Effect of aerosolized bacterial lysate on development of naturally occurring respiratory disease in beef calves
Bibliographic record
Abstract
BACKGROUND: Bovine respiratory disease (BRD) is a major problem affecting beef cattle after arrival to feedlots. Alternatives to antibiotics are needed for prevention. HYPOTHESIS: Stimulation of pulmonary innate immune responses at the time of arrival to a feedlot reduces the occurrence and severity of BRD. ANIMALS: Sixty beef steers at high risk of BRD. METHODS: Randomized, double-blinded, placebo-controlled study. Calves received saline or a lysate of Staphylococcus aureus and Escherichia coli by aerosol, at 16 hours after feedlot arrival. Calves were monitored for 28 days for disease outcomes and levels of Mycoplasma bovis and Mannheimia haemolytica in nasal swabs. RESULTS: Death from M bovis pneumonia was significantly greater in lysate-treated animals (6/29, 24%) compared to controls (1/29, 3%; odds ratio = 10.2; 95% confidence interval [CI] = 1.1-96.0; P = .04). By 28 days after arrival, 29/29 lysate-treated calves had ultrasonographic pulmonary consolidation compared to 24/29 control calves (P = .05). Lysate-treated calves had lower weight gain compared to control calves (-8.8 kg, 95% CI = -17.1 to -0.5; P = .04), and higher body temperatures on days 4, 7, and 21 (0.19°C; 95% CI = 0.01-0.37; P = .04). Nasal M bovis numbers increased over time and were higher in lysate-treated calves (0.76 log CFU, 95% CI = 0.3-1.2; P = .001). CONCLUSIONS AND CLINICAL IMPORTANCE: Aerosol administration of a bacterial lysate exacerbated BRD in healthy high-risk beef calves, suggesting that respiratory tract inflammation adversely affects how calves respond to subsequent natural infection with M bovis and other respiratory pathogens.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".