PSXI-8 Heritability estimates of antibody- and cell-mediated immune response in north American angus beef cattle
Bibliographic record
Abstract
Abstract Including immune response traits in breeding programs has been suggested as a solution to improve overall animal health and enhance disease resistance but is not yet available for Angus cattle in North America. One way to measure immune response is to use the High Immune Response (HIR™) technology, which identifies animals with superior heritable immunity by evaluating antibody-mediated (AMIR) and cell-mediated (CMIR) immune response, allowing for the calculation of an estimated breeding value for total adaptive immune response for each animal. Before HIR™ can be included in beef cattle breeding programs, genetic parameters, including heritability, must be estimated for the traits involved. The objective of this study was to estimate a preliminary heritability for AMIR and CMIR in North American Angus beef cattle. On day 0 of the phenotyping protocol, cattle were immunized intramuscularly with a preparation of type 1 (CMIR) and type 2 (AMIR) antigens with adjuvant. On day 14, cattle received an intradermal injection of 0.1 mL of the CMIR test antigen in the right tail fold, and 0.1 mL PBS in the left tail fold. Change in cutaneous double skinfold thickness after 24 hours was used to assess CMIR. Blood was collected on days 0 and 14 to evaluate serum antibody to the type 2 antigen by ELISA to quantify AMIR. Heritability estimates were calculated for Canada and the USA separately, and then for both countries combined using single-trait animal models in ASReml and are presented in Table 1. The results of this study indicate that the heritabilities of AMIR and CMIR are moderate and emphasize the potential for its inclusion into Angus breeding schemes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".