Are apparent negative effects of feeding GM MON810 maize to Atlantic salmon,<i>Salmo salar</i>, caused by confounding factors?
Bibliographic record
Abstract
The present study was conducted to follow up on apparent differences in growth, relative organ sizes, cellular stress and immune function in Atlantic salmon fed feed containing GM Bacillus thuringiensis maize compared with feed containing the non-modified parental maize line. Gene expression profiling on the distal intestinal segment and liver was performed by microarray, and selected genes were followed up by quantitative PCR (qPCR). In the liver, qPCR revealed some differentially regulated genes, including up-regulation of gelsolin precursor, down-regulation of ferritin heavy subunit and a tendency towards down-regulation of metallothionein (MT)-B. This, combined with the up-regulation of anti-apoptotic protein NR13 and similar tendencies for ferritin heavy chain and MT-A and -B in the distal intestine, suggests changes in cellular stress/antioxidant status. This corresponds well with and strengthens previous findings in these fish. To exclude possible confounding factors, the maize ingredients were analysed for mycotoxins and metabolites. The GM maize contained 90 μg/kg of deoxynivalenol (DON), while the non-GM maize was below the detection limit. Differences were also observed in the metabolite profiles of the two maize varieties, some of which seemed connected to the mycotoxin level. The effects on salmon observed in the present and previous studies correspond relatively well with the effects of DON as reported in the literature for other production animals, but knowledge regarding effects and harmful dose levels in fish is scarce. Thus, it is difficult to conclude whether the observed effects are caused by the DON level or by some other aspect of the GM maize ingredient.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".