Relationship between plasma asprosin, dry matter intake, and plasma glucose at different stages of lactation
Bibliographic record
Abstract
In postpartum dairy cows, dry matter intake (DMI) decreases dramatically, resulting in reduced glucose production and negative energy balance (NEB). Asprosin is a centrally acting orexigenic protein hormone secreted by adipose tissue, and it promotes glucose production in the liver. However, the effects of asprosin on hepatic glucose output in primary bovine hepatocytes, as well as the relationship between plasma asprosin and dry matter intake at different stages of lactation, have not yet been reported. Our results demonstrated that fibrillin 1 (FBN1) exhibited significantly higher mRNA expression in the mammary gland and adipose tissue. The bovine His-asprosin proteins were > 90% pure, as confirmed by Coomassie Blue-stained SDS-PAGE gel analysis. Asprosin increased (p = 0.031) the mRNA expression of phosphoenolpyruvate carboxykinase 2 (PCK2) in primary bovine hepatocytes compared to the control group. Remarkably, glucose output (p = 0.03) in the primary bovine hepatocytes exposed to asprosin was higher than that in the control group. In addition, asprosin was found to promote PKA activity in primary bovine hepatocytes. The postpartum dairy cows exhibited significantly lower plasma asprosin levels compared to those at 110 and 230 days relative to parturition (p < 0.01). Notably, plasma asprosin levels were positively correlated with DMI at different stages of lactation. These findings indicate that increased levels of circulating asprosin should be considered a novel resolution strategy for improving DMI and addressing negative nutrient balance during the postpartum period.
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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) | 0.001 | 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".