Lipid Rafts Act as a Common Platform for Amyloid-β Oligomer-Induced Alzheimer’s Disease Pathology
Bibliographic record
Abstract
BACKGROUND: Amyloid-β (Aβ) oligomers induce the overproduction of phosphorylated tau and neurodegeneration. These cascades gradually cause cognitive impairment in Alzheimer's disease (AD). While each pathological event in AD has been studied in detail separately, the spatial and temporal relationships between pathological events in AD remain unclear. OBJECTIVE: We demonstrated that lipid rafts function as a common platform for the pathological cascades of AD. METHODS: Cellular and synaptosomal lipid rafts were prepared from the brains of Aβ amyloid model mice (Tg2576 mice) and double transgenic mice (Tg2576 x TgTauP301L mice) and longitudinally analyzed. RESULTS: Aβ dimers, the cellular prion protein (PrPc), and Aβ dimer/PrPc complexes were detected in the lipid rafts. The levels of Fyn, the phosphorylated NR2B subunit of the N-methyl-D-aspartate receptor, glycogen synthase kinase 3β, total tau, phosphorylated tau, and tau oligomers increased with Aβ dimer accumulation in both the cellular and synaptosomal lipid rafts. Increases in the levels of these molecules were first seen at 6 months of age and corresponded with the early stages of Aβ accumulation in the amyloid model mice. CONCLUSION: Lipid rafts act as a common platform for the progression of AD pathology. The findings of this study suggest a novel therapeutic approach to AD, involving the modification of lipid raft components and the inhibition of their roles in the sequential pathological events of AD.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".