A single intranasal dose of essential oil spray confers modulation of the nasopharyngeal microbiota and short-term inhibition of Mannheimia in feedlot cattle: a pilot study
Bibliographic record
Abstract
Five essential oils (EOs) were previously characterized in vitro and identified as candidate EOs for the development of an intranasal EO spray to mitigate bovine respiratory disease (BRD) pathogens. In the present study, these EOs were evaluated for their potential to (i) reduce BRD pathogens, (ii) modulate nasopharyngeal microbiota, and (iii) influence animal performance, feeding behavior and immune response when a single dose administered intranasally to feedlot cattle. Forty beef steer calves (7-8 months old, Initial body weight = 284 ± 5 kg [SE]) received either an intranasal EO spray (ajowan, thyme, fennel, cinnamon leaf, and citronella) or PBS (Control; n = 20/group) on day 0. Deep nasopharyngeal swabs were collected on days (d) -1, 1, 2, 7, 14, 28, and 42 and processed for 16S rRNA gene sequencing, qPCR, and culturing. Significant effects of EO on community structure (d1), microbial richness and diversity, relative abundance of some dominant phyla (d1, d2, and d14), and the overall interaction network structure of the nasopharyngeal microbiota were detected. The relative abundance of Mannheimia was lower in the EO calves (4.34%) than in Control calves (10.4%) on d2, and M. haemolytica prevalence on d7 as compared to control calves. Feed intake, average daily gain, feeding behavior, and blood cell counts were not affected by EO treatment. Overall, a single intranasal dose of EO spray resulted in moderate modulation of nasopharyngeal microbiota and short-term inhibition of Mannheimia while not influencing animal performance, feeding behavior or immune response. Our study, for the first time, shows the potential use of intranasal EO to mitigate BRD in feedlot cattle.
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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) | 0.000 | 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".