Rapid Immobilization of Oligonucleotides at High Density on Semiconductor Quantum Dots and Gold Nanoparticles
Bibliographic record
Abstract
Oligonucleotide-coated nanoparticles (NPs) have been used in numerous applications such as bioassays, as intracellular probes, and for drug delivery. One challenge that is confronted in the preparation of oligonucleotide-NP conjugates is derived from surface charge because nanoparticles are often stabilized and made water-soluble with a coating of negatively charged capping ligands. Therefore, an electrostatic repulsion is present when attempting to conjugate oligonucleotides. The result is that the conjugation can be a slow process, sometimes requiring 1 to 2 days to equilibrate at the highest surface density. The effect is compounded by electrostatic repulsion between neighboring oligonucleotide strands on the NP surfaces, which tends to lower the surface density. Herein, we report a novel method that enables conjugation in less than 1 min with a surface density of oligonucleotides up to the theoretical physical limit of occupancy. Negatively charged NPs are first adsorbed onto the surface of positively charged magnetic beads (MBs) to create MB-NP conjugates. Oligonucleotides are subsequently electrostatically adsorbed onto the MB surfaces when added to a suspension of MB-NP conjugates. This creates an oligonucleotide concentration 10 5 to 10 6 greater than in bulk solution in the vicinity of the nanoparticles, resulting in the promotion of the kinetics by over 1000-fold and achieving the maximum density possible for the conjugation reaction.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".