Dietary aflatoxin B1 (AFB1) reduces growth performance, impacting growth axis, metabolism, and tissue integrity in juvenile gilthead sea bream (Sparus aurata)
Bibliographic record
Abstract
Mycotoxins are an increasing threat to all the related commodities from agriculture . Its occurrence is expected to increase due to climate change . Here, we examined the impacts of dietary toxicity of aflatoxin B1 (AFB1) in gilthead sea bream ( Sparus aurata ) at levels of 1 or 2 mg AFB1 kg −1 fish feed. Inclusion of AFB1 in the diet resulted in 80% inhibition of the total weight gain during the 85-day trial. Carbohydrate and lipid energetic metabolites, both in plasma and liver, were depleted. Moreover, the histopathological analysis revealed several tissue anomalies in the liver, kidney, and spleen. Furthermore, the relative expression of gene transcripts for growth regulation was affected by AFB1. Adenohypophyseal gh and hepatic igf1 were inversely correlated due to AFB1 effects. Relative expression levels of gene transcripts as stress indicators were increased at AFB1 highest doses, such as hypothalamic trh , crh, and crhbp , as well as star in head kidney. Interestingly circulating levels of cortisol were unaffected. Overall, our results showed that aquafeeds with AFB1 impaired growth, alter metabolism, tissue integrity, and transcriptomic responses. However, we did find AFB1 residue neither in the liver nor muscle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".