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Record W2050764344 · doi:10.1021/ac025848f

Assessment of Cytotoxicity Using Electric Cell−Substrate Impedance Sensing:  Concentration and Time Response Function Approach

2002· article· en· W2050764344 on OpenAlexaff
Caide Xiao, Bernard Lachance, Geoffrey I. Sunahara, John H. T. Luong

Bibliographic record

VenueAnalytical Chemistry · 2002
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsNational Research Council CanadaBiotechnology Research Institute
Fundersnot available
KeywordsChemistryCytotoxicityElectrical impedanceSubstrate (aquarium)Function (biology)Biological systemIn vitroBiochemistryCell biologyElectrical engineering

Abstract

fetched live from OpenAlex

This paper describes a simple and convenient method to measure the concentration and time response function f (C,t) of cells exposed to a toxicant by electric cell-substrate impedance sensing. Attachment and spreading of fibroblastic V79 cells cultured on small gold electrodes precoated with fibronectin were detected as electrical resistance changes. With this method, chemical cytotoxicity was easily screened by observing the response function of attached cells in the presence of inhibitor. The cytotoxicities of three test models, cadmium chloride, sodium arsenate, and benzalkonium chloride, were quantified by measuring the percentage inhibition as a function of the inhibitor concentration. The half-inhibition concentration, the required concentration to achieve 50% inhibition, derived from the response function agreed well with the results obtained using the standard neutral red assay.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.240
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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

Citations166
Published2002
Admission routes1
Has abstractyes

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