Genetic parameters for natural antibodies and associations with specific antibody and mastitis in Canadian Holsteins
Bibliographic record
Abstract
The objectives of this study were to evaluate (1) natural antibodies (NAb) in Canadian Holstein cows, (2) genetic parameters and associations between NAb and specific antibody (SpAb), and (3) the association of NAb with clinical mastitis and differences in incidence rates of clinical mastitis (IRCM) among cows classified as high, average, or low responders for NAb. Natural antibodies (IgG and IgM) to keyhole limpet hemocyanin and SpAb to a type 2 test antigen were measured on 451 Holsteins from 41 herds across Canada. A series of uni- and tri-variate linear animal models were used to estimate genetic parameters and breeding values for NAb and SpAb. The models included the fixed effects of parity and stage of lactation and the random effects of herd-technician, animal, and residual. Using estimated breeding values for NAb, cows were classified as high, average, or low responders and phenotypic associations with the IRCM were investigated and a logistic regression performed. The estimated heritability was 0.27 for SpAb, and was 0.32 and 0.18 for NAb of the IgG and IgM isotypes, respectively. No significant genetic correlations were found between SpAb and NAb. Although no significant differences in the IRCM were found when cows were classified based on NAb IgG, cows classified as high responders for NAb IgM tended to have a lower IRCM compared with other cows. Immunoglobulin-M was associated with a decreased risk of clinical mastitis (odds ratio=0.958). Results of this study suggest the potential to use NAb IgM as an additional tool to select for disease resistance in cattle, but results need to be validated with a larger sample size.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".