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Record W2847455257 · doi:10.2147/ijn.s164393

Lyophilization and stability of antibody-conjugated mesoporous silica nanoparticle with cationic polymer and PEG for siRNA delivery

2018· article· en· W2847455257 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Nanomedicine · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsnot available
FundersNational Institutes of HealthNational Cancer InstituteUniversity of TorontoProspect Creek FoundationNational Center for Advancing Translational SciencesOregon Health and Science University
KeywordsNanoparticleMaterials sciencePolymerPolyethyleniminePEG ratioChemical engineeringFreeze-dryingConjugated systemChemical stabilityNanotechnologyChemistryChromatographyBiochemistryTransfection

Abstract

fetched live from OpenAlex

INTRODUCTION: Long-term stability of therapeutic candidates is necessary toward their clinical applications. For most nanoparticle systems formulated in aqueous solutions, lyophilization or freeze-drying is a common method to ensure long-term stability. While lyophilization of lipid, polymeric, or inorganic nanoparticles have been studied, little has been reported on lyophilization and stability of hybrid nanoparticle systems, consisting of polymers, inorganic particles, and antibody. Lyophilization of complex nanoparticle systems can be challenging with respect to preserving physicochemical properties and the biological activities of the materials. We recently reported an effective small-interfering RNA (siRNA) nanoparticle carrier consisting of 50-nm mesoporous silica nanoparticles decorated with a copolymer of polyethylenimine and polyethyleneglycol, and antibody. MATERIALS AND METHODS: Toward future personalized medicine, the nanoparticle carriers were lyophilized alone and loaded with siRNA upon reconstitution by a few minutes of simple mixing in phosphate-buffered saline. Herein, we optimize the lyophilization of the nanoparticles in terms of buffers, lyoprotectants, reconstitution, and time and temperature of freezing and drying steps, and monitor the physical and chemical properties (reconstitution, hydrodynamic size, charge, and siRNA loading) and biological activities (gene silencing, cancer cell killing) of the materials after storing at various temperatures and times. RESULTS: The material was best formulated in Tris-HCl buffer with 5% w/w trehalose. Freezing step was performed at -55°C for 3 h, followed by a primary drying step at -40°C (100 µBar) for 24 h and a secondary drying step at 20°C (20 µBar) for 12 h. The lyophilized material can be stored stably for 2 months at 4°C and at least 6 months at -20°C. CONCLUSION: We successfully developed the lyophilization process that should be applicable to other similar nanoparticle systems consisting of inorganic nanoparticle cores modified with cationic polymers, PEG, and antibodies.

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.

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 score0.003
Threshold uncertainty score0.219

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 head0.010
GPT teacher head0.275
Teacher spread0.265 · 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