Abstract 574: High-Density Lipoproteins Suppress Amyloid Beta Induced Human Brain Microvascular Endothelial Cell Activation
Bibliographic record
Abstract
Introduction: Epidemiological studies suggest a link between plasma high-density lipoprotein (HDL) cholesterol levels and Alzheimer’s disease (AD) risk through mechanisms that are not understood. We hypothesize that HDL protects against AD through actions at the blood-brain-barrier. HDL has vasoprotective functions in large peripheral arteries, however, it is unknown if these functions extend to cerebral vessels to reduce the contribution of cerebrovascular dysfunction in AD pathogenesis. We investigated in vitro interactions between HDL and amyloid beta (Aβ), the toxic peptide known to accumulate in AD, in peripheral and brain-derived endothelial cells (EC). Methods: HDL was isolated by density gradient ultracentrifugation and added to human umbilical vein endothelial cells (HUVEC) or human cerebral microvascular endothelial cells (hCMEC/D3). Cell activation was measured by counting adhered labelled peripheral blood mononuclear cells (PBMC) after stimulation with tumour necrosis factor α (TNFα) or Aβ. Aβ binding and uptake into cells was measured using ELISA and immunofluorescence. All experiments included at least 4 independent replicates. Results: We demonstrate that HDL attenuates Aβ-induced EC activation independent of nitric oxide production, miR-233 and changes in adhesion molecule expression. Rather, HDL acts through scavenger receptor BI to block Aβ uptake into ECs and, in vitro , can maintain Aβ in a soluble state. We validated our results using three dimensional engineered vessels composed of primary human endothelial and smooth muscle cells. Following Aβ addition to the abluminal (brain) side, we demonstrated that HDL circulated within the lumen attenuates EC activation, again independent of intracellular adhesion molecule changes. Conclusions: We show that the anti-inflammatory activities of HDL extend to cerebrovascular endothelial cells and work to suppress Aβ-induced activation through a novel mechanism involving the inhibition of Aβ binding and uptake into cells through SR-BI. The protective role for HDL against Aβ may explain the epidemiological evidence supporting a protective effect of high plasma HDL cholesterol levels against dementia.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".