Increased annexin A1 and A2 levels in bronchoalveolar lavage fluid are associated with resistance to respiratory disease in beef calves
Bibliographic record
Abstract
Strategies to control bovine respiratory disease depend on accurate classification of disease risk. An objective method to refine the risk classification of beef calves could be economically beneficial, improve welfare by preventing unexpected disease occurrences, refine and reduce the use of antibiotics in beef production, and facilitate alternative methods of disease control. The objective of this study was to identify proteins in bronchoalveolar lavage fluid (BALF) of stressed healthy calves that predict later disease outcome, serve as biomarkers of susceptibility to pneumonia, and play a role in pathogenesis. BALF was collected from 162 healthy beef calves 1-2 days after weaning and transportation. Difference in gel electrophoresis (DIGE) and mass spectrometry were used to compare proteins in samples from 7 calves that later developed respiratory disease compared to 7 calves that remained healthy. Calves that later developed pneumonia had significantly lower levels of annexin A1, annexin A2, peroxiredoxin I, calcyphosin, superoxide dismutase, macrophage capping protein and dihydrodiol dehydrogenase 3. Differences in annexin levels were partially confirmed by western blot analysis. Thus, lower levels of annexins A1 and A2 are potential biomarkers of increased susceptibility to pneumonia in recently weaned and transported feedlot cattle. Since annexins are regulated by glucocorticoids, this finding may reflect individual differences in the stress response that predispose to pneumonia. These findings also have implications in pathogenesis. Annexins A1 and A2 are known to prevent neutrophil influx and fibrin deposition respectively, and may thus act to minimize the harmful effects of the inflammatory response during development of pneumonia.
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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 | 0.001 | 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 | 0.000 |
| 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".