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Record W2060085637 · doi:10.1021/ja037534v

Nanoparticles from Cationic Copolymer and DNA That Are Soluble and Stable in Common Organic Solvents

2003· article· en· W2060085637 on OpenAlexaff
Munia Ganguli, Kizhakkedathu Jayachandran, Souvik Maiti

Bibliographic record

VenueJournal of the American Chemical Society · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryCationic polymerizationTetrahydrofuranEthylene glycolCopolymerNanoparticleMicelleNanomaterialsDNAPolymer chemistryAcetonitrileOrganic chemistryCombinatorial chemistrySolventChemical engineeringAqueous solutionPolymer

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.247
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations45
Published2003
Admission routes1
Has abstractyes

Explore more

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