Short communication: Cytokine profiles from blood mononuclear cells of dairy cows classified with divergent immune response phenotypes
Bibliographic record
Abstract
Genetic selection for enhanced immune response has been shown to decrease disease occurrence in dairy cattle. Cows can be classified as high (H), average, or low responders based on antibody-mediated immune response (AMIR), predominated by type-2 cytokine production, and cell-mediated immune response (CMIR) through estimated breeding values for these traits. The purpose of this study was to identify in vitro tests that correlate with in vivo immune response phenotyping in dairy cattle. Blood mononuclear cells (BMC) isolated from cows classified as H-AMIR and H-CMIR through estimated breeding values for immune response traits were stimulated with concanavalin A (ConA; Sigma Aldrich, St. Louis, MO) and gene expression, cytokine production, and cell proliferation was determined at multiple time points. A repeated measures model, which included the effects of immune response group, parity, and stage of lactation, was used to compare differences between immune response phenotype groups. The H-AMIR cows produced more IL-4 protein than H-CMIR cows at 48 h; however, no difference in gene expression of type-2 transcription factor GATA3 or IL4 was noted. The BMC from H-CMIR cows had increased production of IFN-γ protein at 48, 72, and 96 h compared with H-AMIR animals. Further, H-CMIR cows had increased expression of the IFNG gene at 16, 24, and 48 h post-treatment with ConA, although expression of the type-1 transcription factor gene TBX21 did not differ between immune response groups. Although proliferation of BMC increased from 24 to 72 h after ConA stimulation, no differences were found between the immune response groups. Overall, stimulation of H-AMIR and H-CMIR bovine BMC with ConA resulted in distinct cytokine production profiles according to genetically defined groups. These distinct cytokine profiles could be used to define disease resistance phenotypes in dairy cows according to stimulation in vitro; however, other immune response phenotypes should be assessed.
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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 | 0.000 | 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) | 0.002 | 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".