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Record W2120322972 · doi:10.1039/b821583a

Effect of mechanical properties of hydrogel nanoparticles on macrophage cell uptake

2009· article· en· W2120322972 on OpenAlexaff
Xavier Banquy, Fernando Suárez‐Obando, Anteneh Argaw, Jean‐Michel Rabanel, Peter Grütter, Jean‐François Bouchard, Patrice Hildgen, Suzanne Giasson

Bibliographic record

VenueSoft Matter · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsInternalizationPinocytosisAcrylamideChemistryBiophysicsIntracellularKineticsNanoparticleDrug deliveryEndocytosisCellNanotechnologyMaterials scienceBiochemistryPolymerOrganic chemistryMonomer

Abstract

fetched live from OpenAlex

Uptake and intracellular trafficking of hydrogel nanoparticles (NPs) of N,N-diethyl acrylamide and 2-hydroxyethyl methacrylate crosslinked with N,N′-methylene-bis-acrylamide were studied with a RAW 264.7 murine macrophage cell line. Results show that the uptake rate, the mechanism of internalization and the concentration of internalized NPs are correlated to the NP Young modulus. Soft NPs are found to be internalized preferentially via macropinocytosis while the uptake of stiff NPs is mediated by a clathrin-dependent mechanism. NPs with an intermediate Young modulus exhibit multiple uptake mechanisms. The accumulation rate of the NPs into lysosomal compartments of the cell is also dependent on the NP elasticity. Our results suggest that control over the mechanical properties of hydrogel NPs can be used to tailor the cellular uptake mechanism and kinetics of drug delivery.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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

Citations259
Published2009
Admission routes1
Has abstractyes

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