Efficacy of the direct-fed microbial Enterococcus faecium alone or in combination with Saccharomyces cerevisiae or Lactococcus lactis during induced subacute ruminal acidosis
Bibliographic record
Abstract
This study aimed at investigating Enterococcus faecium alone or E. faecium in combination with Saccharomyces cerevisiae or Lactococcus lactis during a subacute ruminal acidosis (SARA) challenge. Four ruminally fistulated Holstein dairy cows were assigned to the following treatments in a 4×4 Latin square design: (1) control (CON); (2) E. faecium (EF); (3) EF + S. cerevisiae (EFSC); (4) EF + L. lactis DSM 11037 (EFLL). Each experimental period consisted of 18 d of adaptation to the respective direct-fed microbial, 3 d of SARA challenge, and 7d of rest. Rumen pH was recorded every 10 min over 24 h on d 17 of adaptation, d 2 of SARA, and d 6 of rest. On the last day of adaptation, SARA, and rest, samples of rumen content (0 and 3 h after feeding) were taken for volatile fatty acids, lactate, vitamin B12, rumen microbes, and lipopolysaccharides determination. Blood samples (0 and 6 h after feeding) were taken for the measurement of acute-phase proteins. Dry matter intake and milk yield were recorded daily. During SARA, mean rumen pH with EFSC (5.94) was not different from that of EFLL (5.95) and tended to be higher than with CON (5.82) or EF (5.82). Postfeeding vitamin B12 concentrations in the rumen were greater with EFSC (134.5ng/g) than with EF (99.6ng/g) and tended to be greater when compared with CON (101.2ng/g) or EFLL (104.9ng/g). During rest, prefeed vitamin B12 was greater with EFSC (166.5ng/g) compared with CON (132.3ng/g). The EFSC treatment did better than EF alone on pH characteristics during adaptation and SARA and on maintenance of ruminal vitamin B12 status during SARA. Milk yield drop from d 1 to 3 of SARA was smaller with EFSC (-0.8kg/d), EF (-0.9kg/d), or EFLL (-0.9kg/d) compared with CON (-7.5kg/d).
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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) | 0.001 | 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 | 0.001 |
| 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".