Biophysical characteristics of lipid‐induced Aβ oligomers correlate to distinctive phenotypes in transgenic mice
Bibliographic record
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects cognition and memory. Recent advances have helped identify many clinical sub-types in AD. Mounting evidence point toward structural polymorphism among fibrillar aggregates of amyloid-β (Aβ) to being responsible for the phenotypes and clinical manifestations. In the emerging paradigm of polymorphism and prion-like propagation of aggregates in AD, the role of low molecular weight soluble oligomers, which are long known to be the primary toxic agents, in effecting phenotypes remains inconspicuous. In this study, we present the characterization of three soluble oligomers of Aβ42, namely 14LPOs, 16LPOs, and GM1Os with discreet biophysical and biochemical properties generated using lysophosphatidyl glycerols and GM1 gangliosides. The results indicate that the oligomers share some biophysical similarities but display distinctive differences with GM1Os. Unlike the other two, GM1Os were observed to be complexed with the lipid upon isolation. It also differs mainly in detection by conformation-sensitive dyes and conformation-specific antibodies, temperature and enzymatic stability, and in the ability to propagate morphologically-distinct fibrils. GM1Os also show distinguishable biochemical behavior with pronounced neuronal toxicity. Furthermore, all the oligomers induce cerebral amyloid angiopathy (CAA) and plaque burden in transgenic AD mice, which seems to be a consistent feature among all lipid-derived oligomers, but 16LPOs and GM1Os displayed significantly higher effect than the others. These results establish a correlation between molecular features of Aβ42 oligomers and their distinguishable effects in transgenic AD mice attuned by lipid characteristics, and therefore help bridge the knowledge gap in understanding how oligomer conformers could elicit AD phenotypes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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".