Recurring Necrotic Enteritis Outbreaks in Commercial Broiler Chicken Flocks Strongly Influence Toxin Gene Carriage and Species Richness in the Resident Clostridium perfringens Population
Bibliographic record
Abstract
Extensive use of antibiotic growth promoters (AGPs) in food animals has been questioned due to the globally increasing problem of antibiotic resistance. For the poultry industry, digestive health management following AGP withdrawal in Europe has been a challenge, especially the control of necrotic enteritis. Much research work has focused on gut health in commercial broiler chicken husbandry. Understanding the behavior of Clostridium perfringens in its ecological niche, the poultry barn, is key to a sustainable and cost-effective production in the absence of AGPs. Using polymerase chain reaction and pulsed-field gel electrophoresis, we evaluated how the C. perfringens population evolved in drug-free commercial broiler chicken farms, either healthy or affected with recurring clinical necrotic enteritis outbreaks, over a 14-month period. We show that a high genotypic richness was associated with an increased risk of clinical necrotic enteritis. Also, necrotic enteritis-affected farms had a significant reduction of C. perfringens genotypic richness over time, an increase in the proportion of C. perfringens strains harboring the cpb2 gene, the netB gene, or both. Thus, necrotic enteritis occurrence is correlated with the presence of an initial highly diverse C. perfringens population, increasing the opportunity for the selective sweep of particularly virulent genotypes. Disease outbreaks also appear to largely influence the evolution of this bacterial species in poultry farms over time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".