Amyloidogenesis recapitulated in cell culture: a peptide inhibitor provides direct evidence for the role of heparan sulfate and suggests a new treatment strategy
Bibliographic record
Abstract
To date 22 different polypeptides, including Abeta in Alzheimer's disease and PrP(Sc) in prion disorders, are known to re-fold and assemble into highly organized fibrils, which associate with heparan sulfate (HS) proteoglycans to form tissue deposits called amyloid. Mononuclear phagocytes have long been thought to be involved in this process, and we describe a monocytic cell culture system that can transform the acute-phase protein serum amyloid A (SAA1.1) into AA-amyloid and appears to recapitulate all the main features of amyloidogenesis observed in vivo. These features in common include nucleation-dependent kinetics, identical proteolytic processing of SAA1.1, and co-deposition of HS with the fibrils. Heparin and polyvinylsulfonate previously reported to block AA-amyloidogenesis in mice are also effective inhibitors in this cell culture model. Furthermore, a synthetic peptide (27-mer) corresponding to a HS binding site of SAA, blocks amyloid deposition at a concentration that is several-orders-of-magnitude lower than any other peptide-based inhibitor previously reported. The 27-mer's inhibitory activity may target the amyloidogenic pathway specifically as it does not interfere with the binding of SAA to monocytes. These data provide direct evidence that SAA1.1:HS interactions are a critical step in AA-amyloidogenesis and suggest a novel treatment strategy for other amyloidoses.
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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) | 0.001 | 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) | 0.001 | 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".