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Record W2304959546 · doi:10.5539/ijb.v8n2p85

Investigation of Mutagenic Effects of Synthetic Acidic Textile Dyes by Umu-Test (Salmonella thyphimurium TA1535/pSK1002)-a Short Term Bacterial Assay

2016· article· en· W2304959546 on OpenAlexvenueno aff
Ünal Şenel, Murat Demirtaş, I ̊. G. ŞENEL, Ahmet Dolunay, Murat E. Guveli, Koray Celebı, Salih Denli

Bibliographic record

VenueInternational Journal of Biology · 2016
Typearticle
Languageen
FieldChemistry
TopicDye analysis and toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsChemistrySalmonellaAbsorbanceBiotransformationEnzymeS9 fractionChromatographyOrange (colour)Fraction (chemistry)BiochemistryCarcinogenNuclear chemistryEnterobacteriaceaeBacteriaEscherichia coliFood scienceBiologyMicrosome

Abstract

fetched live from OpenAlex

In this study, genotoxic properties of some synthetic acidic dyes were researched by umu-test (Salmonella thyphimurium TA1535/pSK1002) which is a short term bacterial test. The study analyzed genetoxic activity of Acid Blue 127, Acid Orange 51, Acid Black 63, Acid Yellow 17 and Acid Blue 113 synthetic acidic dyes in presence and absence of S9 fraction used in Textile industry. Solutions of dyes at concentrations of 400 µg/ml, 120 µg/ml, 40 µg/ml and 4 µg/ml were prepared; and biotransformation effects of dyes that undergo chemical modifications on organisms were examined by measuring betagalactosidase activity in presence of liver enzymes by using rat S9 fraction. At the mentioned concentrations the absorbance values of betagalactosidase activity were measured for 5 synthetic acidic dyes and none of them showed mutagenic effect either in presence or absence of S9 fraction. In addition, these results mean that these synthetic acidic dyes are not metabolized with liver enzymes.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.247
Teacher spread0.238 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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Same venueInternational Journal of BiologySame topicDye analysis and toxicityFrench-language works237,207