A molecular approach: understanding the variability in energy expenditure of cattle
Bibliographic record
Abstract
Individual animal variability in energy expenditure may be an important factor that affects the overall efficiency of animal production. Although these variations in energy expenditure have been observed, the genetic and physiologic processes involved in the regulation of such variations is not well understood. Our objective was to examine the variability in metabolism and to evaluate putative linkages between energy metabolism and leptin receptor and neuropeptide Y (NPY) receptor gene expression in target tissues of cattle. A comparison of metabolic rates was made between 36 steers, comprised of 12 of each of three breeds; Charolais, Aberdeen Angus and Brahman/Angus cross, during feeding at two levels of intake (1.2X maintenance, 2.2X maintenance) of a 90% barley concentrate, 10% hay roughage diet. Indirect, open circuit calorimetry was utilized to measure metabolic rate over two days in each period in each animal. We collected Biceps femoris (BF) muscle samples at slaughter, and immediately snap-froze them in liquid nitrogen. The BF represents a large mixed fibre type muscle. Subsequent to the extraction of total RNA, we analysed the relative expression of our receptor genes through RT-PCR, using specific oligo-nucleotide primer sets, in each of our animal’s muscle samples. Our expression levels were standardized using G3PDH as our internal control in our multiplex PCR reactions. Metabolic rates for Charolais ranged from 0.50 MJ/(d·kg0.75) to 0.73 MJ/(d·kg0.75) those of Angus ranged from 0.47 MJ/(d·kg0.75) to 0.73 MJ/(d·kg0.75) and those of Brahman/Angus ranged from 0.45 MJ/(d·kg0.75) to 0.69 MJ/(d·kg0.75). This demonstrates that although breed differences in energy expenditure are small, the variability between individual animals within a breed and feeding level, can be as much as 31%, based on extremes. Our results demonstrate that both receptor genes are expressed in BF, and that these expression levels show large (up to ten fold) variations between animals. Level of expression of the leptin receptor gene and that of the NPY receptor gene, within an animal, were highly correlated (r=0.91). Regression of these receptor gene expressions on several indices of metabolic efficiency showed low positive correlations.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".