Review: The use of direct fed microbials to mitigate pathogens and enhance production in cattle
Bibliographic record
Abstract
McAllister, T. A., Beauchemin, K. A., Alazzeh, A. Y., Baah, J., Teather, R. M. and Stanford, K. 2011. Review: The use of direct fed microbials to mitigate pathogens and enhance production in cattle. Can. J. Anim. Sci. 91: 193–211. Direct-fed microbials (DFM) have been employed in ruminant production for over 30 yr. Originally, DFM were used primarily in young ruminants to accelerate establishment of the intestinal microflora involved in feed digestion and to promote gut health. Further advancements led to more sophisticated mixtures of DFM that are targeted at improving fiber digestion and preventing ruminal acidosis in mature cattle. Through these outcomes on fiber digestion/rumen health, second-generation DFM have also resulted in improvements in milk yield, growth and feed efficiency of cattle, but results have been inconsistent. More recently, there has been an emphasis on the development of DFM that exhibit activity in cattle against potentially zoonotic pathogens such as Escherichia coli O157:H7, Salmonella spp. and Staphylococcus aureus. Regulatory requirements have limited the microbial species within DFM products to organisms that are generally recognized as safe, such as lactic acid-producing bacteria (e.g., Lactobacillus and Enterococcus spp.), fungi (e.g., Aspergillus oryzae), or yeast (e.g., Saccharomyces cerevisiae). Direct-fed microbials of rumen origin, involving lactate-utilizing species (e.g., Megasphaera elsdenii, Selenomonas ruminantium, Propionibacterium spp.) and plant cell wall-degrading isolates of Butyrivibrio fibrisolvens have also been explored, but have not been commercially used. Development of DFM that are efficacious over a wide range of ruminant production systems remains challenging because[0] comprehensive knowledge of microbial ecology is lacking. Few studies have employed molecular techniques to study in detail the interaction of DFM with native microbial communities or the ruminant host. Advancements in the metagenomics of microbial communities and the genomics of microbial–host interactions may enable DFM to be formulated to improve production and promote health, responses that are presently often achieved through the use of antimicrobials in 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".