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Record W2078748900 · doi:10.1002/mabi.201000402

Impact of Lipid Substitution on Assembly and Delivery of siRNA by Cationic Polymers

2011· article· en· W2078748900 on OpenAlexafffund
Hamidreza Montazeri Aliabadi, Breanne Landry, Remant K. Bahadur, Artphop Neamnark, Orawan Suwantong, Hasan Uludağ

Bibliographic record

VenueMacromolecular Bioscience · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsPolymerChemistryCationic polymerizationGene silencingBiophysicsIntracellularSmall interfering RNAPolymer chemistryBiochemistryCombinatorial chemistryTransfectionOrganic chemistryBiologyGene

Abstract

fetched live from OpenAlex

Characterization of a polymer library engineered to enhance their ability to protect and deliver their nucleotide cargo to the cells is reported. The ζ-potential continuously increased with higher polymer:siRNA weight ratio, and the ζ-potential of lipid-modified polymers:siRNA complexes were higher than PEI2 at all ratios. At polymer:siRNA ratio of 1:1, all lipid-substituted polymers showed complete protection against degradation. Lipid-modified polymers significantly increased the cellular uptake of siRNA complexes and down-regulation of GAPDH and P-gp (max. 66% and 67%, respectively). The results indicate that hydrophobic modification of low molecular PEI could render this otherwise ineffective polymer to a safe effective delivery system for intracellular siRNA delivery and protein silencing.

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 score0.002

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)0.0010.000

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 head0.014
GPT teacher head0.250
Teacher spread0.235 · 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

Citations84
Published2011
Admission routes2
Has abstractyes

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