In situ identification and quantification of protein-hydrolyzing ruminal bacteria associated with the digestion of barley and corn grain
Bibliographic record
Abstract
In this study, BODIPY FL DQ™ casein staining combined with fluorescence in situ hybridization (FISH) was used to detect and identify protein-hydrolyzing bacteria within biofilms that produced active cell-surface-associated serine- and metallo-proteases during the ruminal digestion of barley and corn grain in cows fed barley-based diets at 2 different levels. A doublet coccoid bacterial morphotype associated with barley and corn grain particles fluoresced after BODIPY FL DQ™ casein staining. Bacteria with this morphotype accounted for 3%-10% of the total bacteria attached to surface of cereal grain particles, possibly indicative of an important role in the hydrolysis of the protein matrix within the endosperm. However, the identity of these predominant proteolytic bacteria could not be determined using FISH. Quantitative FISH revealed that known proteolytic species, Prevotella ruminicola, Ruminobacter amylophilus, and Butyrivibrio fibrisolvens, were attached to particles of various cultivars of barley grain and corn, confirming their role in the proteolysis of cereal grains. Differences in chemical composition among different barley cultivars did not affect the composition of proteolytic bacterial populations. However, the concentrate level in the basal diet did have an impact on the relative abundance of proteolytic bacteria and thus possibly their overall contribution to the proteolysis of cereal grains.
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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".