Microvascular dysfunction in a murine model of Alzheimer’s disease using intravital microscopy
Bibliographic record
Abstract
Alzheimer’s disease (AD) is a complex neurocognitive disorder. Early theories of AD sought to identify a single unifying explanation underlying AD pathogenesis; however, evolving evidence suggests it is a multifactorial, systemic disease, involving multiple systems. Of note, vascular dysfunction, encompassing both cerebral and peripheral circulation, has been implicated in AD pathogenesis. This pilot study used intravital microscopy to assess differences in responsiveness of gluteal muscle arterioles between a transgenic AD mouse model (APP/PS1; Tg) and wild-type (C57BL/6; WT) mice to further elucidate the role of vascular dysfunction in AD. Arteriole diameters were measured in response to acetylcholine (10–9 to 10–5 M), phenylephrine (10–9 to 10–5 M), histamine (10–9 to 10–4 M) and compound 48/80 (10–9 to 10–3 M). Tg mice demonstrated a trend toward reduced vasodilatory response to acetylcholine with a significant difference at 10–5 M (36.91 vs. 69.55%: p = 0.0107) when compared to WT. No significant differences were observed with histamine, compound 48/80 or phenylephrine; however, a trend toward reduced vasoconstriction to phenylephrine was observed in Tg mice at higher concentrations. Mean net diameter change (resting to maximum) also differed significantly (p = 0.0365) between WT (19.11 μm) and Tg mice (11.13 μm). These findings suggest reduced vascular responsiveness may contribute to the systemic vascular deficits previously observed in AD models. Future research using diverse models and broader variables could further elucidate peripheral vascular dysfunction’s role in AD pathogenesis, including its impact on motor symptoms and disease progression. Such insights may inform the development of vascular-targeted therapeutic strategies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.002 |
| 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".