Abrupt Weaning Significantly Increases Mortality Following a Secondary Bacterial Respiratory Infection
Bibliographic record
Abstract
Secondary bacterial respiratory infections are a major cause of mortality in fall-weaned feedlot calves, and epidemiological studies implicate a variety of stressors as significant contributing factors. Experimental studies have identified stressors that may compromise pulmonary defense mechanisms but there is no evidence that these functional changes alter respiratory disease outcome. We used a model of combined viral and bacterial respiratory disease to determine if nutritional and psychological stressors (abrupt weaning; AW) altered respiratory disease mortality. Mortality was doubled in AW calves challenged with Mannheimia haemolytica four days after a primary bovine herpesvirus-1 (BHV-1) respiratory infection, when compared to calves adapted to weaning (pre-conditioned; PC) for two weeks prior to respiratory challenge. Reduced survival time and decreased lung pathology in the AW group suggested death was due to an acute systemic reaction. Viral shedding did not differ significantly between the two treatment groups. AW calves and all calves developing fatal pneumonia had significantly elevated interferon (IFN)-y levels in nasal secretions and increased systemic proinflammatory responses. Analysis of blood leukocytes revealed significantly increased CD14 and TLR4 gene expression in animals with fatal pneumonia. These analyses support the conclusion that stress enhanced innate immune responses to viral infection without altering the level of BHV-1 infection. These studies provide the first quantitative evidence that stress associated with abrupt weaning contributes significantly to fatal bovine respiratory disease.
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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 | 0.001 |
| 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 | 0.000 | 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".