Biochemical Compositions in the Follicular Fluid of Different Follicle Groups and Their Relationship with the Blood Concentrations in Dromedary Camels
Bibliographic record
Abstract
Metabolic profile changes of the follicular fluid of the growing follicles can be used as an indirect indicator of the oocyte and granulosa cells quality. The aim of this study was to investigate the biochemical compositions of follicular fluid collected from follicles at different stages of growth and their relationship with that of blood serum in Dromedary camel. Ovaries were colleceted from local slaughterhouse (Oniza, KSA). Soon after slaughtering, blood samples were collected from Dromedary camel (n = 20) and follicular fluid was aspirated from three different groups of non-atretic follicles (4–6)mm, 6–8mm and 10–20mm diameter). Follicular samples were pooled by maintaining the follicular sizes. Concentrations of glucose, cholesterol, triglycerides, urea, total protein, lactate dehydrosenase (LDH), cortisol, triiodothyronine (T3), insulin-like growth factor-1 (IGF-1) and non-esterified fatty acids (NEFA) were assayed in each serum and follicular fluid sample. The concentrations of glucose, cholesterol, triglycerides, total protein, LDH, T3, IGF-1 and NEFA decreased in the follicular fluid irrespective of follicular sizes and increasing in trend for urea in comparison with blood serum. There was a significant concentration gradient for IGF-1 in small follicular group compared to large or medium groups. Our data from the present study suggest that the oocyte and the granulosa cells of Dromedary she camel develop in a biochemical environment that does not have remarkable changes from small to large follicles except for IGF-1. In conclusion, the above-mentioned metabolic changes in the growing follicle is related to blood metabolic changes and, therefore, may be used in determining follicular dominance, oocyte and granulosa cells quality in Dromedary camel.
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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) | 0.001 | 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".