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Record W2087808065 · doi:10.1080/15287394.2010.481617

Contaminated Soils (III): In Vitro Dermal Absorption of Ethylene Glycol and Nonylphenol in Human Skin

2010· article· en· W2087808065 on OpenAlexaffabout
Richard P. Moody, Julie Joncas, Mark Richardson, Sanya Petrovic, I. Chu

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotoxicology and immune responses
Canadian institutionsHealth Canada
Fundersnot available
KeywordsAbsorption (acoustics)NonylphenolChemistryEthylene glycolSoil waterBovine serum albuminContaminationDepotIn vitroChromatographyEnvironmental chemistryBiochemistryBiologyEcologyMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Dermal absorption of contaminants from soils at federal contaminated sites in Canada was investigated using one hydrophile, (14)C-ethylene glycol (EG), and one lipophile, (14)C-nonylphenol (NP). In vitro dermal absorption of EG and NP was examined in dermatomed (0.4-0.5 mm) human skin using Bronaugh Teflon flow-through cells with Hanks HEPES buffered (pH 7.4) receiver solution with 4% bovine serum albumin (BSA). Tests were conducted under occlusive conditions with and without a commercial gardening soil spiked with EG or NP applied to skin at a soil load of 5 mg/cm(2). With percent absorption in skin depot included, a total of 9.9 + or - 6.28% (n = 6) and 34.8 + or - 8.47% (n = 6) absorption of EG with and without soil, respectively, and 20.6 + or - 5.56% (n = 7) and 41.1 + or - 6.46% (n = 7) of NP, with and without soil, respectively, were obtained. For tests without soil a reverse pattern was observed with significantly lower percent absorption into the receiver than depot with the lipophile NP, but significantly higher percent absorption in receiver versus depot for the hydrophile EG. This pattern was different in tests with soil, and caution needs to be exercised when extrapolating data from in vitro tests conducted without soil in human health risk assessments at contaminated sites.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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

Citations6
Published2010
Admission routes2
Has abstractyes

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