Putative cardiotoxic compounds extracted from meat meal as a potential risk factor for the development of heart failure in fast-growing commercial broilers
Bibliographic record
Abstract
Thermal processing of meat products generates cardiotoxic compounds capable of inducing heart failure in both humans and laboratory animals. Such compounds may be present in broiler diets because supplements such as meat meal (MM), which are commonly used in broiler rations, are rendered at high temperature. Our objective was to evaluate whether putative cardiotoxic compounds in MM increase the risk of heart failure in broilers. The treatment and control diets were prepared by mixing the condensed MM extract (equivalent to dietary MM inclusion of 25%) or placebo (condensed extraction medium) with commercial broiler feed, and the respective diets were offered to commercial male broilers randomly allocated to either treatment or control groups. Broilers fed a diet spiked with MM extract showed a higher incidence (P<0.05) of chronic heart failure (65.5%) in comparison with the control group (55.4%). Postmortem examination upon termination of the experiment revealed that, in comparison with control broilers, broilers fed diet containing MM extract showed higher incidence of lesions indicative of subclinical heart disease evidenced grossly by ventricular dilation and pericardial effusions, microscopically by changes characteristic of cardiomyocyte degeneration, and ultrastructurally by changes in contractile elements and in mitochondria. Measurements of cardiac high-energy phosphates revealed that broilers fed the diet containing MM extract had lower (P<0.05) levels of cardiac energy reserve as compared with birds fed control diet. We conclude that cardiotoxic factors that can induce patho-physiological changes in the heart are present in MM.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".