Evaluations of Ovarian and Luteal Blood Flow Waveform Patterns in Buffalos Subjected to OvSynch Protocol in Cold and Hot Seasons
Bibliographic record
Abstract
This current study aimed to determine ovarian and luteal blood flow waveform patterns in buffalos synchronized using OvSynch protocol in cold and hot seasons. Six cyclic buffalo cows aged 6±0.5 years old, having a weight of 400 ± 50 kg, were scanned daily along three successive estrous cycles transrectally by Doppler ultrasonography to evaluate the normal ovarian hemodynamic during the normal spontaneous ovulation and before the start of experiments. Buffaloes were synchronized with gonadotropin[GnRH] –prostaglandin[P] –gonadotropin (GPG) protocol in which animals received 10μg of GnRH on day ??, 0.250μg of PGF2α on day 7, and another dose of 10μg of GnRH was administered 48h after the PGF2α injection. Blood sampling and ovarian ultrasound examinations (color and spectral Doppler modes) were conducted on the day of the estrous and luteal phases. Results revealed that peak systolic velocity waveform (PSV) was significantly (P<0.05) increased in the cold season compared to the hot season. The Luteal blood flow after the end of OvSynch protocol on days (5,7,9, and 11) was significantly increased in the cold season than that in the hot one. The serum levels of estradiol (E2) and nitric oxide (NO) after the second GnRH injection in the OvSynch protocol were significantly (P<0.05) elevated in the cold season as compared to the hot one.
 Moreover, the progesterone (P4) levels had risen in OvSynch-treated buffaloes on days 5,7,9, and 11 of the cycle in the cold season compared to the hot one. Conclusion: In the cold season, ovarian hemodynamics was significantly improved compared to the hot one; this may influence the reproductive efficiency of buffaloes. Further studies were needed to prove it.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".