Adsorption of DNA Oligonucleotides by Boronic Acid-Functionalized Hydrogel Nanoparticles
Bibliographic record
Abstract
Boronic acid-functionalized hydrogels were commonly used for covalent binding of cis -diol-contained molecules such as glucose, but noncovalent adsorption by boronic acids was less studied. DNA as an important polymer has been used to enhance the function of hydrogels including boronic acid-containing gels. In this work, noncovalent interactions between DNA oligonucleotides and boronic acid-containing hydrogel nanoparticles were studied in detail. The gels were composed of either poly( N -isopropylacrylamide) or with additional 5.6 mol % of 3-acrylamidophenylboronic acid (AAPBA). DNA adsorption on the AAPBA-containing gels was achieved with a high salt concentration, which can be explained by electrostatic repulsion between DNA and boronic acid. The critical role of boronic acid was confirmed by adding competing cis -diol-containing molecules such as glucose, fructose, and cytidine. Hydrogen bonding and hydrophobic interactions are important for DNA adsorption based on inhibited adsorption by urea and dimethyl sulfoxide. Polycytosine DNA showed a higher adsorption capacity compared to the other three types of DNA homopolymers. When T 15 and T 14 -rU were compared, no covalent binding was detected for T 14 -rU, suggesting that a single terminal diol was insufficient to support covalent binding at the low concentration of DNA used. Finally, the boronic acid-containing gels were able to adsorb an aptamer and inhibit its binding function. Binding was rescued by adding glucose to block the boronic acids. This study demonstrates noncovalent boronic acid interactions with DNA, and this information could be useful for designing and optimization of related biosensors and materials.
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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".