DNA nanostructures prevent the formation of and convert toxic amyloid proteospecies into cytocompatible and biodegradable spherical complexes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The deposition of insoluble proteinaceous aggregates in the form of amyloid fibrils within the extracellular space of tissues is associated with numerous diseases. The development of molecular approaches to arrest amyloid formation and prevent cellular degeneration remains very challenging due to the complexity of the process of protein aggregation, which encompasses an infinite array of conformations and quaternary structures. Polyanionic biopolymers, such as glycosaminoglycans and RNAs, have been shown to modulate the self‐assembly of amyloidogenic polypeptides and to reduce the toxicity induced by the formation of oligomeric and/or pre‐fibrillar proteospecies. This study evaluates the effects of double‐stranded DNA (dsDNA) nanostructures (1D, 2D, and 3D) on amyloid self‐assembly, fibril disaggregation, and the cytotoxicity associated with amyloidogenesis. Using the islet amyloid polypeptide (IAPP) whose pancreatic accumulation is the hallmark of type 2 diabetes, it was observed that dsDNA nanostructures inhibit amyloid formation by inducing the formation of spherical complexes in which the peptide adopts a random coil conformation. Interestingly, the DNA nanostructures showed a persistent ability to disassemble enzymatically and thermodynamically stable amyloid fibrils into nanoscale DNA/IAPP entities that are fully compatible with β‐pancreatic cells and are biodegradable by proteolysis. Notably, dsDNA nanostructures avidly trapped highly toxic soluble oligomeric species in complete cell culture media and converted them into non‐toxic binary complexes. Overall, these results expose the potent modulatory effects of dsDNA on amyloidogenic pathways, and these DNA nanoscaffolds could be used as a source of inspiration for the design of molecules to fight amyloid‐related disorders.
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.
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 it