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Record W2135047086 · doi:10.1002/app.35179

Improved transfection efficiency of chitosan‐DNA complexes employing reverse transfection

2011· article· en· W2135047086 on OpenAlexaff
Surendra Nimesh, Amit Saxena, Ajeet Kumar, Ramesh Chandra

Bibliographic record

VenueJournal of Applied Polymer Science · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsMontreal Clinical Research Institute
Fundersnot available
KeywordsTransfectionChitosanLipofectamineGreen fluorescent proteinChemistryMolecular biologyCytotoxicityDNADynamic light scatteringBiophysicsMaterials scienceBiologyNanotechnologyIn vitroBiochemistryGeneRecombinant DNANanoparticle

Abstract

fetched live from OpenAlex

Abstract The present study was designed to systematically compare the conventional and reverse transfection methodologies for chitosan/DNA complexes using a low molecular weight (MW) chitosan. The hydrodynamic diameter of the complexes, measured by Dynamic Light Scattering (DLS) was found to be ∼ 216 nm and TEM investigations showed spherical and compact complexes with an average size of 200 nm. The transfection efficiency of chitosan using the two methodologies was assessed by employing reporter gene coding for green fluorescent protein (GFP) and luciferase. More than 50% of HEK 293 cells were transfected when transfection done using reverse transfection strategy at pH 6.5 with 10% serum for 24 h followed by media replenishment with pH 7.4 with 10% serum for an additional 24 h period. Also, the cytotoxicity of chitosan/DNA complexes was also considerably lower than the commercially available transfection reagent lipofectamine. Our investigation concludes that maximal transgene expression levels could be achieved using reverse transfection where the chitosan/DNA complexes are pre‐incubated on the plate surface followed by plating of cells at pH 6.5 with 10% serum for 24h and media resupplemented with pH 7.4 with 10% serum for an additional 24 h period. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

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 score0.009
Threshold uncertainty score0.384

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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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