Effects of feed naturally contaminated with Fusarium mycotoxins on metabolism and immunity of dairy cows
Bibliographic record
Abstract
A previous study in dairy cows showed some effect of feed contaminated with Fusarium mycotoxins on metabolism and immunity. A subsequent experiment investigated the effect of feedborne Fusarium mycotoxins on some immune functions in more detail. A total mixed ration (TMR) containing a blend of feedstuffs naturally contaminated with Fusarium mycotoxins was fed for 63 d to 12 mid-lactation Holstein cows with an average milk production of 36 kg/d in a completely randomized design with repeated measures including 1) control TMR and 2) contaminated TMR. Wheat, corn, hay, and corn silage were the contaminated feedstuffs. Deoxynivalenol was the major contaminant and was found in TMR at 3.5 mg/kg of dry matter. The parameters measured were 1) performance: body weight, body condition score, dry matter intake, milk production, composition and somatic cell count; 2) health: blood serum chemistry, hematology, coagulation profile, and rumen fluid ammonia levels; 3) immune function: total serum immunoglobulins (IgA, IgG, IgM), specific antibody response to ovalbumin, and neutrophil phagocytosis. Dry matter intake, body weight, milk production, and milk composition were not affected by diet. Neutrophil phagocytosis was depressed throughout the experiment in cows fed the contaminated diet. Serum sodium concentrations and osmolality were significantly elevated throughout the experiment in cows fed the contaminated diet. Primary antibody response to ovalbumin immunization was higher in cows fed the contaminated diet compared with controls. It was concluded that feed naturally contaminated with Fusarium mycotoxins can affect metabolic parameters and immune function of dairy cows.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".