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Record W2001360443 · doi:10.1002/jbm.a.34176

Synthesis of cationic magnetic nanoparticles and evaluation of their gene delivery efficacy in Hep G2 cells

2012· article· en· W2001360443 on OpenAlexaff
J. J. CHEN, Marya Ahmed, Qingxia Liu, Ravin Narain

Bibliographic record

VenueJournal of Biomedical Materials Research Part A · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsAlberta Glycomics CentreUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceCationic polymerizationNanoparticleGene deliveryMagnetic nanoparticlesHep G2NanotechnologyGenetic enhancementCell cultureGeneBiochemistryBiologyPolymer chemistryGenetics

Abstract

fetched live from OpenAlex

Well-defined cationic polymers were synthesized via the reversible addition fragmentation chain transfer polymerization and were subsequently used as stabilizer for the synthesis of cationic iron-oxide magnetic nanoparticles via the coprecipitation method. The surface-coated iron-oxide nanoparticles made stable suspension in water and were characterized by a range of techniques such as dynamic light scattering, transmission electron microscopy, and thermogravimetric analysis. The presence of protonated amine and carbohydrate residues onto the surface of the nanoparticles allowed their facile complexation with DNA and the resulting nanocomplexes were then studied for their efficacy as DNA carriers in Hep G2 cells.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 head0.060
GPT teacher head0.353
Teacher spread0.293 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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