Effect of 3′,5′-cyclic diguanylic acid in a broiler Clostridium perfringens infection model
Bibliographic record
Abstract
In an effort to explore strategies to control Clostridium perfringens, we investigated the synergistic effect of a ubiquitous bacterial second messenger 3',5'-cyclic diguanylic acid (c-di-GMP) with penicillin G in a broiler challenge model. All chicks were inoculated in the crop by gavage on d 14, 15, and 16 with a mixture of 4 C. perfringens strains. Birds were treated with saline (control group) or 20 nmol of c-di-GMP by gavage or intramuscularly (IM) on d 24, all in conjunction with penicillin G in water for 5 d. Weekly samplings of ceca and ileum were performed on d 21 to 35 for C. perfringens and Lactobacillus enumeration. On d 35 of age, the IM treatment significantly (P < 0.05) reduced C. perfringens in the ceca, suggesting possible synergistic activity between penicillin G and c-di-GMP against C. perfringens in broiler ceca. Moreover, analysis of ceca DNA for the presence of a series of C. perfringens virulence genes showed a prevalence of 30% for the Clostridium perfringens alpha-toxin gene (cpa) from d 21 to 35 in the IM-treated group, whereas the occurrence of the cpa gene increased from 10 to 60% in the other 2 groups (control and gavage) from d 21 to 35. Detection of β-lactamase genes (blaCMY-2, blaSHV, and blaTEM) indicative of gram-negative bacteria in the same samples from d 21 to 35 did not show significant treatment effects. Amplified fragment-length polymorphism showed a predominant 92% similarity between the ceca of 21-d-old control birds and the 35-d-old IM-treated c-di-GMP group. This suggests that c-di-GMP IM treatment might be effective at restoring the normal microflora of the host on d 35 after being challenged by C. perfringens. Our results suggest that c-di-GMP can reduce the colonization of C. perfringens in the gut without increasing the selection pressure for some β-lactamase genes or altering the commensal bacterial population.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".