number of Tg-SwDI hypoperfused mice with haemorrhages was increased compared with hypoperfused wild-type mice. Soluble parenchymal Aβ was associated with elevated NADPH oxidase-2 (NOX2) which was exacerbated by 1-month hypoperfusion. We suggest that in response to hypoperfusion, increased Aβ production/deposition may contribute to degenerative processes by triggering oxidative stress promoting cerebrovascular disruption and the development of microinfarcts.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".