High-Density Lipoprotein Mimetic Peptide 4F Reduces Toxic Amyloid-Beta Exposure to the Blood-Brain Barrier Endothelium in Alzheimer’s Disease Transgenic Mice
Bibliographic record
Abstract
Aβ accumulation in the blood-brain barrier (BBB) endothelium, which lines the cerebrovascular lumen, is a significant contributor to cerebrovascular dysfunction in Alzheimer’s disease (AD). Reduced high-density lipoprotein (HDL) levels are associated with increased AD risk, and the HDL mimetic peptide 4F has been developed as a promising therapeutic agent to improve cerebrovascular health in AD. In this study, we evaluated the impact of 4F on 125 I-Aβ 42 blood-to-brain distribution using dynamic SPECT/CT imaging in both wild-type and APP/PS1 transgenic mice. Graphical analysis of the imaging data demonstrated that 4F significantly reduced the blood-to-brain influx rate in wild-type mice and the distribution of 125 I-Aβ 42 in the BBB endothelium in APP/PS1 mice. To elucidate the molecular mechanisms underlying the effect of 4F, we evaluated its impact on the p38 pathway and its role in mediating Aβ 42 trafficking in human BBB endothelial cell monolayers. Treatment with 4F significantly decreased Aβ 42 induced p38 activation in BBB endothelial cells. Furthermore, inhibition of p38 kinase significantly reduced endothelial accumulation of fluorescence-labeled Aβ 42 and luminal-to-abluminal permeability across the cell monolayer. While our previous publication has hinted at the potential of 4F to reduce Aβ accumulation in the brain parenchyma, the current findings demonstrated the protective effect of 4F in reducing Aβ 42 accumulation in the BBB endothelium of AD transgenic mice. These findings revealed the impact of a clinically tested agent, the HDL mimetic peptide 4F, on Aβ exposure to the BBB endothelium and offer novel mechanistic insights into potential therapeutic strategies to treat cerebrovascular dysfunction in AD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".