Attaching DNA to Gold Nanoparticles With a Protein Corona
Bibliographic record
Abstract
DNA-functionalized gold nanoparticles (AuNPs) have been widely used in directed assembly of materials, biosensors, and drug delivery. This conjugate may encounter proteins in these applications and proteins may affect not only DNA adsorption but also the function of the attached DNA. Bovine serum albumin (BSA) with many cysteine residues can strongly adsorb on AuNPs and this conjugate showed high colloidal stability against salt, acid and base. Similar protection effects were also observed with a few other common proteins including catalase, hemoglobin, glucose oxidase, and horseradish peroxidase. DNA oligonucleotides without a thiol label can hardly displace adsorbed BSA, and BSA cannot displace pre-adsorbed DNA either, indicating a strongly kinetically controlled system. Thiolated DNA can be attached at a low density on the AuNPs with a BSA corona. The BSA corona did not facilitate the hybridization of the conjugated DNA, while a smaller peptide, glutathione allowed faster hybridization. Overall, proteins increase the colloidal stability of AuNPs, and they do not perturb the gold-thiol bond in the DNA conjugate, although a large protein corona may inhibit the hybridization function of DNA.
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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 | 0.001 | 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".