Dietary glycine concentration affects intestinal Clostridium perfringens and lactobacilli populations in broiler chickens1
Bibliographic record
Abstract
Previous studies have reported that intestinal populations of Clostridium perfringens, the causative agent of necrotic enteritis (NE), are correlated with diets high in glycine. To establish a direct causative link, 3 trials were conducted to examine the effect of dietary glycine levels on gut populations of C. perfringens, alpha-toxin production, and NE lesion scores in broiler chickens. In trials 1 and 2, 12 groups of 4 birds were fed 4 different ideal protein-balanced diets formulated to contain 0.75, 1.58, 3.04, or 4.21% glycine from d 14 to 28 of age. In trial 3, 24 groups of 4 birds were given 6 different ideal protein-balanced diets formulated to contain 0.50, 0.75, 1.00, 1.50, 2.00, or 4.00% glycine. All birds were orally challenged with a broth culture of C. perfringens type A on d 1 and between d 14 and 21 of age and killed on d 28. The majority of birds showed clinical signs of NE with 4.16 to 8.33% mortality in the 3 trials. The highest mortality and intestinal lesion scores were observed in chickens receiving 3.04% glycine in trials 1 and 2, and 4.00% glycine in trial 3. Clostridium perfringens populations in the cecum varied quadratically with increasing dietary glycine, with the maximal response seen at 3.30,3.89, and 3.51% dietary glycine in trials 1, 2, and 3, respectively. Numbers of lactobacilli in cecum declined significantly (P < 0.05) with increasing levels of glycine. The results suggest that dietary glycine level has a significant effect on C. perfringens and lactobacilli populations and may be a predisposing factor for NE in broiler chickens.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".