GROWTH AND DEVELOPMENT SYMPOSIUM: Impacts of inflammation on cattle growth and carcass merit1,2
Bibliographic record
Abstract
Inflammation caused by bovine respiratory disease (BRD) continues to be one of the greatest challenges facing beef cattle producers and feedlot managers. Inflammation decreases DMI, ADG, and G:F in feedlot calves, decreasing growth rate and increasing days on feed, which results in economic losses during the feeding period. During the past decade, marketing of feedlot animals has changed from selling cattle on a live basis to a grid-based marketing system. When cattle are marketed on a live basis, the economic effects of BRD stop at increased health cost and decreased feedlot performance, carcass weight, and death loss. However, when cattle are marketed in a grid-based system, inflammation has the potential to also affect carcass cutability and quality. The effects of inflammation on feedlot cattle in regards to performance are well understood; however, specific effects on cattle growth and ultimately carcass merit are not as well described. Recent studies in feedlot cattle have indicated that the incidence of BRD decreases both HCW and marbling; however, mechanisms are not understood. Research in other species has demonstrated that during the acute phase response, pro-inflammatory cytokines promote skeletal muscle catabolism to supply AA and energy substrates for immune tissues. Further, during this early immune response, the liver changes its metabolic priorities to the production of acute phase proteins for use in host defense. Together these dramatic shifts in systemic metabolism may explain the detrimental effects on performance and carcass traits commonly associated with BRD in feedlot calves. Moreover, recent studies relative to human health have revealed complex multilevel interactions between the metabolic and immune systems, and highlighted inflammation as being a significant contributor to major metabolic diseases. The objective of this paper is to review data to help explain the economical and physiological effects of inflammation on cattle growth and carcass merit.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.011 |
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".