Site‐Specific Disulfide‐Mediated Crosslinking of DNA Nanocubes for Enhanced Biological Applications
Bibliographic record
Abstract
The development of DNA nanotechnology has enabled the creation of diverse nanomaterials with significant potential in biological applications, such as sensing or drug delivery. From DNA origami to wireframe nanostructures, several strategies have been developed to deliver nucleic acid therapeutics into cells. However, these self-assembled structures suffer from poor stability in biological media due to low concentrations of divalent cations, degradation by nucleases, and thermal denaturation. Herein, a site-specific crosslinking method based on thiol-disulfide exchange to stabilize a wireframe DNA nanocube is developed. With nearly quantitative crosslinking yields, the structure retains its structural integrity in conditions that mimic physiological environments. This results in improved cellular uptake, likely due to more favorable interaction with cell-surface scavenger receptors, followed by endocytosis. This study paves the way for in vivo applications of DNA wireframe nanostructures by removing one of the major bottlenecks for their translation from in vitro to preclinical work.
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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".