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Comparative cytotoxicity of gold–doxorubicin and InP–doxorubicin conjugates

2012· article· en· W2056027032 on OpenAlexaff
Xuan Zhang, Hicham Chibli, Dekun Kong, Jay Nadeau

Bibliographic record

VenueNanotechnology · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsDoxorubicinCytotoxicityConjugateDrug deliveryMaterials scienceColloidal goldBiophysicsNanoparticleConfocal microscopyNanotechnologyChemistryIn vitroBiochemistryBiologyChemotherapyCell biology

Abstract

fetched live from OpenAlex

Direct comparisons of different types of nanoparticles for drug delivery have seldom been performed. In this study we compare the physical properties and cellular activity of doxorubicin (Dox) conjugates to gold nanoparticles (Au) and InP quantum dots of comparable diameter. Although the Au particles alone are non-toxic and InP is moderately toxic, Au-Dox is more effective than InP-Dox against the Dox-resistant B16 melanoma cell line. Light exposure does not augment the efficacy of InP-Dox, suggesting that conjugates are breaking down. Electron and confocal microscopy and atomic absorption spectroscopy reveal that over 60% of the Au-Dox conjugates reach the cell nucleus. In contrast, InP-Dox enters cell nuclei to a very limited extent, although liberated Dox from the conjugates does eventually reach the nucleus. These observations are attributed to faster Dox release from Au conjugates under endosomal conditions, greater aggregation of InP-Dox with cytoplasmic proteins, and adherence of InP to membranes. These findings have important implications for design of active drug-nanoparticle conjugates.

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 score0.027
Threshold uncertainty score0.411

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 head0.025
GPT teacher head0.267
Teacher spread0.242 · 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

Citations28
Published2012
Admission routes1
Has abstractyes

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