Functionalized DNA nanostructures as scaffolds for guided mineralization
Bibliographic record
Abstract
The field of DNA nanotechnology uses synthetic DNA strands as building blocks for designing complex shapes in one-, two- and three-dimensions. Here, we investigate whether DNA nanostructures are feasible platforms for the precise organization of polyaspartic acid (pAsp), a known mineral carrier, with a goal towards biomimetic mineralization for enamel regeneration. We describe the preparation of DNA-pAsp conjugates and their subsequent assembly into ordered nanostructures. Covalent attachment of pAsp to DNA was noted to hinder DNA nanostructure formation past a certain threshold (50% pAsp) when tested on a previously published DNA system. However, a simplified double stranded DNA system (3sDH system) was more robust and efficient in its pAsp incorporation. In addition, the 3sDH system was successful in organizing mineral inducing groups in one dimension at repeating intervals of 28.7 ± 4.0 nm, as determined by atomic force microscopy. Our results demonstrate that DNA nanostructures can be functionalized with pAsp and act as a platform to investigate guided mineralization.
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 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 | 0.001 |
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".