<i>In Ovo</i>Administration of Innate Immune Stimulants and Protection from Early Chick Mortalities due to Yolk Sac Infection
Bibliographic record
Abstract
Omphalitis or yolk sac infection (YSI) and colibacillosis are the most common infectious diseases that lead to high rates of early chick mortalities (ECMs) in young chicks. Out of numerous microbial causes, avian pathogenic Escherichia coli (APEC) or extraintestinal pathogenic E. coli infections are considered the most common cause of these conditions. YSI causes deterioration and decomposition of yolk, leading to deficiency of necessary nutrients and maternal antibodies, retarded growth, poor carcass quality, and increased susceptibility to other infections, including omphalitis, colibacillosis, and respiratory tract infection. Presently, in ovo injection of antibiotics, heavy culling, or after hatch use of antibiotics is practiced to manage ECM. However, increased antibiotic resistance and emergence of "super bugs" associated with use or misuse of antibiotics in the animal industry have raised serious concerns. These concerns urgently require a focus on host-driven nonantibiotic approaches for stimulation of protective antimicrobial immunity. Using an experimental YSI model in newborn chicks, we evaluated the prophylactic potential of three in ovo-administered innate immune stimulants and immune adjuvants for protection from ECM due to YSI. Our data have shown >80%, 65%, and 60% survival with in ovo use of cytosine-phosphodiester-guanine (CpG) oligodeoxynucleotides (ODN), polyinosinic:polycytidylic acid, and polyphosphazene, respectively. In conclusion, data from these studies suggest that in ovo administration of CpG ODN may serve as a potential candidate for replacement of antibiotics for the prevention and control of ECM due to YSI in young chicks.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".