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Record W4406779277 · doi:10.1021/acs.estlett.4c00955

Methylene Blue Is a Widely Used Antifungal Agent That Confounds Behavioral Toxicity Assays in Larval Zebrafish

2025· article· en· W4406779277 on OpenAlexafffund
Niepukolie Nipu, Lai Wei, Jith K. Thomas, Jan A. Mennigen

Bibliographic record

VenueEnvironmental Science & Technology Letters · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsHealth CanadaUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAntifungalMethylene blueToxicityZebrafishLarvaPharmacologyChemistryBiologyMicrobiologyEcologyBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Zebrafish are widely used as model organisms in biological research with embryos typically reared in media supplemented with methylene blue (MB) as an antifungal agent. Many animal care guidelines recommend the use of MB during early development stages. However, this practice overlooks MB’s known effects as a monoamine oxidase inhibitor and antidepressant. This study demonstrates that at recommended husbandry concentrations, MB significantly reduces zebrafish locomotion in a 24 h behavior assay, a finding consistent across strains and laboratories. Gene expression profiling and pharmacological experiments using the MAO-inhibitor deprenyl suggest that MB induces hypolocomotion by increasing the serotonergic tone. Importantly, MB use in standard embryo medium masks known hypolocomotor responses to fluoxetine, a common aquatic contaminant and selective serotonin-reuptake inhibitor. These findings have significant implications for the increasing use of larval zebrafish in high-throughput neurotoxicity assessments and highlight the need to reconsider the use of MB in zebrafish research. The study emphasizes the importance of eliminating potential confounds in husbandry practices and improving experimental protocol reporting to enhance reproducibility in zebrafish-based (eco)toxicity testing.

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 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 score0.017
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.013
GPT teacher head0.292
Teacher spread0.279 · 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
Published2025
Admission routes2
Has abstractyes

Explore more

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