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Record W2566676006 · doi:10.22606/epp.2016.11001

Neurotoxicological Effects of Municipal Effluents in Fathead Minnow Pimephale Promelas

2016· article· en· W2566676006 on OpenAlexaff
François Gagné, Sonia Trépanier, C. André

Bibliographic record

VenueEnvironmental Pollution and Protection · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReproductive biology and impacts on aquatic species
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsMinnowVitellogeninPimephales promelasEffluentAcetylcholinesteraseAchéBiologyPollutantToxicologyNeurotoxicityNonylphenolEnvironmental chemistryInternal medicineLipid peroxidationEndocrinologyToxicityChemistryFish <Actinopterygii>EcologyBiochemistryFisheryOxidative stressEnzymeEnvironmental scienceMedicineEnvironmental engineering

Abstract

fetched live from OpenAlex

Municipal effluents are known to be able of disrupting neuro-endocrine signaling pathways in oviparous organisms.The purpose of this study was to examine the neurotoxicity of a chemically-treated municipal effluent to adult fathead minnow (Pimephales promelas) after 21 days.Brain somatic index and lipid peroxidation (LPO), monoamine oxidase (MAO) and acetylcholinesterase (AChE) levels were determined in both male and female fish.The estrogenicity of the municipal effluent was confirmed by measuring vitellogenin production and energy expenses in the liver.Brain MAO and AChE activities increased at low effluent concentrations and decreased at higher concentrations (>10% v/v).The data suggest that males expend more metabolic energy than females and was related to vitellogenin, and that brain activity is impaired in both sexes in the presence of the effluent.In conclusion, exposure to municipal effluents could produce biochemical changes in the central nervous system in fish.

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 score0.002
Threshold uncertainty score0.005

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 head0.009
GPT teacher head0.217
Teacher spread0.209 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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