Amino acid composition of rumen bacteria and protozoa in cattle
Bibliographic record
Abstract
Because microbial crude protein (MCP) constitutes more than 50% of the protein digested in cattle, its AA composition is needed to adequately estimate AA supply. Our objective was to update the AA contributions of the rumen microbial AA flowing to the duodenum using only studies from cattle, differentiating between fluid-associated bacteria (FAB), particle-associated bacteria (PAB), and protozoa, based on published literature (53, 16, and 18 treatment means were used for each type of microorganism, respectively). In addition, Cys and Met reported concentrations were retained only when an adequate protection of the sulfur groups was performed before the acid hydrolysis. The total AA (or true protein) fraction represented 82.4% of CP in bacteria. For 10 AA, including 4 essential AA, the AA composition differed between protozoa and bacteria. The most noticeable differences were a 45% lower Lys concentration and 40% higher Ala concentration in bacteria than in protozoa. Differences between FAB and PAB were less pronounced than differences between bacteria and protozoa. Assuming 33% FAB, 50% PAB, and 17% of protozoa in MCP duodenal flow, the updated concentrations of AA would decrease supply estimates of Met, Thr, and Val originating from MCP and increase those of Lys and Phe by 5 to 10% compared with those calculated using the FAB composition reported previously. Therefore, inclusion of the contribution of PAB and protozoa to the duodenal MCP flow is needed to adequately estimate AA supply from microbial origin when a factorial method is used to estimate duodenal AA flow. Furthermore, acknowledging the fact that hydrolysis of 1 kg of true microbial protein yields 1.16 kg of free AA substantially increases the estimates of AA supply from MCP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".