Decreased lactose percentage in milk associated with quarter health disorder and hyperketolactia, a proxy for negative energy balance, in dairy cows
Bibliographic record
Abstract
Several studies have described variations in lactose content ( LC ) in dairy cows during udder quarter health disorder or negative energy balance ( NEB ). However, their joint effects on LC have never been described. This was the aim of a longitudinal observational study performed on 5 Quebec dairy farms using automatic milking systems. Quarter milk samples were collected every 14 d from 5 to 300 DIM. Quarter health status was described by combining SCC level (SCC - or SCC + : < or ≥100,000 cells/mL) and infectious status (Patho - or Patho + : presence or absence of pathogens on a milk culture). Cows with NEB in early lactation (DIM <70) were identified using milk β-hydroxybutyrate ( BHB ) content: 0.15 mM=BHB-; 0.15 – 0.19 mM=BHB+; > 0.19 mM=BHB++. A total of 14,505 quarter cisternal milk samples were collected from 380 lactating cows. The quarter LC was analyzed using a mixed linear regression model with the following fixed effects: quarter health status, parity, time interval between last milking and sampling, quarter milk yield (in kg/d), DIM, and herd. A random quarter intercept with a repeated measures correlation structure and a cow random intercept were also specified. The LC of SCC + quarters was lower (−0.17 ± 0.013% pts) compared with LC of SCC - quarters for both primiparous and multiparous cows. Over the 162 bacterial species identified, only 8 species had a prevalence greater than 4.0%, and just 5 of them were associated with a reduction in LC: Staphylococcus aureus, Staph. chromogenes , Streptococcus dysgalactiae, Staph. epidermidis, and Staph. simulans . Cows identified as BHB+ and BHB++ in early lactation had a lower LC (−0.05 ± 0.019% and −0.13 ± 0.020% pts, respectively) compared with BHB- cows. For BHB++ cows, in both parity groups the decrease in LC (−0.20 ± 0.025% pts) was higher in SCC + quarters compared with SCC - quarters. Moreover, the additive effect of the quarter health status and NEB on milk LC was greater with larger increases in BHB. Our findings highlight the necessity to jointly take into consideration both quarter health status and milk BHB concentration when using LC as a biomarker for NEB.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".