A Randomized Controlled Trial to Assess the Impact of Dietary Energy Sources, Feed Supplements, and the Presence of Super-Shedders on the Detection of <i>Escherichia coli</i> O157:H7 in Feedlot Cattle Using Different Diagnostic Procedures
Bibliographic record
Abstract
Alteration of the gastro-intestinal tract through manipulation of cattle diets has been proposed as a preharvest control measure to reduce fecal shedding of Escherichia coli O157:H7. The objective of this study was to examine the effects of the energy source's moisture content (high moisture corn and dry whole-shelled corn), two natural feed supplements (Saccaromyces cerevisiae boulardii CNCM 1079-Levucell and Aspergillus oryzae-Amaferm), and two levels of vitamin A (2200 IU/kg and no supplementation) on the fecal excretion of E. coli O157:H7 in naturally infected cattle. One hundred sixty-eight Angus-cross beef steers were randomly allocated to 24 pens, and each pen was assigned 1 of 12 dietary treatments in a randomized complete block design. E. coli O157:H7 was detected by rectoanal mucosal swab (RAMS) and fecal grab samples using immunomagnetic separation (IMS) and standard microbiological techniques. On the basis of multivariable multilevel logistic regression models, we found a statistically significant (p < 0.05) increase in the prevalence of E. coli O157:H7 in animals fed dry whole-shelled corn in models based on fecal-IMS, and this effect was increased if a super-shedding animal (shedding > 10(4) colony forming units of E. coli O157:H7 per gram of feces) was present in the pen at the time of testing relative to animals fed high moisture corn and nonexposed to super-shedders. However, in similar models based on RAMS-IMS testing, the effect of corn type on the prevalence of E. coli O157:H7 varied with the type of feed additive used. Being exposed to a super-shedding pen-mate also increased the odds of being positive to E. coli O157:H7 in the RAMS-IMS models. These models demonstrate that the impact of different supplements may vary with the diagnostic test used, and that further research into the biological significance of differences between RAMS- and fecal-IMS test results is warranted.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".