O3‐06‐02: Venular degeneration in the pathogenesis of Alzheimer's disease
Bibliographic record
Abstract
Accumulation of amyloid-beta peptide (Ab) on leptomeningeal and cortical arterioles, or cerebral amyloid angiopathy (CAA) is associated with impaired vascular reactivity and accelerated cognitive decline in Alzheimer's disease. The significance of this vascular dysfunction in AD etiology and progression remains uncertain and the mechanism underlying the injury is not fully understood. To date research has focused on Ab-induced damage to capillaries and CAA-associated arterioles, without examining effects across the entire vascular bed We utilized in vivo two photon microscopy imaging of TgCRND8 mice microvasculature, to examine structure and function of the arterioles and venules of the somatosensory cortex. We confirmed these results using confocal microscopy and image analyses software Here, we report the differential regulation of vascular function in both the feeding (arteriolar) and draining (venular) vessels in the TgCRND8 mouse model that develops progressive CAA. We found that CAA correlated with degeneration of mural cells on the penetrating venules but not on the penetrating arterioles. We further depleted mural cells with thea platelet-derived growth factor receptor-antagonist, SU6668, and demonstrated increased tortuosity of the venules but not the arterioles, exacerbation of CAA in the arterioles but not the venules. We demonstrated alterations of the microvascular network cerebral blood flow response to hypercapnia as a result of decreased mural cells and increased CAA Together, our work shows previously unrecognized structural and functional alterations in penetrating venules and sheds light on the complexity of the relationship between vascular network structure and function in AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".