Transition Metal-Mediated DNA Adsorption on Polydopamine Nanoparticles
Bibliographic record
Abstract
Polydopamine (PDA) is a widely used universal coating for a broad range of materials. Interfacing PDA with various biomolecules, such as DNA, is critical for applications such as sensing, intracellular delivery, and material fabrication. Because of the negative surface charge of PDA at neutral pH, electrostatic repulsion exists between PDA and DNA. In previous studies, modified DNA or low pH was used to overcome this repulsion for DNA adsorption. More recently, divalent Ca 2+ was found to bridge DNA and PDA. Herein, we studied four transition metals (Mn 2+, Co 2+, Zn 2+, and Ni 2+ ) and compared their efficiencies with Ca 2+ for promoting DNA adsorption. These transition metals induced a more efficient and tighter DNA binding compared to Ca 2+ . In all these cases, the DNA phosphate backbone played a dominant role in adsorption, although DNA bases might also interact with strong binding metals such as Ni 2+ . Moreover, when the adsorption affinity was stronger, sensing was more selective to complementary DNA. Finally, aging of PDA appeared to be detrimental for DNA adsorption, which could be due to further oxidation of PDA. We showed that using Zn 2+ or Ni 2+ could considerably relieve the aging effect, while storing PDA at 4 °C could slow down aging.
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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) | 0.001 | 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".