A Ligated Intestinal Loop Model in Anesthetized Specific Pathogen Free Chickens to Study <em>Clostridium Perfringens</em> Virulence
Bibliographic record
Abstract
Necrotic enteritis was studied in chickens using various in vivo infection models. Most of these use a combination of predisposing factors, such as coccidiosis and diet, with gavage or administration via the feed using Clostridium perfringens. In these models, the comparison of multiple C. perfringens strains for virulence studies requires a large number of hosts to obtain significant results. Mortality during the course of the study can be high depending on the experimental model, hence raising ethical concerns regarding animal welfare in research. The development of new infection models requiring fewer animals to study pathogenesis, yet providing statistically significant and valid results, is important in reducing animal use in research. Intestinal ligated loop models have been used to study clostridial infections in various species such as mice, rabbits and calves. Following surgical procedures to create ligated loop segments, C. perfringens strains are injected directly into the loops to establish a close contact between the bacteria and the intestinal mucosa. Samples of the small intestine and luminal contents are taken at the termination of the procedures after a few hours. Multiple bacterial strains can be inoculated in each animal, hence reducing the number of required subjects in the experiments. Also, procedures are performed under general anesthesia to reduce animal pain. In chickens, this model would be more appropriate than oral administration to compare C. perfringens strain pathogenicity because fewer animals are needed, no predisposing factors are required to induce the disease, and pain is controlled by analgesics. The intestinal ligated loop model is poorly described in chickens and standardization is essential for its optimal use. This manuscript provides all the necessary steps to create numerous intestinal ligated loops in chickens and brings information on the critical points to obtain valid results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".