PSVIII-40 Stress alters bacterial density in the upper respiratory tract of beef calves.
Bibliographic record
Abstract
Weaning and transportation are associated with an increased risk of bovine respiratory disease (BRD) in cattle. How these stressors increase the risk of BRD is not completely understood but dysbiosis of the upper respiratory tract (URT) microbiome is hypothesized to be one potential cause. This study explored the bacterial density dynamics in the URT of beef calves following weaning and transportation stress. Deep nasopharyngeal swabs were collected from 5- to 6-month-old beef calves [suckling/control (S, n=10), weaned/stress group 1 (W, n=10) and weaned plus transportation/stress group 2 (W+T, n=10)] before (d0) and after (d2, d4, d7, d14 and d28) subjecting to stressors. Total bacterial density and the density of Mannheimia heamolytica and Pasteurella multocida were estimated by quantitative real-time PCR. Bacterial density data were analyzed using a repeated measures experimental design with time as the repeated measurement and animal as the experimental unit. Significant temporal variations in estimated bacterial densities were observed, regardless of the treatment group. Total bacterial density was, however, significantly (P < 0.01) higher in suckling calves (log10 7.32 16S rRNA gene copy/swab) than stressed calves (W - log10 7.12 16S rRNA gene copy/swab; W+T - log10 7.18 16S rRNA gene copy/swab). In contrast, density of the potential pathogenic bacteria, M. heamolytica (S - log10 5.29 lktA gene copy/swab; W - log105.23 lktA gene copy/swab; W+T - log105.33 lktA gene copy/swab) and P. multocida (S - log105.34 16S rRNA gene copy/swab; W - log105.19 16S rRNA gene copy/swab; W+T - log105.36 16S rRNA gene copy/swab) were similar among groups. Whole genome sequencing of the URT microbiome is being completed to provide a greater understanding of URT microbiome dynamics and functional changes following stress. This knowledge will better elucidate impact of stress on the URT microbiome, especially the commensal bacteria that become opportunistic pathogens in the lung.
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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 | 0.000 |
| 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".