Comparison of Vascular Perturbations in an A<i>β</i>‐Injected Animal Model and in AD Brain
Bibliographic record
Abstract
The validity of amyloid-β peptide (Aβ(1-42)) intrahippocampal injection, as an animal model of Alzheimer's disease (AD), has previously been considered in terms of inflammatory reactivity and neuronal damage. In this work, we have extended the testing of the animal model to vasculature by comparison of selected properties of microvessels in vivo with those in human AD brain tissue. The injection of Aβ(1-42), relative to control PBS (phosphate buffered saline), increased the mean number of microvessels and diminished the mean length of microvessels in the molecular layer of dentate gyrus. The animal model showed Aβ(1-42), but not PBS, injection was associated with abnormalities in morphology of microvessels which were characterized as looping, fragmented, knob-like, uneven, and constricted. In particular, numbers of constricted microvessels, defined as vessels with diameters less than 3 μm, were considerably enhanced for Aβ(1-42), compared to PBS, injection. In comparison, human AD brain demonstrated an elevated number of microvessels with a diminished mean length relative to nondemented (ND) brain. Additionally, microvessel perturbations in AD brain showed a similar pattern of morphological abnormalities to those observed in Aβ(1-42)-injected rat hippocampus. Constricted microvessels were a prominent feature of AD brain but were rarely observed in ND tissue. These results provide the first evidence that a peptide-injection animal model exhibits a commonality in perturbations of microvessels compared with those evident in 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| 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".