Effects of a wide range of dietary forage-to-concentrate ratios on nutrient utilization and hepatic transcriptional profiles in limit-fed Holstein heifers
Bibliographic record
Abstract
BACKGROUND: Improving the efficiency of animal production is a relentless pursuit of ruminant producers. Energy utilization and partition can be affected by dietary composition and nutrient availability. Furthermore, the liver is the central metabolic intersection in cattle. However, the specific metabolic changes in the liver under conditions of limit-feeding remain unclear and require further study. The present study aimed to elucidate the effects of a wide range of dietary forage:concentrate ratios (F:C) on energy utilization, and identify potential changes in molecular metabolism by analyzing hepatic transcriptional profiles. Twenty-four half-sib Holstein heifers were fed four F:C diets (20:80, 40:60, 60:40, and 80:20 on a dry matter basis), with similar intake levels of metabolizable energy (ME) and crude protein. Liver biopsy samples were obtained and RNA sequencing was conducted to identify the hepatic transcriptomic changes. Moreover, the ruminal fermentation profiles, growth characteristics, and levels of metabolites in the liver and plasma of the heifers were monitored. RESULTS: The proportion of acetate showed a linear increase (P < 0.01) with increasing dietary forage levels, whereas the proportion of propionate showed a linear decline (P ≤ 0.01). Lower levels of average daily gain and feed efficiency (P < 0.01) were observed in heifers fed high levels of forage, with a significant linear response. Using the Short Time-series Expression Miner software package, the expression trends of significant differentially expressed genes (DEGs) were generally divided into 20 clusters, according to their dynamic expression patterns. Functional classification analysis showed that lipid metabolism (particularly cholesterol and steroid metabolism which were in line with the cholesterol content in the liver and plasma) was significantly increased with increasing dietary forage levels and slightly reduced by the 80% forage diet. Nine DEGs were enriched in the related pathways, namely HMGCS1, HMGCR, MSMO1, MVK, MVD, IDI1, FDPS, LSS, and DHCR7. CONCLUSIONS: The ruminal fermentation and feed efficiency results suggest that different mechanisms of energy utilization might occur in heifers fed different F:C diets with similar levels of ME intake. Increased cholesterol synthesis from acetate might be responsible for the reduced efficiency of energy utilization in heifers fed high-forage diets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".