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Record W2508507454 · doi:10.1021/acs.estlett.6b00277

A Reagent-Free Screening Assay for Evaluation of the Effects of Chemicals on the Proliferation and Morphology of HeLa-GFP Cells

2016· article· en· W2508507454 on OpenAlexafffund
Shiyang Cheng, Jing Li, Guanyong Su, Robert J. Letcher, John P. Giesy, Chunsheng Liu

Bibliographic record

VenueEnvironmental Science & Technology Letters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversity of SaskatchewanCarleton University
FundersMinistry of Education of the People's Republic of ChinaCanada Research Chairs
KeywordsHeLaReagentFluorescenceTrisChemistryGreen fluorescent proteinCell growthXenobioticPhosphateBiochemistryMolecular biologyCellChromatographyBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

A reagent-free screening assay using HeLa cells with green fluorescent protein expressed in the cytoplasm was developed to describe adherence and proliferation of cells after seeding and to evaluate the dose- and time-dependent effects of three classes of chemicals, including metals (CdCl 2, MeHg, HgCl 2, and NiCl 2 ), flame retardants [tris(1,3-dichloro-2-propyl) phosphate, heptadecafluoro-1-octanesulfonic acid, tetrabromobisphenol A, and tris(2-chloroethyl) phosphate], and phenolic fungicides (2,4,6-trichlorophenol, 4- tert -butylphenol, 3-bromophenol, and 2,4-dibromophenol), on the proliferation and morphology of cells. A seeding density of 5000 cells/well was determined to be optimal, and the most suitable duration of xenobiotic exposure was 120 h beginning 58 h postseeding. Dose- and time-dependent alterations in total fluorescence in the fluorescent field and number of cells, area per cell, and cellular roundness in the bright field were identified after exposure to each of the target chemicals. Results were comparable to those of the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay or other end points published in the literature for the same chemicals.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.087
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental Science & Technology LettersSame topicToxic Organic Pollutants ImpactFrench-language works237,207