Associations of cytological endometritis with insulin resistance and gene expression in adipose tissue of transition dairy cows
Bibliographic record
Abstract
Cytological endometritis (CYTO), characterized by an elevated number of polymorphonuclear neutrophils in the endometrium, negatively affects reproductive outcomes in dairy cows. In this study, we investigated the associations between insulin resistance (IR) during the transition period and the occurrence of CYTO. We measured insulin sensitivity and adipose tissue gene expression on d -21 and d 21 and a selection of blood metabolites weekly from d -21 to d 42 relative to calving of 39 Holstein dairy cows. Study groups were formed based on the CYTO status on d 42. Our findings indicate that cows with CYTO had a greater insulin response to a glucose infusion prepartum, suggesting a link between prepartum IR and the development of CYTO. Postpartum, CYTO cows showed lower insulin and higher nonesterified fatty acids concentrations in plasma. Additionally, CYTO cows showed altered gene expression in subcutaneous adipose tissue, with increased mRNA levels of hormone-sensitive lipase (LIPE) and insulin receptor (INSR), and a tendency for higher glucose transporter 4 (GLUT4) protein levels. These results suggest that metabolic stress and IR are interconnected, contributing to the development of CYTO. The study underscores the importance of managing metabolic health before calving to prevent CYTO and improve reproductive performance in dairy cows.
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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 | 0.000 |
| 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) | 0.000 | 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".