Evaluation of the levels of Leptin, Beta hydroxyl butyrate, Glucose, Cholesterol and Triglyceride in serum of Holstein cows with sub clinical ketosis
Bibliographic record
Abstract
Leptin hormone is secreted from the white adipocytes of adipose tissue and its levels increase with the increase in size of the adipose tissue. One of the most important actions of this hormone is the regulation of body metabolism by consuming adipose tissue and production of energy. The objective of this study was determination of Leptin and BHB, glucose, cholesterol and triglyceride levels in healthy Holstein cows and cows with Sub clinical Ketosis and the determination of the prevalence of Sub clinical Ketosis, using BHB level in blood serum as the gold standard. In this survey 7 dairy farms were chosen in Shahriar, (Tehran province), Samples were taken from 100 cows at two periods: 1) last week of pregnancy (dry period), 2) The same cows at 2 months after parturition. Serum samples were harvested and leptin levels were measured using DBC ELISA kit,Canada, BHB levels were measured using RANBUT kits and glucose, cholesterol and triglyceride levels were measured by commercial kits (ziest chem) and spectrophotometer. In this study, the prevalence of Sub clinical Ketosis, using the 1/2, 1/4, 1/7 mmol BHB, as the cut point was calculated as 18%, 14% and 4% respectively. Leptin levels decreased significantly after parturition in healthy cows and those affected by subclinical ketosis. There was a significant correlation between leptin and glucose (r=0.53) and BHB and glucose (r= -0.27) in pre parturient group of cows. In the group of cows 2 month after parturition, there was a significant correlation between leptin and glucose (r=0.65), BHB and triglyceride (r=0.97) and BHB and glucose (r= -0.64). In the group affected by subclinical ketosis, a significant correlation was observed between leptin and glucose (r=0.72), BHB and glucose (r=-0.38), BHB and triglyceride (r=0.85) and BHB and cholesterol (r=0.64).
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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 | 0.001 | 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".