Nanoparticles from Cationic Copolymer and DNA That Are Soluble and Stable in Common Organic Solvents
Bibliographic record
Abstract
DNA by virtue of its superlative ability to self-assemble has found use beyond biological research in the design and fabrication of nanomaterials. However, developing novel DNA-based materials for chemical applications might be restricted due to the insoluble nature of DNA in most common organic solvents. In this Communication, we are reporting the first demonstration of making DNA soluble in a variety of nonbiological solvents such as acetonitrile, benzene, dimethyl sulfoxide (DMSO), and tetrahydrofuran with the help of poly(ethylene glycol) (PEG)-based cationic random copolymers. Because of complex formation between cationic copolymer and anionic DNA, nanoparticles are formed. These nanoparticles are expected to exhibit micelle-like structures with a nanometric core of cationic units neutralized by phosphate anions of DNA, surrounded by a shell of PEG segments. As PEG is soluble in the organic solvents used in this study, nanoparticles are stable in these solvents, making entrapped DNA soluble in these organic solvents.
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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 | 0.001 | 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".