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Record W2152201763 · doi:10.1155/2015/420702

Immunomodulation by Zearalenone in Carp (<i>Cyprinus carpio</i>L.)

2015· article· en· W2152201763 on OpenAlexaff
Constanze Pietsch, Ranka Junge, Patricia Burkhardt‐Holm

Bibliographic record

VenueBioMed Research International · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsUniversity of Alberta
FundersUniversität Basel
KeywordsCyprinusZearalenoneImmune systemCarpBiologyCommon carpMycotoxinAflatoxinAquacultureFood sciencePhysiologyAnimal scienceFish <Actinopterygii>FisheryImmunology

Abstract

fetched live from OpenAlex

The mycotoxin zearalenone (ZEN) is a frequent contaminant of animal feeds, but its effects on fish have not yet been investigated extensively. In order to fill this gap a feeding trial with juvenile carp was conducted. Three groups of fish were fed feeds contaminated with ZEN at three concentrations (low: 332 μg kg(-1), medium: 621 μg kg(-1), and high: 797 μg kg(-1) feed) for four weeks. Possible reversible effects of ZEN were evaluated by feeding additional groups with the ZEN-contaminated feeds for four weeks, followed by the uncontaminated diet for two weeks. Immune function of isolated leukocytes from head kidney and trunk kidney was assessed using the assessment of NO production, the respiratory burst assay, the chemiluminescence assay, and the measurement of arginase activities. These investigations frequently revealed increased immune responses after exposure of fish to low ZEN concentrations and reduced immune responses after exposure to high mycotoxin concentrations. Moreover, the feeding of the uncontaminated diet for further two weeks did not improve the immune responses in most cases. These results indicate that cellular immune functions in ZEN-contaminated carp are influenced which may be relevant for fish health in aquaculture.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.089
GPT teacher head0.370
Teacher spread0.282 · 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 designNot applicable
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

Citations22
Published2015
Admission routes1
Has abstractyes

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