MétaCan
Menu
Back to cohort

Impact of carbondiimide crosslinker used for magnetic carbon nanotube mediated GFP plasmid delivery

2011· article· en· W1979367435 on OpenAlexafffund
Yuzhi Hao, Peng Xu, Chuan He, Xiaoyan Yang, Min Huang, James Z. Xing, Jie Chen

Bibliographic record

VenueNanotechnology · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsInstitute of Cancer ResearchNational Institute for NanotechnologyUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCalifornia HIV/AIDS Research Program
KeywordsMaterials scienceBiomoleculeFluorescein isothiocyanateFluoresceinCytotoxicityPropidium iodideFlow cytometryFluorescence microscopeBiophysicsFluorescenceGreen fluorescent proteinCarbon nanotubeNanotechnologyNanostructureNuclear chemistryMolecular biologyApoptosisProgrammed cell deathBiochemistryChemistryBiologyIn vitro

Abstract

fetched live from OpenAlex

1-Ethyl-3-(3-dimethylaminopropyl) carbondiimide hydrochloride (EDC) is commonly used as a crosslinker to help bind biomolecules, such as DNA plasmids, with nanostructures. However, EDC often remains, after a crosslink reaction, in the micro-aperture of the nanostructure, e.g., carbon nanotube. The remaining EDC shows positive green fluorescent signals and makes a nanostructure with a strong cytotoxicity which induces cell death. The toxicity of EDC was confirmed on a breast cancer cell line (MCF-7) and two leukemic cell lines (THP-1 and KG-1). The MCF-7 cells mainly underwent necrosis after treatment with EDC, which was verified by fluorescein isothiocyanate (FITC) annexin V staining, video microscopy and scanning electronic microscopy (SEM). If the EDC was not removed completely, the nanostructures with remaining EDC produced a green fluorescent background that could interfere with flow cytometry (FACS) measurement and result in false information about GFP plasmid delivery. Effective methods to remove residual EDC on macromolecules were also developed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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.

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

Citations38
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueNanotechnologySame topicCarbon Nanotubes in CompositesFrench-language works237,207