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Record W2970473523 · doi:10.1039/c9ra03668g

Model Affitin and PEG modifications onto siRNA lipid nanocapsules: cell uptake and <i>in vivo</i> biodistribution improvements

2019· article· en· W2970473523 on OpenAlexafffund
Pauline Resnier, Élise Lepeltier, Anthea Lucrezia Emina, Natacha Galopin, Jérôme Bejaud, Stéphanie David, Caroline Ballet, Thierry Benvegnu, Frédéric Pecorari, Igor Chourpa, Jean‐Pierre Benoît, Catherine Passirani

Bibliographic record

VenueRSC Advances · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsCanadian Nautical Research Society
FundersLigue Contre le CancerScience Foundation IrelandUniversite AngersCentre National de la Recherche ScientifiqueCanadian Institute for Theoretical Astrophysics
KeywordsPEGylationBiodistributionNanocarriersNanocapsulesIn vivoPEG ratioSmall interfering RNAChemistryBiophysicsConfocal microscopyInternalizationPolyethylene glycolFörster resonance energy transferFlow cytometryMelanomaNanomedicineCancer researchCellIn vitroDrug deliveryTransfectionMolecular biologyMaterials scienceNanotechnologyCell biologyNanoparticleBiochemistryMedicineFluorescenceBiology

Abstract

fetched live from OpenAlex

biofluorescence imaging (BFI), to evaluate the potential tumor targeting ability. The post-insertion of DSPE-PEG induced a strong decrease of the internalization into melanoma cells compared to TE-PEG modification. Both PEG polymer decorations induced a great plasma protection of siRNA but only DSPE-PEG led to stealth properties, even at low concentration (5 mM). The Affitin grafting by thiolation of DSPE-PEG was validated on siRNA LNCs. DSPE-PEG-Affitin LNCs were not detected in this melanoma tumor model but did not show unspecific accumulation in organs. DSPE-PEG and TE-PEG LNCs induced a significant intratumoral accumulation of modified LNCs.

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 score0.028
Threshold uncertainty score0.458

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 head0.238
Teacher spread0.228 · 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

Citations16
Published2019
Admission routes2
Has abstractyes

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