Peripartal alterations of calcitonin gene‐related peptide and minerals in dairy cows affected by milk fever
Bibliographic record
Abstract
BACKGROUND: Milk fever, a metabolic disease of dairy cattle, is associated with perturbations of calcium homeostasis, the pathogenesis of which is not yet completely understood. OBJECTIVE: The aim of this study was to investigate plasma concentrations of calcitonin gene-related peptide and selected minerals and metabolites in periparturient cows with and without milk fever. METHODS: Plasma concentrations of calcitonin gene-related peptide, as well as calcium, phosphate, magnesium, iron, glucose, lactate, and cortisol, were determined in multiple plasma samples from Jersey cows with and without spontaneous milk fever. RESULTS: Cows affected by milk fever (n = 5) had lower concentrations of calcitonin gene-related peptide (P = .038) and inorganic phosphate (P < .001) in plasma than did the controls (n = 5). Also, these cows tended to have lower calcium concentrations (P = .071). Magnesium, iron, lactate, glucose, and cortisol concentrations were comparable between both groups of cows (P > .10). Around the day of calving, plasma concentrations of lactate, glucose, and cortisol increased and the concentration of iron decreased in all cows (P ≤ .01). CONCLUSIONS: Despite the limited number of cows evaluated, this report is the first to indicate lowered concentrations of calcitonin gene-related peptide as part of the metabolic changes during milk fever in cows. Further work with a larger cohort of animals is warranted to understand the precise role of calcitonin gene-related peptide and the potential associations with disturbances in plasma minerals typically observed during milk fever.
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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".