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Record W2784987215 · doi:10.1021/acs.langmuir.7b02822

Simple, Hackable, Size-Selective, Amine-Functionalized Fe-Oxide Nanoparticles for Biomedical Applications

2018· article· en· W2784987215 on OpenAlexafffund
P. K. Manna, Rachel Nickel, Yaroslav Wroczynskyj, Vinith Yathindranath, Jie Li, Song Liu, James A. Thliveris, Thomas Klonisch, Donald W. Miller, J. van Lierop

Bibliographic record

VenueLangmuir · 2018
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsAmine gas treatingNanoparticleSimple (philosophy)ChemistryNanotechnologyOxideAmine oxideSurface modificationChemical engineeringMaterials scienceCombinatorial chemistryOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A facile one-pot method for synthesizing amine-functionalized nonspherical Fe 3 O 4 nanoparticles in gram-scale quantities is presented using just a single source of iron (iron(II) chloride) and an amine (triethylamine). The amine not only transforms iron salt to Fe 3 O 4, but also directs the morphology of the nanoparticles along with the temperature of the reaction and functionalizes them, making the synthesis very economical. By modifying the surface further, these nanoparticles promise to offer useful biomedical applications. For example, after biocide coating, the particles are found to be 100% effective in deactivating methicillin-resistant Staphylococcus aureus (MRSA) bacteria in 2 h. Cellular-uptake studies using biocompatible EDTA–Na 3 ( N -(trimethoxysilyl-propyl)ethylenediaminetriacetate, trisodium salt)-coated nanoparticles in human glioblastoma U-251 cells show that the majority of the particles are internalized by the cells in the presence of a small dc-magnetic field, making these particles a potential candidate as drug carriers for magnetic field-targeted delivery and hyperthermia.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.001

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 head0.015
GPT teacher head0.271
Teacher spread0.255 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2018
Admission routes2
Has abstractyes

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