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Record W2077966049 · doi:10.1039/b802808g

Dendronised block copolymers as potential vectors for gene transfection

2008· article· en· W2077966049 on OpenAlexfundno aff
Tony J. Wigglesworth, Francisco José Soares Teixeira, Fabian Axthelm, Sara Eisler, Noémi Csaba, Hans P. Merkle, Wolfgang Meier, François Diederich

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Center of Competence in Research Chemical Biology
KeywordsChemistryGene deliveryTransfectionEthylene glycolCopolymerDNACationic polymerizationHeLaMicelleBiophysicsPolymerDynamic light scatteringGreen fluorescent proteinIn vitroPolymer chemistryBiochemistryGeneNanotechnologyNanoparticleOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

A series of block copolymers containing a dendronised cationic block for efficient DNA binding and a poly(ethylene glycol) block for encapsulation of the complex were synthesised in a modular fashion using a combination of click chemistry and ring-opening metathesis polymerisation. DNA binding experiments, investigated using gel electrophoresis, dynamic light scattering and transmission electron microscopy, showed that all polymers prepared in this study strongly complex DNA and self-assemble into polyion complex micelles with apparent hydrodynamic radii ranging from 20-120 nm at physiological pH (7.4). The in vitro transfection efficiency and toxicity of these potential non-viral vectors were also evaluated in HeLadouble dagger cells using plasmid DNA encoding for green fluorescent protein as the reporter gene.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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.

Opus teacher head0.006
GPT teacher head0.214
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2008
Admission routes1
Has abstractyes

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