Serum Anti-Müllerian Hormone and Cytokine Profiling of Bubalus bubalis (Murrah buffalo) Calves for Puberty Prediction
Bibliographic record
Abstract
The present study incorporated ten buffalo calves aged 0 to 6 months, with an average weight of 35 kg, and ten buffalo heifers aged 12 months, with an average weight of 200 kg, to study the cytokine and AMH profile in relation to pubertal advancement. Venous blood samples (5ml) were collected from buffalo calves on the day of birth (day 0), day 15, day 30, day 60, day 90, day 120, day 150, and day 180. A single blood sample was collected from Buffalo heifers (1 year age). Cytokines: IFN-γ, IL-6, IL-1, IL-13, TNF-α, and TGF-β, and anti-Müllerian hormone: AMH were estimated using respective ELISA kits. At birth, cytokine levels in serum showed a varied pattern, with lower levels of IFN-γ, IL-6, and IL-13, whereas IL-1, TNF-α, and TGF-β were higher. Throughout the study, IFN-γ, IL-13, and TGF-β levels remained relatively stable, whereas IL-1, IL-6, and TNF-α increased notably by day 180. IL-1, TNF-α, and IL-6 levels were higher (P<0.01) from birth to 180 days as well as on day 365. AMH levels remained consistent from birth to 180 days, indicating a marked increase at Day 15 (33.49 ± 12.63 ng/L), followed by a decline to 4.60 ± 1.55 ng/Lat the end of the first year. Implications of the Karl Pearson correlation coefficient revealed a negative correlation between AMH levels and IFN-γ and TNF-α. AMH was positively correlated with IL 13 and TGF-β. Hence, it was concluded that IFN-γ and TNF-α are predictive markers for a reduction in AMH levels and hence, setting up puberty in buffalo heifers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".