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Record W2163701623 · doi:10.1002/elps.200800737

MEKC‐LIF analysis of rhodamine123 delivered by carbon nanotubes in K562 cells

2009· article· en· W2163701623 on OpenAlexaff
Ruibin Li, Ren’an Wu, Minghuo Wu, Hanfa Zou, Hong Ma, Ling Yang, X. Chris Le

Bibliographic record

VenueElectrophoresis · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCarbon nanotubeK562 cellsQuenching (fluorescence)AdsorptionMultiple drug resistanceMaterials scienceNanotechnologyChemistryCellFluorescenceOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Oxidized single-walled carbon nanotubes (o-SWNTs) were employed as the drug carriers to deliver the small molecules of Rhodamine123 (Rho123) into the K562 cells via physical adsorption. However, due to the fluorescence quenching of Rho123 on carbon nanotubes, the quantitative determination of Rho123 in cells is difficult. Based on the MEKC coupled with LIF detection, a quantitative approach was developed for the determination of Rho123 delivered into K562 cells by o-SWNTs. Where the adsorbed Rho123 on o-SWNTs could be desorbed by SDS in running buffer and be simultaneously separated with o-SWNTs due to the differences of their electrophoretic mobility by applying the electric potential at the both ends of capillary. Using this approach, the intracellular uptakes of Rho123 in multidrug-resistant and multidrug-sensitive leukemia cells were quantified, and the results showed that o-SWNTs could be used as the potential drug carriers to deliver small molecules into cells via the physical adsorption along with the circumventing of multidrug resistance of leukemia cells.

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 score0.002
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.003
GPT teacher head0.231
Teacher spread0.227 · 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

Citations10
Published2009
Admission routes1
Has abstractyes

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