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Record W2103351739 · doi:10.1039/c5nr05826k

Adsorption of doxorubicin on citrate-capped gold nanoparticles: insights into engineering potent chemotherapeutic delivery systems

2015· article· en· W2103351739 on OpenAlexafffund
Dennis Curry, Amanda Cameron, Bruce C. MacDonald, Collins Nganou, Hope Scheller, James R. Marsh, Stefanie Beale, Mingsheng Lü, Zhi Shan, Rajendran Kaliaperumal, Heping Xu, Mark R. Servos, Craig Bennett, Stephanie MacQuarrie, Ken D. Oakes, Martin Mkandawire, Xu Zhang

Bibliographic record

VenueNanoscale · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsCape Breton Regional HospitalUniversity of WaterlooAcadia UniversityCape Breton University
FundersCanadian Institutes of Health Research
KeywordsDoxorubicinDrug deliveryAdsorptionNanoparticleNanotechnologyColloidal goldCombinatorial chemistryChemistryMaterials scienceMedicineOrganic chemistryChemotherapy

Abstract

fetched live from OpenAlex

Gold nanomaterials have received great interest for their use in cancer theranostic applications over the past two decades. Many gold nanoparticle-based drug delivery system designs rely on adsorbed ligands such as DNA or cleavable linkers to load therapeutic cargo. The heightened research interest was recently demonstrated in the simple design of nanoparticle-drug conjugates wherein drug molecules are directly adsorbed onto the as-synthesized nanoparticle surface. The potent chemotherapeutic, doxorubicin often serves as a model drug for gold nanoparticle-based delivery platforms; however, the specific interaction facilitating adsorption in this system remains understudied. Here, for the first time, we propose empirical and theoretical evidence suggestive of the main adsorption process where (1) hydrophobic forces drive doxorubicin towards the gold nanoparticle surface before (2) cation-π interactions and gold-carbonyl coordination between the drug molecule and the cations on AuNP surface facilitate DOX adsorption. In addition, biologically relevant compounds, such as serum albumin and glutathione, were shown to enhance desorption of loaded drug molecules from AuNP at physiologically relevant concentrations, providing insight into the drug release and in vivo stability of such drug 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 score0.003
Threshold uncertainty score0.981

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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

Citations88
Published2015
Admission routes2
Has abstractyes

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