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Record W2000061504 · doi:10.1021/ac8004555

Assessment of Cytotoxicity of Quantum Dots and Gold Nanoparticles Using Cell-Based Impedance Spectroscopy

2008· article· en· W2000061504 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnalytical Chemistry · 2008
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsNational Research Council CanadaBiotechnology Research Institute
Fundersnot available
KeywordsQuantum dotChemistryCytotoxicityCadmium selenideNanomaterialsCadmiumColloidal goldNanoparticleDielectric spectroscopyNanotechnologyBiophysicsAnalytical Chemistry (journal)ChromatographyIn vitroBiochemistryMaterials sciencePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A continuous online technique based on electric cell-substrate impedance sensing (ECIS) was demonstrated for measuring the concentration and time response function of fibroblastic V79 cells exposed to nanomaterials such as quantum dots (QDs) and fluorescent gold nanoparticles. The half-inhibition concentration, (ECIS50), the required concentration to attain 50% inhibition of the cytotoxic response, was estimated from the response function to ascertain cytotoxicity during the course of measurement. The ECIS50 values agreed well with the results obtained using the standard neutral red assay. Cadmium selenide quantum dots showed direct cytotoxicity with the ECIS assay. For the cadmium telluride quantum dots, significant toxicity could be assigned to free cadmium, although additional toxicity could be attributed to the QDs per se. The QDs synthesized with indium gallium phosphide and the fluorescent gold nanoparticles were not cytotoxic.

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.

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 score0.078
Threshold uncertainty score0.408

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 head0.033
GPT teacher head0.286
Teacher spread0.253 · 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