PSXIII-B-13 Investigation of Genetic Markers That may be Associated with Responses of Dairy Cows to Ketosis Treatment
Bibliographic record
Abstract
Abstract The objective of this study was to investigate genetic markers associated with different responses to ketosis treatment when compared to ketosis-free Holstein cows. Holstein cows (N=964) from four commercial farms, located in New York State/USA, were included in a randomized controlled trial for ketosis treatment for a period of 2 months (5/19/2019 to 7/20/2019). The cows were screened for BHB (β-hydroxybutyrate ≥1.2 mmol/L) in the first two weeks postpartum (0-14 DIM). Cows with negative results (BHB < 1.2 mmol/L) in the first week (0-7 DIM) were retested in the second week of lactation (8-14 DIM), if negative at both screening tests, cows were categorized as ketosis-free (control group). The cows with positive results in the screening period (0-14 DIM) were treated as detailed in Capel et al. (2020) and reassessed in the following two weeks. According to the cow`s response to the treatment, they were classified as CURED, RECURRENT, SEVERE, and CHRONIC. Out of the 964 cows, 489 were genotyped using the 50k Illumina Bead Chip array. A mixed linear model-based genome-wide association study (GWAS) was carried out in GCTA software. The GWAS was performed for each ketosis outcome compared to the control group. Several potential genomic regions were identified on chromosomes 1, 3, 4, 7, 8, 14, and 17. Overall, the highlighted genes included COL1A1, NEDD4l, DIP2A, CARD6, ITGA7, and MMP19, which have shared functions with genes previously associated with ketosis (e.g., CASP9, ACACA, and Interleukins) in pathways such as the transport of glucose and other sugars, bile salts and organic acids, metal ions and amine compounds, Cell adhesion_ECM remodeling Pathway, TGF-beta signaling, Nucleotide-binding Oligomerization Domain (NOD), and Mesodermal commitment. These findings contribute to a better understanding of the mechanisms that trigger response to ketosis treatment and warrant further investigation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".