Oxidative stress and cerebrovascular dysfunction in mouse models of Alzheimer's disease
Bibliographic record
Abstract
Several factors have been implicated in Alzheimer's disease (AD) but there is no definite conclusion as to the main pathogenic agents. Mutations in the amyloid precursor protein (APP) that lead to increased production of amyloid beta peptide (A beta) are associated with the early-onset, familial forms of AD. However, in addition to ageing, the most common risk factors for the sporadic, prevalent form of AD are hypertension, hypercholesterolaemia, ischaemic stroke, the ApoE4 allele and diabetes, all characterized by a vascular pathology. In AD, the vascular pathology includes accumulation of A beta in the vessel wall, vascular fibrosis, and other ultrastructural changes in constituent endothelial and smooth muscle cells. Moreover, the ensuing chronic cerebral hypoperfusion has been proposed as a determinant factor in the accompanying cognitive deficits. In transgenic mice that overexpress mutated forms of the human APP (APP mice), the increased production of A beta results in vascular oxidative stress and loss of vasodilatory function. The culprit molecule, superoxide, triggers the synthesis of other reactive oxygen species and the sequestration of nitric oxide (NO), thus impairing resting cerebrovascular tone and NO-dependent dilatations. The A beta-induced cerebrovascular dysfunction can be completely abrogated in aged APP mice with antioxidant therapy. In contrast, in mice that overproduce an active form of the cytokine transforming growth factor-beta1 and recapitulate the vascular structural changes seen in AD, antioxidants have no beneficial effect on the accompanying cerebrovascular deficits. This review discusses the beneficial role and limitations of antioxidant therapy in AD cerebrovascular pathology.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".