The cholesteryl transfer protein and apolipoprotein E in Alzheimer's disease models
Bibliographic record
Abstract
Alzheimer’s disease (AD) is the most common form of dementia affecting about 500,000 people in Canada and 24 million people worldwide. As AD has been known to be heavily related to lipid & cholesterol metabolism both in the brain and in the periphery, as evidenced by both high plasma LDL levels and increased occurrence of the apolipoprotein E ε4 polymorphism being well-established risk factors, it is important to develop models highly aligned to the human AD profile, particularly in terms of lipid metabolism-related processes. Our lab found that when cholesteryl ester transfer protein (CETP), a protein that shuttles cholesteryl esters from HDL particles to VLDL and LDL particles, is expressed in mice under the human promoter, a humanized profile of rodent lipoprotein particles occurs. Remarkably, when CETP mice were crossed with the Thy1-APP Tg Alzheimer mouse model expressing human APP, a 5-fold increase in soluble and insoluble Aβ levels in the brains of double transgenic mutants were seen. In my MSc research, I found that human apolipoprotein E4 (hApoE4)-expressing astrocytes have larger and more lipid droplets compared to human apolipoprotein E3 (hApoE3)-expressing astrocytes. Furthermore, I found that recombinant CETP (rCETP) can modulate astrocytic lipoproteins in cell-free systems in dependence of hApoE isoform and CETP activity. Despite this, neither secreted CETP from stably CETP-expressing hApoE astrocytes nor exogenous rCETP had activity-dependent effects on Aβ levels in astrocyte-SY5Y co-culture systems. Finally, in my master’s thesis, I developed and characterized liver-specific CETP viruses with high in vivo infectivity, which can be used for future analyses of whether peripheral CETP confers changes in brain Aβ production and cholesterol/lipoprotein profiles in both the CNS and periphery
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".