Amyloid-β Interactions with Chondroitin Sulfate-derived Monosaccharides and Disaccharides
Bibliographic record
Abstract
In Alzheimer's disease, the major pathological features are diffuse and senile plaques that are primarily composed of the amyloid-beta (A beta) peptide. It has been proposed that proteoglycans and glycosaminoglycans (GAG) facilitate amyloid fibril formation and/or stabilize the plaque aggregates. To develop effective therapeutics based on A beta-GAG interactions, understanding the A beta binding motif on the GAG chain is imperative. Using electron microscopy, fluorescence spectroscopy, and competitive inhibition ELISAs, we have evaluated the ability of chondroitin sulfate-derived monosaccharides and disaccharides to induce the structural changes in A beta that are associated with GAG interactions. Our results demonstrate that the disaccharides GalNAc-4-sulfate(4S), Delta UA-GalNAc-6-sulfate(6S), and Delta UA-GalNAc-4,6-sulfate(4S,6S), the iduronic acid-2-sulfate analogues, and the monosaccharides d-GalNAc-4S, d-GalNAc-6S, and d-GalNAc-4S,6S, but not d-GalNAc, d-GlcNAc, or Delta UA-GalNAc, induce the fibrillar features of A beta-GAG interactions. The binding affinities of all chondroitin sulfate-derived saccharides mimic those of the intact GAG chains. The sulfated monosaccharides and disaccharides compete with the intact chondroitin sulfate and heparin GAGs for A beta binding, as illustrated by competitive inhibition ELISAs. Therefore, the development of therapeutics based on the model of A beta-chondroitin sulfate binding may lead to effective inhibitors of the GAG-induced amyloid formation that is observed in vitro.
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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 | 0.000 |
| 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".