Supplementing Forage with Traditional Chinese Medicine Can Increase Microbial Protein Synthesis in Sheep
Bibliographic record
Abstract
Traditional Chinese medicine (TCM) encompasses a wide range of natural herbs and plants that are used to treat or prevent diseases or promote health. This study aimed to evaluate the effect of feeding a TCM formula extract on nitrogen (N) balance, microbial nitrogen supply (MNS), and plasma leucine kinetics in sheep. Six sheep were fed with mixed hay (Hay-diet) only or supplemented with 2% TCM (mixture of Astragalus root, Angelica root, and Atractylodes rhizome; TCM-diet) in a crossover design over two 21-day periods. An isotope dilution of [1-13C]leucine was used to measure the rate of plasma leucine turnover. Purine derivative (PD) excretion in urine was determined to estimate the MNS. The TCM-diet significantly increased N intake (p < 0.01) and N digestibility (p = 0.02) compared to the Hay-diet, with less N excretion (p = 0.02) in feces, while no significant difference was observed between diets in terms of N excretion in urine and N retention. Total PD excretion and MNS were higher (p < 0.01), as well as the turnover rate of plasma leucine tended to be higher (p = 0.06) with the supplementation of TCM. The present results suggested that the TCM formula could be considered as a potential feed additive for ruminant production.
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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 | 0.001 |
| 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 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".